diff --git a/data/mibig.csv b/data/mibig.csv
new file mode 100644
index 0000000..4f3da13
--- /dev/null
+++ b/data/mibig.csv
@@ -0,0 +1,608 @@
+BGC,ORF,A-ID,M domain,L-/D- (E domain),PRED_TOP5,START_POS,END_POS,STRAND,STRUCTURE ID,rBan STRUCTURE,rBan VERTEX,rBan AA-ID,rBan STRUCT_CONFIGURATION,rBan AA,STRUCTURE,VERTEX,AA-ID,MODIFICATION,AA
+BGC0000300,-,-,-,-,-,-,-,-,BGC0000300,"0,1,2,3,4,5,6",0,Sal,NA,sal,,,,,
+BGC0000300,orf00005,A1,FALSE,L,cys(90.0);orn(60.0);asn(50.0);asp(50.0);gln(50.0),5185.0,8539.0,-,BGC0000300,"0,1,2,3,4,5,6",1,@D-Ser,D,ser,"0,1,2,3,4,5",0,Ser,,
+BGC0000300,orf00006,A1,FALSE,L,ser(95.0);thr(65.0);allothr(65.0);hpg(65.0);dab(60.0),8532.0,15621.0,-,BGC0000300,"0,1,2,3,4,5,6",2,@L-Ser,L,ser,"0,1,2,3,4,5",1,Ser,,
+BGC0000300,orf00006,A2,FALSE,D,ser(95.0);thr(65.0);allothr(65.0);hpg(65.0);dab(60.0),8532.0,15621.0,-,BGC0000300,"0,1,2,3,4,5,6",3,@D-Ser,D,ser,"0,1,2,3,4,5",2,Ser,,
+BGC0000300,orf00007,A1,FALSE,D,bmt(60.0);dht(50.0);cit(50.0);end(50.0);uda(50.0),15613.0,19819.0,-,BGC0000300,"0,1,2,3,4,5,6",6,OH-cOrn,NA,orn,"0,1,2,3,4,5",5,hOrn,,
+BGC0000300,orf00008,A1,FALSE,L,ser(95.0);thr(65.0);allothr(65.0);hpg(65.0);dab(60.0),19803.0,26805.0,-,BGC0000300,"0,1,2,3,4,5,6",4,@L-Ser,L,ser,"0,1,2,3,4,5",3,Ser,,
+BGC0000300,orf00008,A2,FALSE,D,orn(100.0);arg(60.0);lys(60.0);asp(50.0);met(50.0),19803.0,26805.0,-,BGC0000300,"0,1,2,3,4,5,6",5,@D-Fo-OH-Orn,D,orn,"0,1,2,3,4,5",4,hfOrn,,
+BGC0000300,orf00012,A1,FALSE,L,dhb(85.0);sal(80.0);phe(40.0);tyr(40.0);phg(40.0),29168.0,30716.0,+,BGC0000300,,,,,,,,,,
+BGC0000305,orf00003,A1,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),1665.0,8055.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",0,@D-Leu,D,leu,"10,9,8,7,6,5,4,3,2*1,0",0,Leu,,D-Leu
+BGC0000305,orf00003,A2,FALSE,D,asp(100.0);asn(75.0);gln(75.0);glu(75.0);arg(55.0),1665.0,8055.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",1,@D-Asp,D,asp,"10,9,8,7,6,5,4,3,2*1,0",1,Asp,,D-Asp
+BGC0000305,orf00004,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),8236.0,21253.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",2,@D-aThr/Thr,D,thr,"10,9,8,7,6,5,4,3,2*1,0",2,Thr,,D-allo-Thr
+BGC0000305,orf00004,A2,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),8236.0,21253.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",3,@D-Leu,D,leu,"10,9,8,7,6,5,4,3,2*1,0",3,Leu,,D-Leu
+BGC0000305,orf00004,A3,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),8236.0,21253.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",4,@D-Leu,D,leu,"10,9,8,7,6,5,4,3,2*1,0",4,Leu,,D-Leu
+BGC0000305,orf00004,A4,FALSE,D,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),8236.0,21253.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",5,@D-Ser,D,ser,"10,9,8,7,6,5,4,3,2*1,0",5,Ser,,D-Ser
+BGC0000305,orf00005,A1,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),21249.0,39093.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",6,Leu,NA,leu,"10,9,8,7,6,5,4,3,2*1,0",6,Leu,,L-Leu
+BGC0000305,orf00005,A2,FALSE,D,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),21249.0,39093.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",7,@D-Ser,D,ser,"10,9,8,7,6,5,4,3,2*1,0",7,Ser,,D-Ser
+BGC0000305,orf00005,A3,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),21249.0,39093.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",8,@L-Ile/aIle,L,ile,"10,9,8,7,6,5,4,3,2*1,0",8,Ile,,L-Ile
+BGC0000305,orf00005,A4,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),21249.0,39093.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",9,@L-Ile/aIle,L,ile,"10,9,8,7,6,5,4,3,2*1,0",9,Ile,,L-Ile
+BGC0000305,orf00005,A5,FALSE,L,asp(100.0);asn(75.0);gln(75.0);glu(75.0);arg(55.0),21249.0,39093.0,+,BGC0000305,"#,0,1,2,3,4,5,6,7,8,9",10,@L-Asp,L,asp,"10,9,8,7,6,5,4,3,2*1,0",10,Asp,,L-Asp
+BGC0000306,orf00001,A1,TRUE,D,ser(100.0);thr(65.0);hpg(65.0);dab(60.0);dpg(60.0),0.0,10458.0,-,BGC0000306,"#,0,1,2,3,4",0,@D-NMe-Ser,D,ser+MT,"0,1,2,3,4,5",0,Ser,,
+BGC0000306,orf00001,A2,FALSE,D,ala(90.0);gly(80.0);leu(70.0);val(70.0);ala-d(65.0),0.0,10458.0,-,BGC0000306,"#,0,1,2,3,4",1,@D-Ala,D,ala,"0,1,2,3,4,5",1,Ala,,
+BGC0000306,orf00003,A1,FALSE,L,gly(95.0);ala(70.0);ile(65.0);val(65.0);leu(60.0),12314.0,25208.0,+,BGC0000306,"#,0,1,2,3,4",2,Gly,NA,gly,"0,1,2,3,4,5",2,Gly,,
+BGC0000306,orf00003,A2,TRUE,L,hpg(95.0);dpg(90.0);dhpg(80.0);dhp(80.0);ser(65.0),12314.0,25208.0,+,BGC0000306,"#,0,1,2,3,4",3,@L-NMe-Hpg,L,hpg+MT,"0,1,2,3,4,5",3,Hpg,,
+BGC0000306,orf00003,A3,FALSE,L,ala(90.0);gly(80.0);leu(70.0);val(70.0);ala-d(65.0),12314.0,25208.0,+,BGC0000306,"#,0,1,2,3,4",4,@L-Ala,L,ala,"0,1,2,3,4,5",4,Ala/Gly,,
+BGC0000306,orf00003,A4,FALSE,L,tyr(95.0);bht(95.0);phe(85.0);trp(70.0);uda(60.0),12314.0,25208.0,+,BGC0000306,"#,0,1,2,3,4",5,@L-Tyr,L,tyr,"0,1,2,3,4,5",5,Tyr,,
+BGC0000307,orf00001,A1,FALSE,L,ile(65.0);leu(65.0);val(65.0);gly(60.0);ala(55.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",-,-,-,-,"0,1,2,3,4,5,6,7,8*",0,Hmp,,DHmp
+BGC0000307,orf00001,A2,TRUE,L,val(95.0);leu(75.0);ala(70.0);pro(70.0);abu(70.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",1,@L-NMe-Val,L,val+MT,"0,1,2,3,4,5,6,7,8*",1,Val,Methylation,MeVal
+BGC0000307,orf00001,A3,FALSE,L,val(55.0);ala(50.0);leu(50.0);ser(50.0);abu(50.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",2,@L-Phe,L,phe,"0,1,2,3,4,5,6,7,8*",2,Phe,,Phe
+BGC0000307,orf00001,A4,TRUE,L,val(55.0);ala(50.0);leu(50.0);ser(50.0);abu(50.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",3,@L-NMe-Phe,L,phe+MT,"0,1,2,3,4,5,6,7,8*",3,Phe,Methylation,MePhe
+BGC0000307,orf00001,A5,FALSE,L,dab(60.0);aeo(40.0);apa(40.0);ser(35.0);ala(30.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",4,@L-Pro,L,pro,"0,1,2,3,4,5,6,7,8*",4,Pro,,Pro
+BGC0000307,orf00001,A6,FALSE,L,leu(80.0);ile(75.0);val(75.0);ala(65.0);gly(65.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",5,@D-Ile/aIle,D,ile,"0,1,2,3,4,5,6,7,8*",5,alle,,L-allo-Ile
+BGC0000307,orf00001,A7,TRUE,L,val(95.0);leu(75.0);ala(70.0);pro(70.0);abu(70.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",6,@L-NMe-Val,L,val+MT,"0,1,2,3,4,5,6,7,8*",6,Val,Methylation,MeVal
+BGC0000307,orf00001,A8,FALSE,L,leu(90.0);val(80.0);bmt(80.0);ala-d(70.0);ile(70.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",7,@L-Leu,L,leu,"0,1,2,3,4,5,6,7,8*",7,Leu,,Leu
+BGC0000307,orf00001,A9,TRUE,L,val(95.0);leu(75.0);ala(70.0);pro(70.0);abu(70.0),505.0,35485.0,+,BGC0000307,"#,0,1,2,3,4,5,6,7",8,@L-bOH-NMe-Val,L,val+MT+unk,"0,1,2,3,4,5,6,7,8*",8,Val,Methylation,L-OH-MeVal
+BGC0000310,orf00003,A1,FALSE,L,ile(100.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),1492.0,17218.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",0,Ile/aIle,NA,ile,"11,10,9,8,7,6,5*4,3,2,1,0",0,Ile,,
+BGC0000310,orf00003,A2,FALSE,L,cys(100.0);ser(60.0);ala(55.0);gly(55.0);thr(50.0),1492.0,17218.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",1,Cys,NA,cys,"11,10,9,8,7,6,5*4,3,2,1,0",1,Cys,,
+BGC0000310,orf00003,A3,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),1492.0,17218.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",2,Leu,NA,leu,"11,10,9,8,7,6,5*4,3,2,1,0",2,Leu,,
+BGC0000310,orf00003,A4,FALSE,D,glu(100.0);gln(85.0);asp(75.0);uda(70.0);asn(65.0),1492.0,17218.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",3,Glu,NA,glu,"11,10,9,8,7,6,5*4,3,2,1,0",3,D-Leu,,
+BGC0000310,orf00003,A5,FALSE,L,ile(100.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),1492.0,17218.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",4,Ile/aIle,NA,ile,"11,10,9,8,7,6,5*4,3,2,1,0",4,Ile,,
+BGC0000310,orf00004,A1,FALSE,L,lys(100.0);arg(75.0);orn(70.0);end(70.0);glu(55.0),17344.0,25153.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",5,Lys,NA,lys,"11,10,9,8,7,6,5*4,3,2,1,0",5,Lys,,
+BGC0000310,orf00004,A2,FALSE,D,orn(100.0);dab(80.0);arg(75.0);lys(70.0);glu(55.0),17344.0,25153.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",6,Orn,NA,orn,"11,10,9,8,7,6,5*4,3,2,1,0",6,D-Orn,,
+BGC0000310,orf00005,A1,FALSE,L,ile(100.0);leu(75.0);val(70.0);abu(70.0);ala(65.0),25257.0,44337.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",7,Ile/aIle,NA,ile,"11,10,9,8,7,6,5*4,3,2,1,0",7,Ile,,
+BGC0000310,orf00005,A2,FALSE,D,phe(100.0);tyr(85.0);bht(85.0);trp(75.0);uda(60.0),25257.0,44337.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",8,Phe,NA,phe,"11,10,9,8,7,6,5*4,3,2,1,0",8,D-Phe,,
+BGC0000310,orf00005,A3,FALSE,L,tyr(85.0);his(75.0);bht(70.0);phe(65.0);trp(65.0),25257.0,44337.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",9,His,NA,his,"11,10,9,8,7,6,5*4,3,2,1,0",9,His,,
+BGC0000310,orf00005,A4,FALSE,D,asp(100.0);asn(85.0);gln(60.0);glu(60.0);lys(55.0),25257.0,44337.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",10,Asp,NA,asp,"11,10,9,8,7,6,5*4,3,2,1,0",10,D-Asp,,
+BGC0000310,orf00005,A5,FALSE,L,asn(100.0);asp(85.0);glu(65.0);gln(60.0);aad(55.0),25257.0,44337.0,+,BGC0000310,"#,0,1,2,3,4,5,6,7,8,9,10",11,Asn,NA,asn,"11,10,9,8,7,6,5*4,3,2,1,0",11,Asn,,
+BGC0000312,orf00028,A1,FALSE,L,hyv(90.0);gly(65.0);val(60.0);ala(55.0);leu(55.0),21244.0,30685.0,+,BGC0000312,"#,0",0,Hiv,NA,hiv,"0,1,2,3,4,5,6,7*",0,D-Hiv (from L-val),,
+BGC0000312,orf00028,A1,FALSE,L,hyv(90.0);gly(65.0);val(60.0);ala(55.0);leu(55.0),21244.0,30685.0,+,BGC0000312,"#,0",0,Hiv,NA,hiv,"0,1,2,3,4,5,6,7*",2,D-Hiv (from L-val),,
+BGC0000312,orf00028,A1,FALSE,L,hyv(90.0);gly(65.0);val(60.0);ala(55.0);leu(55.0),21244.0,30685.0,+,BGC0000312,"#,0",0,Hiv,NA,hiv,"0,1,2,3,4,5,6,7*",4,D-Hiv (from L-val),,
+BGC0000312,orf00028,A1,FALSE,L,hyv(90.0);gly(65.0);val(60.0);ala(55.0);leu(55.0),21244.0,30685.0,+,BGC0000312,"#,0",0,Hiv,NA,hiv,"0,1,2,3,4,5,6,7*",6,D-Hiv (from L-val),,
+BGC0000312,orf00028,A2,TRUE,L,vol(60.0);cha(60.0);met(50.0);dht(50.0);bmt(50.0),21244.0,30685.0,+,BGC0000312,"#,0",1,NMe-Leu,NA,leu+MT,"0,1,2,3,4,5,6,7*",1,N-Me-Leu,,
+BGC0000312,orf00028,A2,TRUE,L,vol(60.0);cha(60.0);met(50.0);dht(50.0);bmt(50.0),21244.0,30685.0,+,BGC0000312,"#,0",1,NMe-Leu,NA,leu+MT,"0,1,2,3,4,5,6,7*",3,N-Me-Leu,,
+BGC0000312,orf00028,A2,TRUE,L,vol(60.0);cha(60.0);met(50.0);dht(50.0);bmt(50.0),21244.0,30685.0,+,BGC0000312,"#,0",1,NMe-Leu,NA,leu+MT,"0,1,2,3,4,5,6,7*",5,N-Me-Leu,,
+BGC0000312,orf00028,A2,TRUE,L,vol(60.0);cha(60.0);met(50.0);dht(50.0);bmt(50.0),21244.0,30685.0,+,BGC0000312,"#,0",1,NMe-Leu,NA,leu+MT,"0,1,2,3,4,5,6,7*",7,N-Me-Leu,,
+BGC0000323,-,-,,,,,,,BGC0000323,"#,0,1,2,3,4,5,6,7",0,@L-His,L,his,,,,,
+BGC0000323,orf00003,A1,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),1141.0,10639.0,+,BGC0000323,"#,0,1,2,3,4,5,6,7",1,@L-Leu,L,leu,"0,1,2,3,4,5,6,7",0,Leu,,
+BGC0000323,orf00003,A2,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),1141.0,10639.0,+,BGC0000323,"#,0,1,2,3,4,5,6,7",2,@L-Leu,L,leu,"0,1,2,3,4,5,6,7",1,Leu,,
+BGC0000323,orf00003,A3,FALSE,D,asp(75.0);gln(75.0);glu(75.0);asn(70.0);arg(60.0),1141.0,10639.0,+,BGC0000323,"#,0,1,2,3,4,5,6,7",3,@L-Gln,L,gln,"0,1,2,3,4,5,6,7",2,Gln,,
+BGC0000323,orf00004,A1,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),10635.0,28374.0,+,BGC0000323,"#,0,1,2,3,4,5,6,7",4,@L-Leu,L,leu,"0,1,2,3,4,5,6,7",3,Leu,,
+BGC0000323,orf00004,A2,FALSE,D,asp(80.0);asn(75.0);gln(75.0);glu(75.0);arg(60.0),10635.0,28374.0,+,BGC0000323,"#,0,1,2,3,4,5,6,7",5,@L-Gln,L,gln,"0,1,2,3,4,5,6,7",4,Gln,,
+BGC0000323,orf00004,A3,FALSE,L,val(85.0);ile(80.0);leu(75.0);abu(75.0);ala(65.0),10635.0,28374.0,+,BGC0000323,"#,0,1,2,3,4,5,6,7",6,@L-Val,L,val,"0,1,2,3,4,5,6,7",5,Val,,
+BGC0000323,orf00004,A4,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),10635.0,28374.0,+,BGC0000323,"#,0,1,2,3,4,5,6,7",7,@L-Leu,L,leu,"0,1,2,3,4,5,6,7",6,Leu,,
+BGC0000323,orf00004,A5,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),10635.0,28374.0,+,BGC0000323,"#,0,1,2,3,4,5,6,7",8,@L-Leu,L,leu,"0,1,2,3,4,5,6,7",7,Leu,,
+BGC0000330,orf00008,A1,FALSE,L,gly(95.0);ala(75.0);ile(70.0);leu(65.0);val(65.0),8970.0,12198.0,-,BGC0000330,"#,0,1,2,3",3,Gly,NA,gly,"0,1,2,3,4",3,Gly,,
+BGC0000330,orf00010,A1,FALSE,D,gln(65.0);glu(65.0);orn(65.0);asn(60.0);asp(60.0),13216.0,19243.0,-,BGC0000330,"#,0,1,2,3",4,@L-OH-Orn,L,orn+unk,"0,1,2,3,4",4,L-N-hydroxy-N-(3-hydroxybutyryl)-ornithine,,
+BGC0000330,orf00011,A1,FALSE,L,asp(95.0);asn(85.0);gln(60.0);glu(60.0);lys(50.0),19280.0,22244.0,-,BGC0000330,"#,0,1,2,3",2,@L-OH-Asp,L,asp+unk,"0,1,2,3,4",2,L-Asp,,
+BGC0000330,orf00012,A1,FALSE,L,asp(100.0);asn(90.0);glu(65.0);gln(60.0);cha(60.0),22368.0,31653.0,-,BGC0000330,"#,0,1,2,3",0,@L-OH-Asp,L,asp+unk,"0,1,2,3,4",0,L-Asp,,
+BGC0000330,orf00012,A2,FALSE,L,arg(50.0);asp(50.0);ser(50.0);orn(50.0);dab(50.0),22368.0,31653.0,-,BGC0000330,"#,0,1,2,3",1,@L-Dab,L,dab,"0,1,2,3,4",1,L-Dab,,
+BGC0000332,orf00003,A1,FALSE,L,gln(100.0);glu(80.0);asp(65.0);asn(60.0);arg(55.0),3991.0,7249.0,+,BGC0000332,"#,0,1,2,3,4,5",0,@L-Ile/aIle,L,ile,"6,5,4,3,2,1*0",0,Acylated-Gln,,
+BGC0000332,orf00004,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),7263.0,10569.0,+,BGC0000332,"#,0,1,2,3,4,5",1,@L-aThr/Thr,L,thr,"6,5,4,3,2,1*0",1,Thr,,
+BGC0000332,orf00005,A1,FALSE,L,arg(75.0);gln(75.0);lys(75.0);glu(70.0);uda(70.0),10565.0,24731.0,+,BGC0000332,"#,0,1,2,3,4,5",2,@L-Ile/aIle,L,ile,"6,5,4,3,2,1*0",2,Ile/Thr,,
+BGC0000332,orf00005,A2,FALSE,L,ahp(100.0);gln(70.0);glu(70.0);asp(65.0);asn(60.0),10565.0,24731.0,+,BGC0000332,"#,0,1,2,3,4,5",3,@L-Glu,L,glu,"6,5,4,3,2,1*0",3,Ahp,,
+BGC0000332,orf00005,A3,FALSE,L,phe(95.0);tyr(85.0);bht(80.0);trp(75.0);uda(70.0),10565.0,24731.0,+,BGC0000332,"#,0,1,2,3,4,5",4,@L-aThr/Thr,L,thr,"6,5,4,3,2,1*0",4,Phe,,
+BGC0000332,orf00005,A4,TRUE,L,bht(95.0);tyr(90.0);phe(85.0);trp(65.0);vol(60.0),10565.0,24731.0,+,BGC0000332,"#,0,1,2,3,4,5",5,@L-NMe-Phe,L,phe+MT,"6,5,4,3,2,1*0",5,Tyr+CH3+Cl,,
+BGC0000332,orf00007,A1,FALSE,L,ile(100.0);leu(85.0);val(85.0);abu(70.0);ala(65.0),26601.0,30858.0,+,BGC0000332,"#,0,1,2,3,4,5",6,@L-Glu,L,glu,"6,5,4,3,2,1*0",6,Gln/Ile,,
+BGC0000336,orf00045,A1,FALSE,L,tyr(75.0);bht(70.0);phe(65.0);trp(65.0);phg(55.0),51567.0,69060.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",0,@L-Trp,L,trp,"12,11,10,9,8,7,6,5,4*3,2,1,0",0,Trp,,
+BGC0000336,orf00045,A2,FALSE,D,asn(95.0);asp(90.0);gln(65.0);glu(65.0);orn(55.0),51567.0,69060.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",1,@D-Asn,D,asn,"12,11,10,9,8,7,6,5,4*3,2,1,0",1,D-Asn,,
+BGC0000336,orf00045,A3,FALSE,L,asn(95.0);asp(95.0);gln(65.0);glu(65.0);orn(60.0),51567.0,69060.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",2,@L-Asp,L,asp,"12,11,10,9,8,7,6,5,4*3,2,1,0",2,Asp,,
+BGC0000336,orf00045,A4,FALSE,L,thr(100.0);allothr(90.0);ser(80.0);dht(80.0);hpg(60.0),51567.0,69060.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",3,@L-aThr/Thr,L,thr,"12,11,10,9,8,7,6,5,4*3,2,1,0",3,Thr,,
+BGC0000336,orf00045,A5,FALSE,L,gly(95.0);ala(70.0);ile(65.0);val(65.0);leu(60.0),51567.0,69060.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",4,Gly,NA,gly,"12,11,10,9,8,7,6,5,4*3,2,1,0",4,Gly,,
+BGC0000336,orf00046,A1,FALSE,L,glu(65.0);arg(55.0);asp(55.0);gln(55.0);lys(50.0),69053.0,91073.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",5,@L-Orn,L,orn,"12,11,10,9,8,7,6,5,4*3,2,1,0",5,Orn,,
+BGC0000336,orf00046,A2,FALSE,L,asn(95.0);asp(95.0);gln(65.0);glu(65.0);orn(60.0),69053.0,91073.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",6,@L-Asp,L,asp,"12,11,10,9,8,7,6,5,4*3,2,1,0",6,Asp,,
+BGC0000336,orf00046,A3,FALSE,D,ala(85.0);gly(70.0);val(70.0);ala-d(65.0);ile(60.0),69053.0,91073.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",7,@D-Ala,D,ala,"12,11,10,9,8,7,6,5,4*3,2,1,0",7,D-Ala,,
+BGC0000336,orf00046,A4,FALSE,L,asn(95.0);asp(95.0);gln(65.0);glu(65.0);orn(60.0),69053.0,91073.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",8,@L-Asp,L,asp,"12,11,10,9,8,7,6,5,4*3,2,1,0",8,Asp,,
+BGC0000336,orf00046,A5,FALSE,L,gly(95.0);ala(65.0);leu(65.0);val(65.0);ala-d(55.0),69053.0,91073.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",9,Gly,NA,gly,"12,11,10,9,8,7,6,5,4*3,2,1,0",9,Gly,,
+BGC0000336,orf00046,A6,FALSE,D,ser(95.0);thr(65.0);allothr(65.0);hpg(65.0);dab(60.0),69053.0,91073.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",10,@D-Ser,D,ser,"12,11,10,9,8,7,6,5,4*3,2,1,0",10,D-Ser,,
+BGC0000336,orf00047,A1,FALSE,L,asn(75.0);asp(75.0);glu(60.0);lys(55.0);orn(50.0),91069.0,98209.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",11,@L-3Me-Glu,L,glu+MT,"12,11,10,9,8,7,6,5,4*3,2,1,0",11,mGlu,,
+BGC0000336,orf00047,A2,FALSE,L,phe(80.0);trp(70.0);tyr(70.0);bht(70.0);bmt(70.0),91069.0,98209.0,+,BGC0000336,"#,0,1,2,3,4,5,6,7,8,9,10,11",12,@L-Kyn,L,kyn,"12,11,10,9,8,7,6,5,4*3,2,1,0",12,Kyn,,
+BGC0000342,orf00001,A1,FALSE,L,hyv(100.0);ala(65.0);gly(60.0);val(60.0);ala-d(55.0),1020.0,10416.0,+,BGC0000342,"#,0,1,2,3,4",0,Hiv,NA,hiv,"0,1,2,3,4,5*",0,,,
+BGC0000342,orf00001,A1,FALSE,L,hyv(100.0);ala(65.0);gly(60.0);val(60.0);ala-d(55.0),1020.0,10416.0,+,BGC0000342,"#,0,1,2,3,4",2,Hiv,NA,hiv,"0,1,2,3,4,5*",2,,,
+BGC0000342,orf00001,A1,FALSE,L,hyv(100.0);ala(65.0);gly(60.0);val(60.0);ala-d(55.0),1020.0,10416.0,+,BGC0000342,"#,0,1,2,3,4",4,Hiv,NA,hiv,"0,1,2,3,4,5*",4,,,
+BGC0000342,orf00001,A2,TRUE,L,ile(70.0);leu(70.0);val(70.0);ala(65.0);gly(65.0),1020.0,10416.0,+,BGC0000342,"#,0,1,2,3,4",1,@L-NMe-Val,L,val+MT,"0,1,2,3,4,5*",1,,,
+BGC0000342,orf00001,A2,TRUE,L,ile(70.0);leu(70.0);val(70.0);ala(65.0);gly(65.0),1020.0,10416.0,+,BGC0000342,"#,0,1,2,3,4",3,@L-NMe-Val,L,val+MT,"0,1,2,3,4,5*",3,,,
+BGC0000342,orf00001,A2,TRUE,L,ile(70.0);leu(70.0);val(70.0);ala(65.0);gly(65.0),1020.0,10416.0,+,BGC0000342,"#,0,1,2,3,4",5,@L-NMe-Val,L,val+MT,"0,1,2,3,4,5*",5,,,
+BGC0000367,-,-,,,,,,,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",12,@L-Trp,L,trp,,,,,
+BGC0000367,-,-,,,,,,,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",13,@D-Leu,D,leu,,,,,
+BGC0000367,orf00009,A1,FALSE,L,leu(80.0);ala(75.0);gly(75.0);ile(75.0);val(65.0),10658.0,17549.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",0,@L-NFo-Val,L,val+unk,,,,,
+BGC0000367,orf00009,A2,FALSE,D,ala(55.0);cys(55.0);gly(50.0);ile(45.0);pro(45.0),10658.0,17549.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",1,Gly,NA,gly,,,,,
+BGC0000367,orf00010,A1,FALSE,L,cys(70.0);ala(55.0);pro(55.0);gly(50.0);ser(50.0),17619.0,40791.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",2,@L-Ala,L,ala,,,,,
+BGC0000367,orf00010,A2,FALSE,D,leu(95.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),17619.0,40791.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",3,@D-Leu,D,leu,,,,,
+BGC0000367,orf00010,A3,FALSE,L,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),17619.0,40791.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",4,@L-Ala,L,ala,,,,,
+BGC0000367,orf00010,A4,FALSE,D,val(100.0);ile(85.0);leu(80.0);abu(80.0);ala(65.0),17619.0,40791.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",5,@D-Val,D,val,,,,,
+BGC0000367,orf00010,A5,FALSE,L,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),17619.0,40791.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",6,@L-Val,L,val,,,,,
+BGC0000367,orf00010,A6,FALSE,D,val(100.0);ile(85.0);leu(80.0);abu(80.0);ala(65.0),17619.0,40791.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",7,@L-Val,L,val,,,,,
+BGC0000367,orf00011,A1,FALSE,L,val(100.0);ile(85.0);leu(80.0);abu(80.0);ala(65.0),40795.0,59995.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",8,@L-Trp,L,trp,,,,,
+BGC0000367,orf00011,A2,FALSE,D,val(100.0);ile(85.0);leu(80.0);abu(80.0);ala(65.0),40795.0,59995.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",9,@D-Leu,D,leu,,,,,
+BGC0000367,orf00011,A3,FALSE,L,leu(75.0);val(70.0);ala(65.0);gly(65.0);ile(65.0),40795.0,59995.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",10,@L-Trp,L,trp,,,,,
+BGC0000367,orf00011,A4,FALSE,D,leu(95.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),40795.0,59995.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",11,@D-Leu,D,leu,,,,,
+BGC0000367,orf00011,A5,FALSE,L,arg(60.0);apa(60.0);ahp(60.0);orn(55.0);asn(50.0),40795.0,59995.0,+,BGC0000367,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14",14,@L-Trp,L,trp,,,,,
+BGC0000374,orf00013,A1,FALSE,L,ala(80.0);gly(75.0);ala-d(70.0);leu(70.0);cys(65.0),11144.0,12728.0,+,BGC0000374.1,"#,0,1,2,3,4,5,6",-,-,-,-,,,,,
+BGC0000374,orf00017,A1,FALSE,L,cha(60.0);met(50.0);vol(50.0);bmt(50.0);hty(50.0),15557.0,31262.0,+,BGC0000374.1,"#,0,1,2,3,4,5,6",1,@L-X1,L,none,,,,,
+BGC0000374,orf00017,A2,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),15557.0,31262.0,+,BGC0000374.1,"#,0,1,2,3,4,5,6",2,@D-aThr/Thr,D,thr,,,,,
+BGC0000374,orf00017,A3,FALSE,L,phe(75.0);trp(70.0);abu(55.0);leu(50.0);bmt(50.0),15557.0,31262.0,+,BGC0000374.1,"#,0,1,2,3,4,5,6",3,@L-bMe-Phe,L,phe+MT,,,,,
+BGC0000374,orf00017,A4,FALSE,D,cha(60.0);met(50.0);vol(50.0);bmt(50.0);hty(50.0),15557.0,31262.0,+,BGC0000374.1,"#,0,1,2,3,4,5,6",4,@D-X1,D,none,,,,,
+BGC0000374,orf00018,A1,FALSE,L,phe(75.0);trp(70.0);abu(55.0);leu(50.0);bmt(50.0),33715.0,41674.0,+,BGC0000374.1,"#,0,1,2,3,4,5,6",5,@L-bMe-Phe,L,phe+MT,,,,,
+BGC0000374,orf00018,A2,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(70.0);ala(60.0),33715.0,41674.0,+,BGC0000374.1,"#,0,1,2,3,4,5,6",6,@L-Ile/aIle,L,ile,,,,,
+BGC0000379,orf00018,A1,FALSE,L,ser(40.0);dab(40.0);hty(40.0);gua(40.0);cit(40.0),22787.0,25616.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",1,@L-Asp,L,asp,"10,9,8,7,6,5,4,3,2,1*0",0,Asp,,
+BGC0000379,orf00025,A1,FALSE,L,asp(95.0);asn(85.0);glu(65.0);gln(60.0);hty(60.0),32711.0,42275.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",2,@L-Dpr,L,dpr,"10,9,8,7,6,5,4,3,2,1*0",1,Dap,,
+BGC0000379,orf00025,A2,FALSE,D,pip(85.0);pro(70.0);ala(50.0);ile(50.0);leu(50.0),32711.0,42275.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",3,@L-Hpr,L,pip,"10,9,8,7,6,5,4,3,2,1*0",2,Pip,,
+BGC0000379,orf00026,A1,FALSE,L,gly(100.0);ala(75.0);leu(65.0);val(65.0);ile(60.0),42271.0,62701.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",4,Gly,NA,gly,"10,9,8,7,6,5,4,3,2,1*0",3,Gly,,
+BGC0000379,orf00026,A2,FALSE,L,asp(100.0);asn(85.0);glu(65.0);gln(60.0);hty(60.0),42271.0,62701.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",5,@L-Asp,L,asp,"10,9,8,7,6,5,4,3,2,1*0",4,Asp,,
+BGC0000379,orf00026,A3,FALSE,L,gly(100.0);ala(75.0);leu(65.0);val(65.0);ile(60.0),42271.0,62701.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",6,Gly,NA,gly,"10,9,8,7,6,5,4,3,2,1*0",5,Gly,,
+BGC0000379,orf00026,A4,FALSE,L,asp(100.0);asn(85.0);glu(65.0);gln(60.0);hty(60.0),42271.0,62701.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",7,@L-Asp,L,asp,"10,9,8,7,6,5,4,3,2,1*0",6,Asp,,
+BGC0000379,orf00026,A5,FALSE,L,gly(100.0);ala(75.0);leu(65.0);val(65.0);ile(60.0),42271.0,62701.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",8,Gly,NA,gly,"10,9,8,7,6,5,4,3,2,1*0",7,Gly,,
+BGC0000379,orf00026,A6,FALSE,D,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),42271.0,62701.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",9,@L-aThr/Thr,L,thr,"10,9,8,7,6,5,4,3,2,1*0",8,D-Thr,,
+BGC0000379,orf00027,A1,FALSE,L,val(90.0);ile(80.0);leu(75.0);abu(75.0);ala(60.0),62700.0,69918.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",10,@L-Ile/aIle,L,ile,"10,9,8,7,6,5,4,3,2,1*0",9,Ile,,
+BGC0000379,orf00027,A2,FALSE,L,pro(100.0);pip(80.0);uda(60.0);ala(55.0);ser(55.0),62700.0,69918.0,+,BGC0000379,"#,0,1,2,3,4,5,6,7,8,9,10",11,@L-Pro,L,pro,"10,9,8,7,6,5,4,3,2,1*0",10,Pro,,
+BGC0000385,orf00066,A1,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),80786.0,92306.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",0,Leu,NA,leu,"10,9,8,7,6,5,4,3,2*1,0",0,D-Leu,,
+BGC0000385,orf00066,A2,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),80786.0,92306.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",1,Leu,NA,leu,"10,9,8,7,6,5,4,3,2*1,0",1,Leu,,
+BGC0000385,orf00066,A3,FALSE,L,ala(70.0);leu(70.0);val(70.0);gly(65.0);ile(60.0),80786.0,92306.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",2,Ph-Ser,NA,none,"10,9,8,7,6,5,4,3,2*1,0",2,hyPhe,,
+BGC0000385,orf00066,A4,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),80786.0,92306.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",3,3OH-Leu,NA,leu+unk,"10,9,8,7,6,5,4,3,2*1,0",3,hyLeu,,
+BGC0000385,orf00067,A1,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),92320.0,117916.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",4,Leu,NA,leu,"10,9,8,7,6,5,4,3,2*1,0",4,Leu,,
+BGC0000385,orf00067,A2,FALSE,D,glu(70.0);asp(65.0);arg(60.0);asn(60.0);gln(60.0),92320.0,117916.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",5,Arg,NA,arg,"10,9,8,7,6,5,4,3,2*1,0",5,D-Arg,,
+BGC0000385,orf00067,A3,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),92320.0,117916.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",6,Ile/aIle,NA,ile,"10,9,8,7,6,5,4,3,2*1,0",6,Ile,,
+BGC0000385,orf00067,A4,FALSE,L,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),92320.0,117916.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",7,aThr/Thr,NA,thr,"10,9,8,7,6,5,4,3,2*1,0",7,aThr,,
+BGC0000385,orf00067,A5,FALSE,L,gly(95.0);ala(75.0);leu(70.0);ile(65.0);val(65.0),92320.0,117916.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",8,Gly,NA,gly,"10,9,8,7,6,5,4,3,2*1,0",8,Gly,,
+BGC0000385,orf00067,A6,FALSE,L,asn(100.0);asp(85.0);gln(65.0);glu(65.0);arg(55.0),92320.0,117916.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",9,OH-Asn,NA,asn+unk,"10,9,8,7,6,5,4,3,2*1,0",9,hyAsn,,
+BGC0000385,orf00067,A7,FALSE,L,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),92320.0,117916.0,+,BGC0000385,"#,0,1,2,3,4,5,6,7,8,9",10,Ser,NA,ser,"10,9,8,7,6,5,4,3,2*1,0",10,Ser,,
+BGC0000388,-,-,,,,,,,BGC0000388,"0,1,2,3,4,5*",3,@L-bhEnd,L,none,,,,,
+BGC0000388,orf00009,A1,FALSE,L,thr(90.0);ser(85.0);allothr(85.0);dht(70.0);ala(60.0),10101.0,18312.0,+,BGC0000388,"0,1,2,3,4,5*",5,@L-Ser,L,ser,"0,1,2,3,4,5*",0,Ser,,
+BGC0000388,orf00009,A2,FALSE,L,ser(65.0);met(60.0);ala(50.0);ala-d(50.0);cys(50.0),10101.0,18312.0,+,BGC0000388,"0,1,2,3,4,5*",0,Gly,NA,gly,"0,1,2,3,4,5*",1,Gly,,
+BGC0000388,orf00009,A3,FALSE,L,ser(60.0);dhpg(60.0);dhp(60.0);thr(55.0);allothr(55.0),10101.0,18312.0,+,BGC0000388,"0,1,2,3,4,5*",1,@L-bMe-Phe,L,phe+MT,"0,1,2,3,4,5*",2,Phe,,
+BGC0000388,orf00010,A1,FALSE,D,tyr(100.0);bht(95.0);phe(85.0);trp(70.0);uda(60.0),18308.0,29315.0,+,BGC0000388,"0,1,2,3,4,5*",2,@D-Tyr,D,tyr,"0,1,2,3,4,5*",3,Tyr,,
+BGC0000388,orf00010,A2,FALSE,D,ala(65.0);ala-d(65.0);gly(65.0);leu(65.0);ile(60.0),18308.0,29315.0,+,BGC0000388,"0,1,2,3,4,5*",4,@D-bhEnd,D,none,"0,1,2,3,4,5*",4,End,,
+BGC0000388,orf00010,A2,FALSE,D,ala(65.0);ala-d(65.0);gly(65.0);leu(65.0);ile(60.0),18308.0,29315.0,+,BGC0000388,"0,1,2,3,4,5*",4,@D-bhEnd,D,none,"0,1,2,3,4,5*",5,End,,
+BGC0000389,-,-,,,,,,,BGC0000389,"#,0,1,2,3,4,5,6,7",0,@L-Leu,L,leu,,,,,
+BGC0000389,-,-,,,,,,,BGC0000389,"#,0,1,2,3,4,5,6,7",1,@D-Glu,D,glu,,,,,
+BGC0000389,orf00001,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),1176.0,12924.0,+,BGC0000389,"#,0,1,2,3,4,5,6,7",2,@D-aThr/Thr,D,thr,"8,7,6,5,4,3,2*1,0",2,Thr,,
+BGC0000389,orf00001,A2,FALSE,D,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),1176.0,12924.0,+,BGC0000389,"#,0,1,2,3,4,5,6,7",3,@D-Ile/aIle,D,ile,"8,7,6,5,4,3,2*1,0",3,Val,,
+BGC0000389,orf00001,A3,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),1176.0,12924.0,+,BGC0000389,"#,0,1,2,3,4,5,6,7",4,@L-Leu,L,leu,"8,7,6,5,4,3,2*1,0",4,Leu,,
+BGC0000389,orf00001,A4,FALSE,L,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),1176.0,12924.0,+,BGC0000389,"#,0,1,2,3,4,5,6,7",5,@D-Ser,D,ser,"8,7,6,5,4,3,2*1,0",5,Ser,,
+BGC0000389,-,-,,,,,,,BGC0000389,"#,0,1,2,3,4,5,6,7",6,@L-Leu,L,leu,,,,,
+BGC0000389,orf00002,A1,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),16490.0,24248.0,+,BGC0000389,"#,0,1,2,3,4,5,6,7",7,@D-Ser,D,ser,,,,,
+BGC0000389,orf00002,A2,FALSE,L,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),16490.0,24248.0,+,BGC0000389,"#,0,1,2,3,4,5,6,7",8,@L-Ile/aIle,L,ile,,,,,
+BGC0000397,orf00007,A1,FALSE,L,tyr(100.0);bht(95.0);phe(85.0);trp(70.0);uda(60.0),8495.0,19703.0,+,BGC0000397,"#,0,1,2,3,4,5",-,-,-,-,,,,,
+BGC0000397,orf00007,A2,FALSE,L,gly(100.0);ala(75.0);leu(65.0);val(65.0);ile(60.0),8495.0,19703.0,+,BGC0000397,"#,0,1,2,3,4,5",1,Gly,NA,gly,,,,,
+BGC0000397,orf00007,A3,FALSE,D,gln(100.0);glu(80.0);asp(65.0);asn(60.0);arg(55.0),8495.0,19703.0,+,BGC0000397,"#,0,1,2,3,4,5",2,@D-Gln,D,gln,,,,,
+BGC0000397,orf00008,A1,FALSE,L,ile(100.0);leu(85.0);val(85.0);abu(70.0);ala(65.0),19699.0,34111.0,+,BGC0000397,"#,0,1,2,3,4,5",3,@L-Ile/aIle,L,ile,,,,,
+BGC0000397,orf00008,A2,FALSE,L,ser(100.0);dab(70.0);hpg(65.0);thr(60.0);allothr(60.0),19699.0,34111.0,+,BGC0000397,"#,0,1,2,3,4,5",4,@L-Ser,L,ser,,,,,
+BGC0000397,orf00008,A3,FALSE,L,pro(95.0);pip(70.0);gua(60.0);uda(60.0);ala(55.0),19699.0,34111.0,+,BGC0000397,"#,0,1,2,3,4,5",5,@L-4Me-Pro,L,pro+MT,,,,,
+BGC0000397,orf00008,A4,FALSE,L,phe(90.0);trp(80.0);bht(80.0);bmt(80.0);tyr(75.0),19699.0,34111.0,+,BGC0000397,"#,0,1,2,3,4,5",-,-,-,-,,,,,
+BGC0000399,orf00003,A1,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),2885.0,9251.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",0,@L-Leu,L,leu,"9,8,7,6,5,4,3,2*1,0",0,L-Leu,,
+BGC0000399,orf00003,A2,FALSE,D,asp(90.0);glu(75.0);asn(70.0);gln(70.0);arg(55.0),2885.0,9251.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",1,@D-Glu,D,glu,"9,8,7,6,5,4,3,2*1,0",1,D-Glu/Asp,,
+BGC0000399,orf00004,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),9568.0,22672.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",2,@D-aThr/Thr,D,thr,"9,8,7,6,5,4,3,2*1,0",2,D-allo Thr,,
+BGC0000399,orf00004,A2,FALSE,D,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),9568.0,22672.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",3,@D-Ile/aIle,D,ile,"9,8,7,6,5,4,3,2*1,0",3,D-allo Ile,,
+BGC0000399,orf00004,A3,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),9568.0,22672.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",4,@L-Leu,L,leu,"9,8,7,6,5,4,3,2*1,0",4,L-Leu,,
+BGC0000399,orf00004,A4,FALSE,D,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),9568.0,22672.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",5,@D-Ser,D,ser,"9,8,7,6,5,4,3,2*1,0",5,D-Ser,,
+BGC0000399,orf00005,A1,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),22668.0,37374.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",6,@L-Leu,L,leu,"9,8,7,6,5,4,3,2*1,0",6,L-Leu,,
+BGC0000399,orf00005,A2,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),22668.0,37374.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",7,@L-Leu,L,leu,"9,8,7,6,5,4,3,2*1,0",7,L-Leu,,
+BGC0000399,orf00005,A3,FALSE,D,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),22668.0,37374.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",8,@D-Ser,D,ser,"9,8,7,6,5,4,3,2*1,0",8,D-Ser,,
+BGC0000399,orf00005,A4,FALSE,L,ile(90.0);val(85.0);leu(80.0);abu(75.0);ala(65.0),22668.0,37374.0,+,BGC0000399.1,"#,0,1,2,3,4,5,6,7,8",9,@L-Val,L,val,"9,8,7,6,5,4,3,2*1,0",9,L-Val,,
+BGC0000407,orf00004,A1,FALSE,L,glu(100.0);gln(80.0);asp(70.0);bmt(70.0);asn(65.0),4372.0,12079.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",0,Glu,NA,glu,"7,6,5,4,3,2,1,0*8,9,#",9,Glu,,
+BGC0000407,orf00004,A2,FALSE,D,orn(100.0);dab(90.0);lys(75.0);arg(70.0);gln(50.0),4372.0,12079.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",1,Orn,NA,orn,"7,6,5,4,3,2,1,0*8,9,#",8,Orn,,
+BGC0000407,orf00005,A1,FALSE,L,tyr(100.0);trp(65.0);bht(65.0);phe(60.0);phg(50.0),12094.0,19786.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",2,Tyr,NA,tyr,"7,6,5,4,3,2,1,0*8,9,#",0,Tyr,,
+BGC0000407,orf00005,A2,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),12094.0,19786.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",3,aThr/Thr,NA,thr,"7,6,5,4,3,2,1,0*8,9,#",7,Thr/Ser,,
+BGC0000407,orf00006,A1,FALSE,L,glu(100.0);gln(80.0);asp(70.0);bmt(70.0);asn(65.0),19803.0,27471.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",4,Glu,NA,glu,"7,6,5,4,3,2,1,0*8,9,#",6,Glu,,
+BGC0000407,orf00006,A2,FALSE,D,val(100.0);abu(80.0);ile(75.0);ala(70.0);leu(70.0),19803.0,27471.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",5,Ala,NA,ala,"7,6,5,4,3,2,1,0*8,9,#",5,Ala/Val/Aba,,
+BGC0000407,orf00007,A1,FALSE,L,pro(100.0);pip(75.0);uda(60.0);ala(55.0);ala-d(50.0),27490.0,38347.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",6,Pro,NA,pro,"7,6,5,4,3,2,1,0*8,9,#",4,Pro,,
+BGC0000407,orf00007,A2,FALSE,L,glu(100.0);gln(75.0);asn(65.0);asp(65.0);aad(60.0),27490.0,38347.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",7,Gln,NA,gln,"7,6,5,4,3,2,1,0*8,9,#",3,Gln,,
+BGC0000407,orf00007,A3,FALSE,D,tyr(100.0);trp(65.0);bht(65.0);phe(60.0);phg(50.0),27490.0,38347.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",8,Tyr,NA,tyr,"7,6,5,4,3,2,1,0*8,9,#",2,Tyr,,
+BGC0000407,orf00008,A1,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(65.0),38375.0,42194.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",9,Ile/aIle,NA,ile,"7,6,5,4,3,2,1,0*8,9,#",1,Ile/Val,,
+BGC0000407,orf00013,A1,FALSE,L,aad(60.0);asp(55.0);asn(50.0);glu(50.0);gln(45.0),46129.0,47779.0,+,BGC0000407,"#,0,1,2,3,4,5,6,7,8",-,-,-,-,,,,,
+BGC0000416,-,-,,,,,,,BGC0000416.2,"#,0,1,2,3,4",0,@D-NMe-Val,D,val+MT,,,,,
+BGC0000416,-,-,,,,,,,BGC0000416.2,"#,0,1,2,3,4",1,@D-NMe-Leu,D,leu+MT,,,,,
+BGC0000416,orf00001,A1,TRUE,L,phe(65.0);tyr(65.0);bht(60.0);ala(55.0);trp(55.0),0.0,4683.0,+,BGC0000416.2,"#,0,1,2,3,4",2,@D-NMe-Val,D,val+MT,"0,1,2,",0,Leu,,
+BGC0000416,orf00002,A1,TRUE,L,phe(65.0);tyr(65.0);bht(60.0);ala(55.0);trp(55.0),4679.0,9344.0,+,BGC0000416.2,"#,0,1,2,3,4",3,@D-NMe-Val,D,val+MT,"0,1,2,",1,Val,,
+BGC0000416,orf00003,A1,TRUE,L,phe(65.0);tyr(65.0);bht(60.0);ala(55.0);trp(55.0),9340.0,15337.0,+,BGC0000416.2,"#,0,1,2,3,4",4,@D-NMe-Val,D,val+MT,"0,1,2,",2,Val,,
+BGC0000424,orf00007,A1,FALSE,D,asp(100.0);asn(90.0);glu(65.0);gln(60.0);cha(60.0),6092.0,33575.0,+,BGC0000424.1,"#,0,1,2,3,4",0,OH-Asp,NA,asp+unk,"0,1,2,3,4,5",0,Asp,,
+BGC0000424,orf00007,A2,FALSE,L,ser(100.0);dab(70.0);hpg(65.0);thr(60.0);allothr(60.0),6092.0,33575.0,+,BGC0000424.1,"#,0,1,2,3,4",1,Ser,NA,ser,"0,1,2,3,4,5",1,Ser,,
+BGC0000424,orf00007,A3,FALSE,L,asp(100.0);asn(90.0);glu(65.0);gln(60.0);cha(60.0),6092.0,33575.0,+,BGC0000424.1,"#,0,1,2,3,4",2,OH-Asp,NA,asp+unk,"0,1,2,3,4,5",2,Asp,,
+BGC0000424,orf00007,A4,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),6092.0,33575.0,+,BGC0000424.1,"#,0,1,2,3,4",3,aThr/Thr,NA,thr,"0,1,2,3,4,5",3,Thr,,
+BGC0000424,orf00007,A5,FALSE,L,ser(100.0);dab(70.0);hpg(65.0);thr(60.0);allothr(60.0),6092.0,33575.0,+,BGC0000424.1,"#,0,1,2,3,4",4,Ser,NA,ser,"0,1,2,3,4,5",4,Ser,,
+BGC0000424,orf00007,A6,FALSE,L,gln(70.0);asn(65.0);asp(65.0);glu(65.0);orn(60.0),6092.0,33575.0,+,BGC0000424.1,"#,0,1,2,3,4",-,-,-,-,"0,1,2,3,4,5",5,N^5-OH Orn,,
+BGC0000425,orf00004,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),4805.0,24047.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",0,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",0,x-dhAbu,,dhAbu
+BGC0000425,orf00004,A2,FALSE,D,pro(95.0);pip(75.0);uda(60.0);ser(55.0);ala(50.0),4805.0,24047.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",1,Pro,NA,pro,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",1,D-Pro,,
+BGC0000425,orf00004,A3,FALSE,D,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),4805.0,24047.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",2,@D-Ser,D,ser,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",2,D-Ser,,
+BGC0000425,orf00004,A4,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),4805.0,24047.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",3,@D-Leu,D,leu,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",3,D-Leu,,
+BGC0000425,orf00004,A5,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),4805.0,24047.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",4,@D-Val,D,val,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",4,D-Val,,
+BGC0000425,orf00004,A6,FALSE,D,gln(95.0);glu(80.0);asp(65.0);asn(60.0);arg(55.0),4805.0,24047.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",5,@D-Gln,D,gln,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",5,D-Gln,,
+BGC0000425,orf00005,A1,FALSE,D,leu(95.0);ile(75.0);val(70.0);abu(70.0);ala(65.0),24043.0,43444.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",6,@D-Leu,D,leu,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",6,D-Leu,,
+BGC0000425,orf00005,A2,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),24043.0,43444.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",7,@D-Val,D,val,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",7,D-Val,,
+BGC0000425,orf00005,A3,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),24043.0,43444.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",8,@L-Val,L,val,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",8,L-Val,,
+BGC0000425,orf00005,A4,FALSE,D,gln(95.0);glu(80.0);asp(65.0);asn(60.0);arg(55.0),24043.0,43444.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",9,@D-Gln,D,gln,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",9,D-Gln,,
+BGC0000425,orf00005,A5,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),24043.0,43444.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",10,@L-Leu,L,leu,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",10,L-Leu,,
+BGC0000425,orf00005,A6,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),24043.0,43444.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",11,@D-Val,D,val,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",11,D-Val,,
+BGC0000425,orf00006,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),43821.0,64995.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",12,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",12,x-dhAbu,,dhAbu
+BGC0000425,orf00006,A2,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),43821.0,64995.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",13,@D-aThr/Thr,D,thr,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",13,D-Thr,,
+BGC0000425,orf00006,A3,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),43821.0,64995.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",14,@L-Ile/aIle,L,ile,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",14,L-lle,,
+BGC0000425,orf00006,A4,FALSE,L,asn(65.0);asp(65.0);gln(60.0);glu(60.0);aad(60.0),43821.0,64995.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",15,@L-Hse,L,hse,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",15,L-Hse,,
+BGC0000425,orf00006,A5,FALSE,D,dab(100.0);ala(65.0);ala-d(60.0);val(60.0);gly(55.0),43821.0,64995.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",16,@D-Dab,D,dab,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",16,D-Dab,,
+BGC0000425,orf00006,A6,FALSE,L,bmt(50.0);end(50.0);cha(50.0);dab(40.0);hyv(40.0),43821.0,64995.0,+,BGC0000425,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",17,@L-Lys,L,lys,"0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17",17,L-Lys,,
+BGC0000433,orf00011,A1,FALSE,L,glu(95.0);gln(90.0);asp(80.0);asn(65.0);arg(60.0),8557.0,19312.0,+,BGC0000433,"#,0,1,2,3,4,5",0,@L-Glu,L,glu,,,,,
+BGC0000433,orf00011,A2,FALSE,L,leu(100.0);val(80.0);ile(75.0);ala(65.0);gly(65.0),8557.0,19312.0,+,BGC0000433,"#,0,1,2,3,4,5",1,@L-Leu,L,leu,,,,,
+BGC0000433,orf00011,A3,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),8557.0,19312.0,+,BGC0000433,"#,0,1,2,3,4,5",2,@D-Leu,D,leu,,,,,
+BGC0000433,orf00012,A1,FALSE,L,val(100.0);ile(80.0);abu(80.0);leu(75.0);ala(65.0),19333.0,30094.0,+,BGC0000433,"#,0,1,2,3,4,5",3,@L-Val,L,val,,,,,
+BGC0000433,orf00012,A2,FALSE,L,asp(100.0);asn(85.0);gln(60.0);glu(60.0);lys(55.0),19333.0,30094.0,+,BGC0000433,"#,0,1,2,3,4,5",4,@L-Asp,L,asp,,,,,
+BGC0000433,orf00012,A3,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),19333.0,30094.0,+,BGC0000433,"#,0,1,2,3,4,5",5,@D-Leu,D,leu,,,,,
+BGC0000433,orf00013,A1,FALSE,L,leu(100.0);val(90.0);ile(85.0);gly(70.0);ala(65.0),30128.0,33965.0,+,BGC0000433,"#,0,1,2,3,4,5",6,@L-Leu,L,leu,,,,,
+BGC0000437,orf00003,A1,FALSE,D,ser(100.0);hpg(70.0);dpg(65.0);thr(60.0);dab(60.0),2470.0,30844.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",0,@L-Ser,L,ser,"1,2,3,4,5,6,7,8,0*,#",0,Ser,,
+BGC0000437,orf00003,A2,FALSE,D,ser(100.0);hpg(70.0);dpg(65.0);thr(60.0);dab(60.0),2470.0,30844.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",1,@D-Ser,D,ser,"1,2,3,4,5,6,7,8,0*,#",1,Ser,,
+BGC0000437,orf00003,A3,FALSE,D,dab(100.0);ala(65.0);ala-d(60.0);val(60.0);gly(55.0),2470.0,30844.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",2,@D-Dab,D,dab,"1,2,3,4,5,6,7,8,0*,#",2,Dab,,
+BGC0000437,orf00003,A4,FALSE,L,dab(100.0);ala(65.0);ala-d(60.0);val(60.0);gly(55.0),2470.0,30844.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",3,@L-Dab,L,dab,"1,2,3,4,5,6,7,8,0*,#",3,Dab,,
+BGC0000437,orf00003,A5,FALSE,L,arg(100.0);lys(75.0);orn(70.0);dab(60.0);asp(50.0),2470.0,30844.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",4,@L-Arg,L,arg,"1,2,3,4,5,6,7,8,0*,#",4,Arg,,
+BGC0000437,orf00003,A6,FALSE,L,phe(100.0);tyr(80.0);trp(70.0);bht(65.0);phg(55.0),2470.0,30844.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",5,@L-Phe,L,phe,"1,2,3,4,5,6,7,8,0*,#",5,Phe,,
+BGC0000437,orf00003,A7,FALSE,D,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),2470.0,30844.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",6,dhAbu,NA,abu+unk,"1,2,3,4,5,6,7,8,0*,#",6,Dhb,,
+BGC0000437,orf00003,A8,FALSE,L,asp(100.0);glu(80.0);gln(75.0);asn(70.0);cit(60.0),2470.0,30844.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",7,@L-OH-Asp,L,asp+unk,"1,2,3,4,5,6,7,8,0*,#",7,(3-OH)Asp,,
+BGC0000437,orf00006,A1,FALSE,L,thr(100.0);allothr(90.0);ser(80.0);dht(80.0);hpg(60.0),33476.0,35321.0,-,BGC0000437,"#,0,1,2,3,4,5,6,7",8,@L-4Cl-Thr,L,thr+unk,"1,2,3,4,5,6,7,8,0*,#",8,(4-Cl)Thr,,
+BGC0000438,-,-,,,,,,,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",3,@L-Ala,L,ala,,,,,
+BGC0000438,-,-,,,,,,,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",4,@L-Ala,L,ala,,,,,
+BGC0000438,-,-,,,,,,,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",6,@L-Leu,L,leu,,,,,
+BGC0000438,orf00001,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),137.0,16277.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",0,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",21,Dhb,,
+BGC0000438,orf00001,A2,FALSE,D,pro(100.0);pip(80.0);uda(60.0);ala(55.0);ser(55.0),137.0,16277.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",1,@L-Pro,L,pro,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",20,Pro,,
+BGC0000438,orf00001,A3,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),137.0,16277.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",2,@L-Val,L,val,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",19,Val,,
+BGC0000438,orf00001,A4,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),137.0,16277.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",5,@L-Val,L,val,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",18,Val,,
+BGC0000438,orf00001,A5,FALSE,D,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),137.0,16277.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",7,@L-Ala,L,ala,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",17,Ala,,
+BGC0000438,orf00002,A1,FALSE,D,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),16279.0,32689.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",8,@L-Ala,L,ala,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",16,Ala,,
+BGC0000438,orf00002,A2,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),16279.0,32689.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",9,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",15,Val,,
+BGC0000438,orf00002,A3,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),16279.0,32689.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",10,@L-Val,L,val,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",14,Val,,
+BGC0000438,orf00002,A4,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),16279.0,32689.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",11,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",13,Dhb,,
+BGC0000438,orf00002,A5,FALSE,D,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),16279.0,32689.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",12,@L-Ala,L,ala,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",12,Ala,,
+BGC0000438,orf00003,A1,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",13,@L-Val,L,val,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",11,Val,,
+BGC0000438,orf00003,A10,FALSE,L,dab(100.0);ala(65.0);ala-d(60.0);val(60.0);gly(55.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",22,@L-Dab,L,dab,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",2,Dab,,
+BGC0000438,orf00003,A11,FALSE,L,dab(100.0);ala(65.0);ala-d(60.0);val(60.0);gly(55.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",23,@L-Dab,L,dab,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",1,Dab,,
+BGC0000438,orf00003,A12,FALSE,L,tyr(90.0);phe(80.0);trp(65.0);bht(65.0);phg(55.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",24,@L-Tyr,L,tyr,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",0,Tyr,,
+BGC0000438,orf00003,A2,FALSE,D,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",14,@L-Ala,L,ala,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",10,Ala,,
+BGC0000438,orf00003,A3,FALSE,D,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",15,@L-Ala,L,ala,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",9,Ala,,
+BGC0000438,orf00003,A4,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",16,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",8,Dhb,,
+BGC0000438,orf00003,A5,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",17,@L-aThr/Thr,L,thr,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",7,aThr,,
+BGC0000438,orf00003,A6,FALSE,D,ser(100.0);hpg(70.0);dpg(65.0);thr(60.0);dab(60.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",18,@L-Ser,L,ser,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",6,Ser,,
+BGC0000438,orf00003,A7,FALSE,D,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",19,@L-Ala,L,ala,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",5,Ala,,
+BGC0000438,orf00003,A8,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",20,@L-Val,L,val,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",4,Dhb,,
+BGC0000438,orf00003,A9,FALSE,L,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),33114.0,73725.0,+,BGC0000438,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23",21,@L-Ala,L,ala,"0,1,2,3,4,5,6,7*,8,9,10,11,12,13,14,15,16,17,18,19,20,21,#",3,Ala,,
+BGC0000439,orf00012,A1,FALSE,L,tyr(75.0);bht(75.0);ahp(60.0);met(50.0);dht(50.0),11571.0,28905.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",-,-,-,-,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",0,6-Сl-Trp,,
+BGC0000439,orf00012,A2,FALSE,D,asn(85.0);asp(85.0);glu(65.0);gln(60.0);aad(50.0),11571.0,28905.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",1,@D-Asn,D,asn,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",1,Asp,,
+BGC0000439,orf00012,A3,FALSE,L,asp(90.0);asn(85.0);gln(60.0);glu(60.0);hty(60.0),11571.0,28905.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",2,@L-Asp,L,asp,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",2,Asp,,
+BGC0000439,orf00012,A4,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),11571.0,28905.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",3,@L-aThr/Thr,L,thr,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",3,Thr,,
+BGC0000439,orf00012,A5,FALSE,L,gly(100.0);ala(75.0);leu(65.0);val(65.0);ile(60.0),11571.0,28905.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",4,Gly,NA,gly,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",4,Gly,,
+BGC0000439,orf00013,A1,FALSE,L,glu(65.0);arg(55.0);asp(55.0);gln(55.0);lys(50.0),28901.0,50819.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",5,@L-Orn,L,orn,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",5,Orn,,
+BGC0000439,orf00013,A2,FALSE,L,asp(90.0);asn(85.0);gln(60.0);glu(60.0);hty(60.0),28901.0,50819.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",6,@L-Asp,L,asp,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",6,Asp,,
+BGC0000439,orf00013,A3,FALSE,D,ala(90.0);gly(75.0);ala-d(65.0);ser(60.0);ile(55.0),28901.0,50819.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",7,@D-Ala,D,ala,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",7,Ala,,
+BGC0000439,orf00013,A4,FALSE,L,asp(90.0);asn(85.0);gln(60.0);glu(60.0);hty(60.0),28901.0,50819.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",8,@L-Asp,L,asp,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",8,Asp,,
+BGC0000439,orf00013,A5,FALSE,L,gly(95.0);ala(70.0);ile(65.0);val(65.0);leu(60.0),28901.0,50819.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",9,Gly,NA,gly,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",9,Gly,,
+BGC0000439,orf00013,A6,FALSE,D,ala(90.0);gly(80.0);leu(70.0);val(70.0);ala-d(65.0),28901.0,50819.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",10,@D-Ala,D,ala,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",10,Ala,,
+BGC0000439,orf00014,A1,FALSE,L,asn(80.0);asp(80.0);glu(60.0);gln(50.0);lys(50.0),50820.0,57978.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",11,@L-3Me-Glu,L,glu+MT,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",11,Glu,,
+BGC0000439,orf00014,A2,FALSE,L,phe(80.0);trp(70.0);tyr(70.0);bht(70.0);bmt(70.0),50820.0,57978.0,+,BGC0000439,"#,0,1,2,3,4,5,6,7,8,9,10,11",-,-,-,-,"12,11,10,9,8,7,6,5,4,3*,2,1,0,#",12,4-Cl-Kyn,,
+BGC0000443,orf00007,A1,FALSE,L,ser(100.0);hpg(70.0);dpg(65.0);thr(60.0);dab(60.0),5608.0,21733.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",0,Ser,NA,ser,"0,1,2,3,4,5,6,7,8*",0,Ser,,
+BGC0000443,orf00007,A2,FALSE,D,asp(70.0);cit(70.0);asn(65.0);gln(60.0);glu(60.0),5608.0,21733.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",1,X1,NA,none,"0,1,2,3,4,5,6,7,8*",1,Orn,,
+BGC0000443,orf00007,A3,FALSE,L,asp(100.0);glu(80.0);gln(75.0);asn(70.0);cit(60.0),5608.0,21733.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",2,Asp,NA,asp,"0,1,2,3,4,5,6,7,8*",2,Asp,,
+BGC0000443,orf00007,A4,FALSE,D,asn(65.0);asp(65.0);gln(60.0);glu(60.0);aad(60.0),5608.0,21733.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",3,Hse,NA,hse,"0,1,2,3,4,5,6,7,8*",3,Lys,,
+BGC0000443,orf00007,A5,FALSE,L,leu(70.0);val(65.0);ala(60.0);gly(60.0);ile(60.0),5608.0,21733.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",4,X2,NA,none,"0,1,2,3,4,5,6,7,8*",4,His,,
+BGC0000443,orf00008,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),21736.0,35314.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",5,X0,NA,none,"0,1,2,3,4,5,6,7,8*",5,Thr,,
+BGC0000443,orf00008,A2,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),21736.0,35314.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",6,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7,8*",6,Dhb,,
+BGC0000443,orf00008,A3,FALSE,L,asp(100.0);glu(80.0);gln(75.0);asn(70.0);cit(60.0),21736.0,35314.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",7,OH-Asp,NA,asp+unk,"0,1,2,3,4,5,6,7,8*",7,OH-Asp,,
+BGC0000443,orf00009,A1,FALSE,L,thr(100.0);allothr(90.0);ser(80.0);dht(80.0);hpg(60.0),35639.0,37484.0,+,BGC0000443,"#,0,1,2,3,4,5,6,7",8,4Cl-Thr,NA,thr+unk,"0,1,2,3,4,5,6,7,8*",8,4Cl-Thr,,
+BGC0000447,orf00004,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),4794.0,14454.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",0,dhAbu,NA,abu+unk,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",0,"2,3‐didehydrobutyrine",,
+BGC0000447,orf00004,A2,FALSE,D,pro(95.0);pip(70.0);uda(60.0);ala(55.0);gly(50.0),4794.0,14454.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",1,@D-Pro,D,pro,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",1,D-Pro,,
+BGC0000447,orf00004,A3,FALSE,D,ser(90.0);met(40.0);dab(40.0);dht(40.0);bmt(40.0),4794.0,14454.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",2,@L-Ser,L,ser,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",2,D-Ser,,
+BGC0000447,orf00005,A1,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),14450.0,24293.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",3,@L-Leu,L,leu,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",3,D-Leu,,
+BGC0000447,orf00005,A2,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),14450.0,24293.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",4,@D-Val,D,val,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",4,D-Val,,
+BGC0000447,orf00005,A3,FALSE,D,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),14450.0,24293.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",5,@D-Ser,D,ser,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",5,D-Ser,,
+BGC0000447,orf00006,A1,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),24289.0,34258.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",6,@D-Leu,D,leu,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",6,D-Leu,,
+BGC0000447,orf00006,A2,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),24289.0,34258.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",7,@D-Val,D,val,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",7,D-Val,,
+BGC0000447,orf00006,A3,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),24289.0,34258.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",8,@L-Val,L,val,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",8,L-Val/D-Val,,
+BGC0000447,orf00007,A1,FALSE,D,gln(95.0);glu(80.0);asp(65.0);asn(60.0);arg(55.0),34215.0,44247.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",9,@D-Gln,D,gln,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",9,D-Gln,,
+BGC0000447,orf00007,A2,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),34215.0,44247.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",10,@L-Leu,L,leu,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",10,L-Leu,,
+BGC0000447,orf00007,A3,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),34215.0,44247.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",11,@D-Val,D,val,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",11,D-Val,,
+BGC0000447,orf00008,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),44557.0,65716.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",12,dhAbu,NA,abu+unk,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",12,"2,3‐didehydrobutyrine",,
+BGC0000447,orf00008,A2,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),44557.0,65716.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",13,@D-aThr/Thr,D,thr,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",13,D-allo-Thr,,
+BGC0000447,orf00008,A3,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),44557.0,65716.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",14,@L-Ile/aIle,L,ile,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",14,L-Ile/L-Leu,,
+BGC0000447,orf00008,A4,FALSE,L,asn(65.0);asp(65.0);gln(60.0);glu(60.0);aad(60.0),44557.0,65716.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",15,@L-Hse,L,hse,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",15,L-Hse,,
+BGC0000447,orf00008,A5,FALSE,D,dab(100.0);ala(65.0);ala-d(60.0);val(60.0);gly(55.0),44557.0,65716.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",16,@D-Dab,D,dab,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",16,D-Dab,,
+BGC0000447,orf00008,A6,FALSE,L,bmt(50.0);end(50.0);cha(50.0);dab(40.0);hyv(40.0),44557.0,65716.0,+,BGC0000447.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16",17,@L-Lys,L,lys,"17,16,15,14,13*,12,11,10,9,8,7,6,5,4,3,2,1,0",17,L-Lys,,
+BGC0000452,orf00007,A1,FALSE,D,phe(100.0);tyr(80.0);bht(75.0);trp(70.0);uda(60.0),8543.0,11888.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",4,@D-Phe,D,phe,"0,1,2,3,4,5,6,7,8,9*",0,D-Phe,,
+BGC0000452,orf00008,A1,FALSE,L,pro(100.0);pip(75.0);uda(60.0);ala(55.0);ser(55.0),11982.0,22752.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",5,@L-Pro,L,pro,"0,1,2,3,4,5,6,7,8,9*",1,Pro,,
+BGC0000452,orf00008,A2,FALSE,L,phe(85.0);tyr(70.0);trp(65.0);bht(65.0);bmt(60.0),11982.0,22752.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",6,@L-Phe,L,phe,"0,1,2,3,4,5,6,7,8,9*",2,Phe/Trp,,
+BGC0000452,orf00008,A3,FALSE,D,phe(100.0);tyr(80.0);bht(75.0);trp(70.0);uda(60.0),11982.0,22752.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",7,@D-Phe,D,phe,"0,1,2,3,4,5,6,7,8,9*",3,D-Phe/D-Trp,,
+BGC0000452,orf00009,A1,FALSE,L,asn(100.0);asp(85.0);glu(65.0);gln(60.0);aad(55.0),22857.0,42321.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",8,@L-Asn,L,asn,"0,1,2,3,4,5,6,7,8,9*",4,Asn,,
+BGC0000452,orf00009,A2,FALSE,L,gln(100.0);glu(80.0);asp(65.0);asn(60.0);arg(55.0),22857.0,42321.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",9,@L-Gln,L,gln,"0,1,2,3,4,5,6,7,8,9*",5,Gln,,
+BGC0000452,orf00009,A3,FALSE,L,tyr(95.0);trp(70.0);phe(65.0);bht(65.0);phg(55.0),22857.0,42321.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",0,@L-Tyr,L,tyr,"0,1,2,3,4,5,6,7,8,9*",6,Tyr,,
+BGC0000452,orf00009,A4,FALSE,L,val(100.0);ile(80.0);abu(80.0);leu(75.0);ala(65.0),22857.0,42321.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",1,@L-Val,L,val,"0,1,2,3,4,5,6,7,8,9*",7,Val,,
+BGC0000452,orf00009,A5,FALSE,L,orn(100.0);dab(90.0);lys(75.0);arg(70.0);gln(50.0),22857.0,42321.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",2,@L-Orn,L,orn,"0,1,2,3,4,5,6,7,8,9*",8,Orn/Lys,,
+BGC0000452,orf00009,A6,FALSE,L,leu(100.0);ile(70.0);val(65.0);ala-d(60.0);gly(60.0),22857.0,42321.0,+,BGC0000452,"0,1,2,3,4,5,6,7,8,9*",3,@L-Leu,L,leu,"0,1,2,3,4,5,6,7,8,9*",9,Leu,,
+BGC0000461,orf00003,A1,FALSE,L,glu(60.0);arg(55.0);asp(55.0);lys(55.0);orn(55.0),783.0,22974.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",7,Glu,NA,glu,"#,0,1,2,3,4,5,6,7,8,9,10,11*",7,Glu,,
+BGC0000461,orf00003,A2,FALSE,D,asn(95.0);asp(80.0);gln(65.0);glu(65.0);aad(55.0),783.0,22974.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",8,Asn,NA,asn,"#,0,1,2,3,4,5,6,7,8,9,10,11*",8,Asn,,
+BGC0000461,orf00003,A3,FALSE,D,leu(75.0);val(70.0);ala(65.0);gly(65.0);ile(65.0),783.0,22974.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",9,Trp,NA,trp,"#,0,1,2,3,4,5,6,7,8,9,10,11*",9,Trp,,
+BGC0000461,orf00003,A4,FALSE,D,glu(65.0);arg(60.0);cit(60.0);asp(55.0);gln(55.0),783.0,22974.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",10,Orn,NA,orn,"#,0,1,2,3,4,5,6,7,8,9,10,11*",10,Orn,,
+BGC0000461,orf00003,A5,TRUE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),783.0,22974.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",11,NMe-Val,NA,val+MT,"#,0,1,2,3,4,5,6,7,8,9,10,11*",11,N-Me-Val,,
+BGC0000461,orf00004,A1,FALSE,L,ser(100.0);thr(65.0);hpg(65.0);dab(60.0);dpg(60.0),22954.0,50827.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",0,Ser,NA,ser,"#,0,1,2,3,4,5,6,7,8,9,10,11*",0,Ser,,
+BGC0000461,orf00004,A2,FALSE,D,asn(95.0);asp(80.0);gln(65.0);glu(65.0);aad(55.0),22954.0,50827.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",1,OH-Asn,NA,asn+unk,"#,0,1,2,3,4,5,6,7,8,9,10,11*",1,D-OHAsn/D-Asn,,
+BGC0000461,orf00004,A3,FALSE,L,ser(100.0);thr(65.0);hpg(65.0);dab(60.0);dpg(60.0),22954.0,50827.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",2,Ser,NA,ser,"#,0,1,2,3,4,5,6,7,8,9,10,11*",2,Ser,,
+BGC0000461,orf00004,A4,FALSE,L,gly(95.0);ala(75.0);ile(70.0);leu(65.0);val(65.0),22954.0,50827.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",3,Gly,NA,gly,"#,0,1,2,3,4,5,6,7,8,9,10,11*",3,Gly,,
+BGC0000461,orf00004,A5,TRUE,D,phe(95.0);tyr(85.0);bht(80.0);trp(75.0);uda(70.0),22954.0,50827.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",4,NMe-Phe,NA,phe+MT,"#,0,1,2,3,4,5,6,7,8,9,10,11*",4,N-Me-Phe,,
+BGC0000461,orf00004,A6,FALSE,L,phe(75.0);bht(75.0);tyr(70.0);trp(65.0);phg(60.0),22954.0,50827.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",5,Leu,NA,leu,"#,0,1,2,3,4,5,6,7,8,9,10,11*",5,Leu,,
+BGC0000461,orf00004,A7,FALSE,D,glu(60.0);arg(55.0);asp(55.0);gln(55.0);lys(50.0),22954.0,50827.0,-,BGC0000461,"#,0,1,2,3,4,5,6,7,8,9,10",6,Orn,NA,orn,"#,0,1,2,3,4,5,6,7,8,9,10,11*",6,Orn,,
+BGC0000463,-,-,,,,,,,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",0,Leu,NA,leu,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",0,Leu,,
+BGC0000463,-,-,,,,,,,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",1,Glu,NA,glu,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",1,Glu,,
+BGC0000463,orf00001,A1,FALSE,D,asp(80.0);asn(75.0);gln(75.0);glu(75.0);arg(60.0),0.0,25461.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",2,Gln,NA,gln,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",2,Gln,,
+BGC0000463,orf00001,A2,FALSE,D,val(95.0);abu(80.0);ile(75.0);leu(75.0);ala(60.0),0.0,25461.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",3,Val,NA,val,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",3,Val,,
+BGC0000463,orf00001,A3,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),0.0,25461.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",4,Leu,NA,leu,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",4,Leu,,
+BGC0000463,orf00001,A4,FALSE,D,asp(80.0);asn(75.0);gln(75.0);glu(75.0);arg(60.0),0.0,25461.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",5,Gln,NA,gln,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",5,Gln,,
+BGC0000463,orf00001,A5,FALSE,D,ser(95.0);hpg(70.0);thr(65.0);dpg(65.0);allothr(60.0),0.0,25461.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",6,Ser,NA,ser,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",6,Ser,,
+BGC0000463,orf00001,A6,FALSE,D,val(95.0);abu(80.0);ile(75.0);leu(75.0);ala(60.0),0.0,25461.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",7,Val,NA,val,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",7,Val,,
+BGC0000463,orf00001,A7,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),0.0,25461.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",8,Leu,NA,leu,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",8,Leu,,
+BGC0000463,orf00001,A8,FALSE,D,asp(80.0);asn(75.0);gln(75.0);glu(75.0);arg(60.0),0.0,25461.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",9,Gln,NA,gln,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",9,Gln,,
+BGC0000463,orf00002,A1,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),25457.0,39980.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",10,Leu,NA,leu,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",10,Leu,,
+BGC0000463,orf00002,A2,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),25457.0,39980.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",11,Leu,NA,leu,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",11,Leu,,
+BGC0000463,orf00002,A3,FALSE,D,asp(80.0);asn(75.0);gln(75.0);glu(75.0);arg(60.0),25457.0,39980.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",12,Gln,NA,gln,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",12,Gln,,
+BGC0000463,orf00002,A4,FALSE,L,ile(90.0);leu(85.0);val(85.0);abu(70.0);ala(65.0),25457.0,39980.0,+,BGC0000463.1,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",13,Ile/aIle,NA,ile,"13,12,11,10,9,8,7,6*,5,4,3,2,1,0",13,Ile,,
+BGC0000464,orf00008,A1,FALSE,L,pro(100.0);pip(75.0);uda(60.0);ala(55.0);ala-d(50.0),8762.0,31655.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",0,@L-Pro,L,pro,"12,11,10,9,8,7,6,5*,4,3,2,1,0",0,Pro,,
+BGC0000464,orf00008,A2,FALSE,D,ala(90.0);gly(75.0);val(65.0);ala-d(60.0);ile(60.0),8762.0,31655.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",1,@D-Ala,D,ala,"12,11,10,9,8,7,6,5*,4,3,2,1,0",1,Ala,,
+BGC0000464,orf00008,A3,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(75.0);ala(60.0),8762.0,31655.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",2,@L-Val,L,val,"12,11,10,9,8,7,6,5*,4,3,2,1,0",2,Val,,
+BGC0000464,orf00008,A4,FALSE,D,phe(75.0);trp(75.0);bht(75.0);tyr(70.0);met(60.0),8762.0,31655.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",3,@D-Leu,D,leu,"12,11,10,9,8,7,6,5*,4,3,2,1,0",3,Ile,,
+BGC0000464,orf00008,A5,FALSE,L,ile(85.0);leu(80.0);val(80.0);abu(70.0);gly(65.0),8762.0,31655.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",4,@L-Ile/aIle,L,ile,"12,11,10,9,8,7,6,5*,4,3,2,1,0",4,Leu,,
+BGC0000464,orf00008,A6,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),8762.0,31655.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",5,@D-aThr/Thr,D,thr,"12,11,10,9,8,7,6,5*,4,3,2,1,0",5,Thr,,
+BGC0000464,orf00008,A7,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(75.0);ala(60.0),8762.0,31655.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",6,@L-Val,L,val,"12,11,10,9,8,7,6,5*,4,3,2,1,0",6,Val,,
+BGC0000464,orf00009,A1,FALSE,D,ile(85.0);leu(80.0);val(80.0);abu(70.0);gly(65.0),31669.0,38383.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",7,@D-Val,D,val,"12,11,10,9,8,7,6,5*,4,3,2,1,0",7,Val,,
+BGC0000464,orf00009,A2,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(75.0);ala(60.0),31669.0,38383.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",8,@L-Val,L,val,"12,11,10,9,8,7,6,5*,4,3,2,1,0",8,Val,,
+BGC0000464,orf00010,A1,FALSE,D,ala(100.0);gly(70.0);ala-d(65.0);ile(60.0);val(60.0),38397.0,53205.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",9,@D-Ala,D,ala,"12,11,10,9,8,7,6,5*,4,3,2,1,0",9,Ala,,
+BGC0000464,orf00010,A2,FALSE,L,tyr(60.0);b-ala(60.0);trp(55.0);bht(55.0);phe(50.0),38397.0,53205.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",10,bAla,NA,b-ala,"12,11,10,9,8,7,6,5*,4,3,2,1,0",10,Ala,,
+BGC0000464,orf00010,A3,FALSE,L,pro(100.0);pip(75.0);uda(60.0);ala(55.0);ala-d(50.0),38397.0,53205.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",11,@D-Pro,D,pro,"12,11,10,9,8,7,6,5*,4,3,2,1,0",11,Pro,,
+BGC0000464,orf00010,A4,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(75.0);ala(60.0),38397.0,53205.0,+,BGC0000464.1,"#,0,1,2,3,4,5,6,7,8,9,10,11",12,@L-Val,L,val,"12,11,10,9,8,7,6,5*,4,3,2,1,0",12,Val,,
+BGC0001127,-,-,,,,,,,BGC0001127,"#,0,1,2,3,4,5,6,7",0,dhAbu,NA,abu+unk,,,,,
+BGC0001127,-,-,,,,,,,BGC0001127,"#,0,1,2,3,4,5,6,7",6,dhAbu,NA,abu+unk,,,,,
+BGC0001127,orf00008,A1,FALSE,L,thr(95.0);allothr(95.0);dht(90.0);ser(75.0);hpg(60.0),6245.0,11117.0,+,BGC0001127,"#,0,1,2,3,4,5,6,7",1,@L-aThr/Thr,L,thr,,,,,
+BGC0001127,orf00009,A1,FALSE,D,thr(95.0);allothr(95.0);dht(90.0);ser(75.0);hpg(60.0),11180.0,19943.0,+,BGC0001127,"#,0,1,2,3,4,5,6,7",2,@D-aThr/Thr,D,thr,,,,,
+BGC0001127,orf00009,A2,FALSE,D,tyr(95.0);bht(90.0);phe(80.0);trp(65.0);uda(60.0),11180.0,19943.0,+,BGC0001127,"#,0,1,2,3,4,5,6,7",3,@D-Tyr,D,tyr,,,,,
+BGC0001127,orf00010,A1,FALSE,L,thr(100.0);allothr(90.0);ser(80.0);dht(80.0);hpg(60.0),20029.0,30973.0,+,BGC0001127,"#,0,1,2,3,4,5,6,7",-,-,-,-,,,,,
+BGC0001127,orf00010,A2,FALSE,D,gln(100.0);glu(80.0);asp(65.0);asn(60.0);arg(55.0),20029.0,30973.0,+,BGC0001127,"#,0,1,2,3,4,5,6,7",4,@D-Gln,D,gln,,,,,
+BGC0001127,orf00010,A3,FALSE,L,gly(95.0);ala(70.0);leu(65.0);val(65.0);abu(60.0),20029.0,30973.0,+,BGC0001127,"#,0,1,2,3,4,5,6,7",5,Gly,NA,gly,,,,,
+BGC0001127,orf00011,A1,FALSE,L,thr(100.0);allothr(90.0);ser(80.0);dht(80.0);hpg(60.0),30989.0,39770.0,+,BGC0001127,"#,0,1,2,3,4,5,6,7",7,@L-aThr/Thr,L,thr,,,,,
+BGC0001127,orf00011,A2,FALSE,L,leu(70.0);val(65.0);ala(60.0);gly(60.0);ile(60.0),30989.0,39770.0,+,BGC0001127,"#,0,1,2,3,4,5,6,7",8,@L-His,L,his,,,,,
+BGC0001131,orf00006,A1,FALSE,D,ser(100.0);hpg(65.0);thr(60.0);dab(60.0);dpg(60.0),7988.0,27977.0,+,BGC0001131,"0,1,2,3,4,5*",0,@D-Ser,D,ser,"0,1,2,3,4,5*",0,D-Ser,,
+BGC0001131,orf00006,A2,FALSE,L,arg(75.0);gln(75.0);lys(75.0);glu(70.0);uda(70.0),7988.0,27977.0,+,BGC0001131,"0,1,2,3,4,5*",1,@L-Gln,L,gln,"0,1,2,3,4,5*",1,L-Gln,,
+BGC0001131,orf00006,A3,FALSE,D,gly(65.0);ala(60.0);ile(60.0);leu(60.0);val(60.0),7988.0,27977.0,+,BGC0001131,"0,1,2,3,4,5*",2,@D-Phe,D,phe,"0,1,2,3,4,5*",2,D-Phe,,
+BGC0001131,orf00006,A4,FALSE,L,phe(75.0);trp(75.0);tyr(70.0);bht(70.0);met(60.0),7988.0,27977.0,+,BGC0001131,"0,1,2,3,4,5*",3,@L-Leu,L,leu,"0,1,2,3,4,5*",3,L-Leu,,
+BGC0001131,orf00006,A5,FALSE,D,gly(65.0);ala(60.0);ile(60.0);leu(60.0);val(60.0),7988.0,27977.0,+,BGC0001131,"0,1,2,3,4,5*",4,@D-Phe,D,phe,"0,1,2,3,4,5*",4,D-Phe,,
+BGC0001131,orf00006,A6,FALSE,L,lys(65.0);arg(60.0);bmt(60.0);end(60.0);glu(55.0),7988.0,27977.0,+,BGC0001131,"0,1,2,3,4,5*",5,@L-Lys,L,lys,"0,1,2,3,4,5*",5,L-Lys,,
+BGC0001133,orf00024,A1,FALSE,D,leu(85.0);ile(75.0);val(75.0);abu(70.0);ala(65.0),20000.0,31835.0,-,BGC0001133,"#,0,1,2,3,4,5",4,@D-Leu,D,leu,"0,1,2,3,4,5,6*",4,Leu,,
+BGC0001133,orf00024,A2,FALSE,L,leu(85.0);ile(75.0);val(75.0);abu(70.0);ala(65.0),20000.0,31835.0,-,BGC0001133,"#,0,1,2,3,4,5",5,@L-Leu,L,leu,"0,1,2,3,4,5,6*",5,Leu,,
+BGC0001133,orf00024,A3,FALSE,L,ser(100.0);hpg(65.0);thr(60.0);dpg(60.0);allothr(55.0),20000.0,31835.0,-,BGC0001133,"#,0,1,2,3,4,5",6,@L-Ala,L,ala,"0,1,2,3,4,5,6*",6,L-Ala,,
+BGC0001133,orf00025,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),31827.0,45888.0,-,BGC0001133,"#,0,1,2,3,4,5",0,@L-aThr/Thr,L,thr,"0,1,2,3,4,5,6*",0,L-Thr,,
+BGC0001133,orf00025,A2,FALSE,L,ser(100.0);hpg(65.0);thr(60.0);dpg(60.0);allothr(55.0),31827.0,45888.0,-,BGC0001133,"#,0,1,2,3,4,5",1,@L-Ala,L,ala,"0,1,2,3,4,5,6*",1,L-Ala,,
+BGC0001133,orf00025,A3,FALSE,L,leu(85.0);ile(75.0);val(75.0);abu(70.0);ala(65.0),31827.0,45888.0,-,BGC0001133,"#,0,1,2,3,4,5",2,@L-Leu,L,leu,"0,1,2,3,4,5,6*",2,Leu,,
+BGC0001133,orf00025,A4,FALSE,D,leu(85.0);ile(75.0);val(75.0);abu(70.0);ala(65.0),31827.0,45888.0,-,BGC0001133,"#,0,1,2,3,4,5",3,@D-Leu,D,leu,"0,1,2,3,4,5,6*",3,Leu,,
+BGC0001153,orf00001,A1,FALSE,D,phe(90.0);trp(65.0);uda(60.0);dab(50.0);bmt(50.0),8.0,14765.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",5,@D-Phe,D,phe,"9,8,7,6,5,4,3*,2,1,0",5,D-Ple,,
+BGC0001153,orf00001,A2,FALSE,L,ile(90.0);ala(75.0);leu(75.0);val(75.0);gly(70.0),8.0,14765.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",6,@L-Leu,L,leu,"9,8,7,6,5,4,3*,2,1,0",6,L-Leu,,
+BGC0001153,orf00001,A3,FALSE,L,dab(100.0);orn(90.0);arg(70.0);lys(65.0);uda(50.0),8.0,14765.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",7,@L-Dab,L,dab,"9,8,7,6,5,4,3*,2,1,0",7,Dab,,
+BGC0001153,orf00001,A4,FALSE,L,dab(100.0);orn(90.0);arg(70.0);lys(65.0);uda(50.0),8.0,14765.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",8,@L-Dab,L,dab,"9,8,7,6,5,4,3*,2,1,0",8,Dab,,
+BGC0001153,orf00002,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),14919.0,18228.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",9,@L-aThr/Thr,L,thr,"9,8,7,6,5,4,3*,2,1,0",9,Thr,,
+BGC0001153,orf00007,A1,FALSE,L,dab(100.0);orn(95.0);lys(70.0);arg(65.0);aeo(40.0),22064.0,40826.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",0,@L-Dab,L,dab,"9,8,7,6,5,4,3*,2,1,0",0,Dab,,
+BGC0001153,orf00007,A2,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),22064.0,40826.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",1,@L-aThr/Thr,L,thr,"9,8,7,6,5,4,3*,2,1,0",1,Thr,,
+BGC0001153,orf00007,A3,FALSE,D,dab(100.0);orn(95.0);lys(70.0);arg(65.0);aeo(40.0),22064.0,40826.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",2,@L-Dab,L,dab,"9,8,7,6,5,4,3*,2,1,0",2,L-Dab,,
+BGC0001153,orf00007,A4,FALSE,L,dab(100.0);orn(90.0);arg(70.0);lys(65.0);uda(50.0),22064.0,40826.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",3,@L-Dab,L,dab,"9,8,7,6,5,4,3*,2,1,0",3,Dab,,
+BGC0001153,orf00007,A5,FALSE,L,dab(100.0);orn(90.0);arg(70.0);lys(65.0);uda(50.0),22064.0,40826.0,+,BGC0001153,"#,0,1,2,3,4,5,6,7,8",4,@L-Dab,L,dab,"9,8,7,6,5,4,3*,2,1,0",4,Dab,,
+BGC0001189,orf00005,A1,FALSE,L,asp(100.0);asn(90.0);glu(65.0);gln(60.0);cha(60.0),6173.0,9353.0,+,BGC0001189,"#,0,1,2,3,4",0,@L-OH-Asp,L,asp+unk,"0,1,2,3,4,5",0,Asp,,L-Asp
+BGC0001189,orf00006,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),9377.0,17168.0,+,BGC0001189,"#,0,1,2,3,4",1,@D-aThr/Thr,D,thr,"0,1,2,3,4,5",1,alloThr,,D-allo-Thr
+BGC0001189,orf00006,A2,FALSE,L,asp(100.0);asn(90.0);glu(65.0);gln(60.0);cha(60.0),9377.0,17168.0,+,BGC0001189,"#,0,1,2,3,4",2,@L-Asp,L,asp,"0,1,2,3,4,5",2,Asp,,L-Asp
+BGC0001189,orf00007,A1,FALSE,D,orn(65.0);apa(60.0);ahp(60.0);arg(55.0);gln(50.0),17168.0,29036.0,+,BGC0001189,"#,0,1,2,3,4",3,@D-OH-Orn,D,orn+unk,"0,1,2,3,4,5",3,Orn,,D-Nδ-hydroxy-Orn
+BGC0001189,orf00007,A2,FALSE,L,ser(100.0);thr(65.0);hpg(65.0);dab(60.0);dpg(60.0),17168.0,29036.0,+,BGC0001189,"#,0,1,2,3,4",4,@L-Ser,L,ser,"0,1,2,3,4,5",4,Ser,,L-Ser
+BGC0001189,orf00007,A3,FALSE,L,orn(65.0);apa(60.0);ahp(60.0);arg(55.0);gln(50.0),17168.0,29036.0,+,BGC0001189,"#,0,1,2,3,4",-,-,-,-,"0,1,2,3,4,5",5,Orn,,L-Nδ-hydroxy-Orn
+BGC0001192,orf00001,A1,FALSE,D,phe(80.0);leu(75.0);trp(75.0);pro(60.0);pip(60.0),0.0,14997.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",5,@D-Leu,D,leu,"9,8,7,6,5,4*,3,2,1,0",5,D-Leu,,
+BGC0001192,orf00001,A2,FALSE,L,ile(100.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),0.0,14997.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",6,@L-Leu,L,leu,"9,8,7,6,5,4*,3,2,1,0",6,L-Leu,,
+BGC0001192,orf00001,A3,FALSE,L,dab(100.0);orn(90.0);arg(70.0);lys(65.0);uda(50.0),0.0,14997.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",7,@L-Dab,L,dab,"9,8,7,6,5,4*,3,2,1,0",7,L-Dab,,
+BGC0001192,orf00001,A4,FALSE,L,dab(100.0);orn(90.0);arg(70.0);lys(65.0);uda(50.0),0.0,14997.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",8,@L-Dab,L,dab,"9,8,7,6,5,4*,3,2,1,0",8,L-Dab,,
+BGC0001192,orf00002,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),15149.0,18458.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",9,@L-aThr/Thr,L,thr,"9,8,7,6,5,4*,3,2,1,0",9,L-Thr,,
+BGC0001192,orf00005,A1,FALSE,L,dab(100.0);orn(95.0);lys(70.0);arg(65.0);aeo(40.0),22233.0,41172.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",0,@L-Dab,L,dab,"9,8,7,6,5,4*,3,2,1,0",0,L-Dab,,
+BGC0001192,orf00005,A2,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),22233.0,41172.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",1,@L-aThr/Thr,L,thr,"9,8,7,6,5,4*,3,2,1,0",1,L-Thr,,
+BGC0001192,orf00005,A3,FALSE,D,orn(90.0);dab(90.0);lys(70.0);arg(65.0);met(40.0),22233.0,41172.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",2,@L-Dab,L,dab,"9,8,7,6,5,4*,3,2,1,0",2,D-Dab,,
+BGC0001192,orf00005,A4,FALSE,L,dab(100.0);orn(90.0);arg(70.0);lys(65.0);uda(50.0),22233.0,41172.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",3,@L-Dab,L,dab,"9,8,7,6,5,4*,3,2,1,0",3,L-Dab,,
+BGC0001192,orf00005,A5,FALSE,L,dab(100.0);orn(90.0);arg(70.0);lys(65.0);uda(50.0),22233.0,41172.0,+,BGC0001192.1,"#,0,1,2,3,4,5,6,7,8",4,@L-Dab,L,dab,"9,8,7,6,5,4*,3,2,1,0",4,L-Dab,,
+BGC0001196,orf00010,A1,FALSE,L,asn(100.0);asp(90.0);glu(65.0);gln(60.0);cha(60.0),7767.0,15696.0,-,BGC0001196,"0,1,2,3,4,5*",0,@L-Asn,L,asn,"0,1,2,3,4,5,6*",4,L-Asn,,
+BGC0001196,orf00010,A2,FALSE,D,gly(100.0);ala(75.0);leu(65.0);val(65.0);ile(60.0),7767.0,15696.0,-,BGC0001196,"0,1,2,3,4,5*",1,Gly,NA,gly,"0,1,2,3,4,5,6*",5,Gly,,
+BGC0001196,orf00011,A1,FALSE,D,leu(80.0);ile(70.0);val(70.0);hty(70.0);ala(65.0),15837.0,22680.0,-,BGC0001196,"0,1,2,3,4,5*",4,@D-Leu,D,leu,"0,1,2,3,4,5,6*",2,D-Leu,,
+BGC0001196,orf00011,A2,FALSE,L,val(85.0);leu(80.0);abu(75.0);ile(70.0);cha(70.0),15837.0,22680.0,-,BGC0001196,"0,1,2,3,4,5*",5,@L-Ile/aIle,L,ile,"0,1,2,3,4,5,6*",3,L-allo-Ile/L-Val,,
+BGC0001196,orf00012,A1,FALSE,L,ahp(70.0);apa(60.0);leu(55.0);ala(50.0);met(50.0),23189.0,30242.0,-,BGC0001196,"0,1,2,3,4,5*",2,@L-Trp,L,trp,"0,1,2,3,4,5,6*",0,L-Trp,,
+BGC0001196,orf00012,A2,FALSE,D,leu(80.0);ile(70.0);val(70.0);hty(70.0);ala(65.0),23189.0,30242.0,-,BGC0001196,"0,1,2,3,4,5*",3,@L-Leu,L,leu,"0,1,2,3,4,5,6*",1,L-Leu,,
+BGC0001207,orf00006,A1,TRUE,D,ala(70.0);phe(70.0);val(70.0);gly(65.0);leu(65.0),8135.0,27245.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",0,@D-NMe-Phe,D,phe+MT,"10,9,8,7*,6,5,4,3,2,1,0",0,Nm-Phe,N-methylated,
+BGC0001207,orf00006,A2,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),8135.0,27245.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",1,@L-Ile/aIle,L,ile,"10,9,8,7*,6,5,4,3,2,1,0",1,Ile,,
+BGC0001207,orf00006,A3,FALSE,L,ser(100.0);thr(65.0);hpg(65.0);allothr(60.0);dpg(60.0),8135.0,27245.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",2,@L-Ser,L,ser,"10,9,8,7*,6,5,4,3,2,1,0",2,Ser,,
+BGC0001207,orf00006,A4,FALSE,D,arg(75.0);gln(70.0);glu(70.0);lys(70.0);orn(65.0),8135.0,27245.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",3,@D-Gln,D,gln,"10,9,8,7*,6,5,4,3,2,1,0",3,Gln,,
+BGC0001207,orf00006,A5,FALSE,D,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),8135.0,27245.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",4,@D-Ile/aIle,D,ile,"10,9,8,7*,6,5,4,3,2,1,0",4,Ile,,
+BGC0001207,orf00006,A6,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),8135.0,27245.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",5,@L-Ile/aIle,L,ile,"10,9,8,7*,6,5,4,3,2,1,0",5,Ile,,
+BGC0001207,orf00007,A1,FALSE,L,ser(100.0);thr(65.0);hpg(65.0);allothr(60.0);dpg(60.0),27249.0,46377.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",6,@L-Ser,L,ser,"10,9,8,7*,6,5,4,3,2,1,0",6,Ser,,
+BGC0001207,orf00007,A2,FALSE,D,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),27249.0,46377.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",7,@D-aThr/Thr,D,thr,"10,9,8,7*,6,5,4,3,2,1,0",7,Thr,,
+BGC0001207,orf00007,A3,FALSE,L,ala(100.0);gly(75.0);ala-d(65.0);ile(60.0);leu(60.0),27249.0,46377.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",8,@L-Ala,L,ala,"10,9,8,7*,6,5,4,3,2,1,0",8,Ala,,
+BGC0001207,orf00007,A4,FALSE,L,uda(60.0);ala(50.0);leu(50.0);pro(50.0);val(50.0),27249.0,46377.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",9,@L-End,L,none,"10,9,8,7*,6,5,4,3,2,1,0",9,End,,
+BGC0001207,orf00007,A5,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),27249.0,46377.0,+,BGC0001207,"#,0,1,2,3,4,5,6,7,8,9",10,@L-Ile/aIle,L,ile,"10,9,8,7*,6,5,4,3,2,1,0",10,Ile,,
+BGC0001214,-,-,,,,,,,BGC0001214.1,"#,0,1,2,3,4,5",4,@L-Piz,L,piperazic,,,,,
+BGC0001214,orf00005,A1,FALSE,L,val(90.0);abu(80.0);leu(75.0);ile(70.0);cha(70.0),5164.0,16174.0,+,BGC0001214.1,"#,0,1,2,3,4,5",0,@L-NFo-Val,L,val+unk,"6,5,4,3,2,1*,0",0,L-Val/L-allo-Ile,,
+BGC0001214,orf00005,A2,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),5164.0,16174.0,+,BGC0001214.1,"#,0,1,2,3,4,5",1,@L-aThr/Thr,L,thr,"6,5,4,3,2,1*,0",1,L-Thr,,
+BGC0001214,orf00005,A3,FALSE,D,phe(80.0);trp(70.0);tyr(70.0);bht(70.0);vol(60.0),5164.0,16174.0,+,BGC0001214.1,"#,0,1,2,3,4,5",2,@D-X0,D,none,"6,5,4,3,2,1*,0",2,O-Me-L-Tyr,,
+BGC0001214,orf00006,A1,FALSE,D,val(95.0);ile(90.0);leu(80.0);abu(75.0);ala(60.0),16155.0,20772.0,+,BGC0001214.1,"#,0,1,2,3,4,5",3,@D-Ile/aIle,D,ile,"6,5,4,3,2,1*,0",3,L-Val/L-allo-Ile,,
+BGC0001214,orf00007,A1,FALSE,L,leu(80.0);ile(70.0);val(70.0);hty(70.0);ala(65.0),20774.0,31691.0,+,BGC0001214.1,"#,0,1,2,3,4,5",5,@L-Leu,L,leu,"6,5,4,3,2,1*,0",5,L-Leu,,
+BGC0001214,orf00007,A2,TRUE,L,val(95.0);abu(85.0);ile(75.0);leu(70.0);ala(60.0),20774.0,31691.0,+,BGC0001214.1,"#,0,1,2,3,4,5",6,@L-NMe-Val,L,val+MT,"6,5,4,3,2,1*,0",6,L-Val,,
+BGC0001214,orf00013,A1,FALSE,L,pro(90.0);pip(65.0);ala(50.0);ala-d(45.0);cys(45.0),35425.0,37030.0,+,BGC0001214.1,"#,0,1,2,3,4,5",-,-,-,-,"6,5,4,3,2,1*,0",4,L-pip,,
+BGC0001220,orf00068,A1,FALSE,L,ala(75.0);dab(70.0);ala-d(65.0);pro(50.0);ser(50.0),56221.0,78301.0,+,BGC0001220,"0,1,2,3,4,5*",0,@L-X0,L,none,"0,1,2,3,4,5*",0,Orn,,"4R,5Rdihydroxy-L-Orn"
+BGC0001220,orf00068,A2,FALSE,L,lys(50.0);uda(50.0);arg(45.0);gln(45.0);asn(40.0),56221.0,78301.0,+,BGC0001220,"0,1,2,3,4,5*",1,@L-aThr/Thr,L,thr,"0,1,2,3,4,5*",1,Thr,,L-Thr
+BGC0001220,orf00068,A3,FALSE,L,met(50.0);dab(50.0);ahp(50.0);aeo(40.0);hse(40.0),56221.0,78301.0,+,BGC0001220,"0,1,2,3,4,5*",2,@L-4OH-Pro,L,pro+unk,"0,1,2,3,4,5*",2,Pro,,4R-hydroxyl-L-Pro
+BGC0001220,orf00068,A4,FALSE,L,arg(50.0);asp(50.0);gln(50.0);lys(50.0);orn(50.0),56221.0,78301.0,+,BGC0001220,"0,1,2,3,4,5*",3,@L-X2,L,none,"0,1,2,3,4,5*",3,Tyr,,"3S,4S-dihydroxylL-homoTyr"
+BGC0001220,orf00068,A5,FALSE,L,uda(60.0);arg(50.0);dab(50.0);vol(50.0);asp(45.0),56221.0,78301.0,+,BGC0001220,"0,1,2,3,4,5*",4,@L-aThr/Thr,L,thr,"0,1,2,3,4,5*",4,Thr,,L-Thr
+BGC0001220,orf00068,A6,FALSE,L,gly(50.0);ala(45.0);pro(45.0);ser(45.0);val(45.0),56221.0,78301.0,+,BGC0001220,"0,1,2,3,4,5*",5,@L-X1,L,none,"0,1,2,3,4,5*",5,Pro,,"3S-hydroxyl,4Smethyl-L-Pro"
+BGC0001233,orf00017,A1,FALSE,D,pro(65.0);pip(60.0);bmt(60.0);uda(60.0);cha(60.0),21743.0,38087.0,+,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",0,Hpg,NA,hpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",0,Hpg,,
+BGC0001233,orf00017,A2,FALSE,D,cha(70.0);pro(65.0);pip(60.0);bmt(60.0);leu(55.0),21743.0,38087.0,+,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",1,Dhpg,NA,dhpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",1,Dpg,,
+BGC0001233,orf00017,A3,FALSE,L,val(95.0);abu(85.0);ile(80.0);leu(75.0);ala(60.0),21743.0,38087.0,+,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",2,Val,NA,val,"0,1,2,3,4,5,6,7,8,9,10,11,12",2,Val,,
+BGC0001233,orf00017,A4,FALSE,D,cha(70.0);pro(65.0);pip(60.0);bmt(60.0);leu(55.0),21743.0,38087.0,+,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",3,Dhpg,NA,dhpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",3,Dpg,,
+BGC0001233,orf00018,A1,FALSE,D,hpg(100.0);dpg(90.0);dhpg(80.0);dhp(80.0);ser(65.0),56647.0,61951.0,+,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",4,Hpg,NA,hpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",4,Hpg,,
+BGC0001233,orf00018,A2,-,-,cha(70.0);pro(65.0);pip(60.0);bmt(60.0);leu(55.0),,,,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",5,Dhpg,NA,dhpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",5,Dpg,,
+BGC0001233,orf00018,A3,-,-,hpg(95.0);dpg(85.0);dhpg(75.0);dhp(75.0);gly(55.0),,,,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",6,Hpg,NA,hpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",6,Hpg,,
+BGC0001233,orf00018,A4,-,-,cha(70.0);pro(65.0);pip(60.0);bmt(60.0);leu(55.0),,,,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",7,Dhpg,NA,dhpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",7,Dpg,,
+BGC0001233,orf00018,A5,-,-,val(95.0);abu(85.0);ile(80.0);leu(75.0);ala(60.0),,,,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",8,Val,NA,val,"0,1,2,3,4,5,6,7,8,9,10,11,12",8,Val,,
+BGC0001233,orf00018,A6,-,-,pro(60.0);pip(60.0);bmt(60.0);cha(60.0);leu(55.0),,,,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",9,Dhpg,NA,dhpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",9,Dpg,,
+BGC0001233,orf00019,A1,FALSE,L,hpg(100.0);dpg(95.0);dhpg(85.0);dhp(85.0);leu(55.0),61952.0,72176.0,+,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",10,Hpg,NA,hpg,"0,1,2,3,4,5,6,7,8,9,10,11,12",10,Hpg,,
+BGC0001233,orf00019,A2,FALSE,L,phe(100.0);tyr(85.0);bht(85.0);trp(80.0);bmt(60.0),61952.0,72176.0,+,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",11,Phe,NA,phe,"0,1,2,3,4,5,6,7,8,9,10,11,12",11,Phe,,
+BGC0001233,orf00019,A3,FALSE,L,asp(100.0);asn(85.0);gln(60.0);glu(60.0);lys(55.0),61952.0,72176.0,+,BGC0001233,"#,0,1,2,3,4,5,6,7,8,9,10,11",12,Asp,NA,asp,"0,1,2,3,4,5,6,7,8,9,10,11,12",12,Asp,,
+BGC0001290,orf00001,A1,FALSE,L,gly(80.0);ala(70.0);ala-d(65.0);tcl(40.0);uda(40.0),0.0,18009.0,-,BGC0001290.1,"#,0,1,2,3,4",1,Gly,NA,gly,"0,1,2,3,4*,$",0,Gly,,
+BGC0001290,orf00001,A2,FALSE,L,gln(55.0);arg(50.0);glu(50.0);lys(50.0);orn(50.0),0.0,18009.0,-,BGC0001290.1,"#,0,1,2,3,4",2,@L-Val,L,val,"0,1,2,3,4*,$",1,Val,,
+BGC0001290,orf00001,A3,FALSE,L,hty(60.0);gly(55.0);leu(55.0);ala(50.0);pro(50.0),0.0,18009.0,-,BGC0001290.1,"#,0,1,2,3,4",3,@L-Leu,L,leu,"0,1,2,3,4*,$",2,Leu,,
+BGC0001290,orf00001,A4,FALSE,L,pro(85.0);cha(60.0);ala(55.0);pip(55.0);gly(50.0),0.0,18009.0,-,BGC0001290.1,"#,0,1,2,3,4",4,@L-Ala,L,ala,"0,1,2,3,4*,$",3,Ala,,
+BGC0001290,orf00001,A5,FALSE,L,pro(70.0);ala(55.0);pip(55.0);gly(50.0);leu(50.0),0.0,18009.0,-,BGC0001290.1,"#,0,1,2,3,4",5,@L-Ala,L,ala,"0,1,2,3,4*,$",4,Ala,,
+BGC0001312,-,-,,,,,,,BGC0001312,"#,0,1,2,3,4,5,6,7",0,@L-Leu,L,leu,,,,,
+BGC0001312,-,-,,,,,,,BGC0001312,"#,0,1,2,3,4,5,6,7",1,@D-Glu,D,glu,,,,,
+BGC0001312,orf00005,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),5733.0,18618.0,+,BGC0001312,"#,0,1,2,3,4,5,6,7",2,@D-aThr/Thr,D,thr,,,,,
+BGC0001312,orf00005,A2,FALSE,D,val(100.0);abu(80.0);ile(75.0);leu(70.0);ala(65.0),5733.0,18618.0,+,BGC0001312,"#,0,1,2,3,4,5,6,7",3,@D-Val,D,val,,,,,
+BGC0001312,orf00005,A3,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),5733.0,18618.0,+,BGC0001312,"#,0,1,2,3,4,5,6,7",4,@L-Leu,L,leu,,,,,
+BGC0001312,orf00005,A4,FALSE,D,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),5733.0,18618.0,+,BGC0001312,"#,0,1,2,3,4,5,6,7",5,@D-Ser,D,ser,,,,,
+BGC0001312,orf00006,A1,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),18614.0,29936.0,+,BGC0001312,"#,0,1,2,3,4,5,6,7",6,@L-Leu,L,leu,,,,,
+BGC0001312,orf00006,A2,FALSE,D,ser(100.0);thr(70.0);hpg(65.0);allothr(60.0);dpg(60.0),18614.0,29936.0,+,BGC0001312,"#,0,1,2,3,4,5,6,7",7,@D-Ser,D,ser,,,,,
+BGC0001312,orf00006,A3,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),18614.0,29936.0,+,BGC0001312,"#,0,1,2,3,4,5,6,7",8,@L-Ile/aIle,L,ile,,,,,
+BGC0001341,orf00004,A1,FALSE,L,ala(50.0);pro(45.0);val(45.0);cys(40.0);gly(40.0),2639.0,10637.0,-,BGC0001341,"#,0",0,Lac,NA,lac,,,,,
+BGC0001341,orf00004,A2,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(75.0);ala(65.0),2639.0,10637.0,-,BGC0001341,"#,0",1,Val,NA,val,,,,,
+BGC0001341,orf00005,A1,FALSE,L,tcl(60.0);ala(45.0);gly(45.0);pro(45.0);val(45.0),10642.0,20767.0,-,BGC0001341,"#,0",0,Hiv,NA,hiv,,,,,
+BGC0001341,orf00005,A2,FALSE,D,val(100.0);ile(85.0);leu(80.0);abu(80.0);ala(65.0),10642.0,20767.0,-,BGC0001341,"#,0",1,@D-Val,D,val,,,,,
+BGC0001346,orf00003,A1,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),2410.0,8821.0,+,BGC0001346.1,"#,0,1,2,3,4,5,6",0,Leu,NA,leu,,,,,
+BGC0001346,orf00003,A2,FALSE,D,asp(100.0);asn(75.0);gln(75.0);glu(75.0);arg(55.0),2410.0,8821.0,+,BGC0001346.1,"#,0,1,2,3,4,5,6",1,Asp,NA,asp,,,,,
+BGC0001346,orf00004,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),9071.0,22079.0,+,BGC0001346.1,"#,0,1,2,3,4,5,6",2,aThr/Thr,NA,thr,,,,,
+BGC0001346,orf00004,A2,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),9071.0,22079.0,+,BGC0001346.1,"#,0,1,2,3,4,5,6",3,Ile/aIle,NA,ile,,,,,
+BGC0001346,orf00004,A3,FALSE,D,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),9071.0,22079.0,+,BGC0001346.1,"#,0,1,2,3,4,5,6",4,Leu,NA,leu,,,,,
+BGC0001346,orf00004,A4,FALSE,D,gln(80.0);glu(80.0);asp(75.0);asn(65.0);bmt(60.0),9071.0,22079.0,+,BGC0001346.1,"#,0,1,2,3,4,5,6",5,Gln,NA,gln,,,,,
+BGC0001346,orf00005,A1,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),22075.0,30376.0,+,BGC0001346.1,"#,0,1,2,3,4,5,6",6,Leu,NA,leu,,,,,
+BGC0001346,orf00005,A2,FALSE,L,ile(100.0);leu(80.0);val(80.0);abu(70.0);ala(60.0),22075.0,30376.0,+,BGC0001346.1,"#,0,1,2,3,4,5,6",7,Leu,NA,leu,,,,,
+BGC0001370,orf00016,A1,FALSE,L,ser(100.0);thr(65.0);hpg(65.0);allothr(60.0);dpg(60.0),16354.0,38248.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",0,@L-Ser,L,ser,,,,,
+BGC0001370,orf00016,A2,FALSE,L,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),16354.0,38248.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",1,@L-aThr/Thr,L,thr,,,,,
+BGC0001370,orf00016,A3,FALSE,D,trp(100.0);phe(80.0);tyr(75.0);bht(70.0);bmt(60.0),16354.0,38248.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",2,@L-Trp,L,trp,,,,,
+BGC0001370,orf00016,A4,FALSE,L,asp(100.0);asn(85.0);glu(65.0);gln(60.0);hty(60.0),16354.0,38248.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",3,@L-Asp,L,asp,,,,,
+BGC0001370,orf00016,A5,FALSE,L,asp(100.0);asn(85.0);glu(65.0);gln(60.0);hty(60.0),16354.0,38248.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",4,@L-Asp,L,asp,,,,,
+BGC0001370,orf00016,A6,FALSE,D,hpg(100.0);dpg(90.0);dhpg(80.0);dhp(80.0);ser(70.0),16354.0,38248.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",5,@D-Hpg,D,hpg,,,,,
+BGC0001370,orf00017,A1,FALSE,L,asp(100.0);asn(85.0);glu(65.0);gln(60.0);hty(60.0),38244.0,49158.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",6,@L-Asp,L,asp,,,,,
+BGC0001370,orf00017,A2,FALSE,L,gly(100.0);ala(75.0);leu(65.0);val(65.0);ile(60.0),38244.0,49158.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",7,Gly,NA,gly,,,,,
+BGC0001370,orf00017,A3,FALSE,D,asn(100.0);asp(90.0);glu(65.0);gln(60.0);cha(60.0),38244.0,49158.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",8,@D-X0,D,none,,,,,
+BGC0001370,orf00018,A1,FALSE,L,glu(75.0);asp(70.0);asn(65.0);gly(60.0);ile(60.0),49142.0,56366.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",9,@L-Glu,L,glu,,,,,
+BGC0001370,orf00018,A2,FALSE,L,trp(100.0);phe(80.0);tyr(70.0);bht(70.0);phg(50.0),49142.0,56366.0,+,BGC0001370.1,"#,0,1,2,3,4,5,6,7,8,9",10,@L-Trp,L,trp,,,,,
+BGC0001393,orf00008,A1,FALSE,L,val(90.0);ile(85.0);leu(80.0);abu(75.0);ala(70.0),5583.0,12708.0,+,BGC0001393,"0,1,2,3,4,5,6*",3,@D-Val,D,val,"0,1,2,3,4,5*",1,Val,,
+BGC0001393,orf00008,A2,FALSE,L,val(60.0);thr(55.0);ala(50.0);gly(50.0);leu(50.0),5583.0,12708.0,+,BGC0001393,"0,1,2,3,4,5,6*",4,@L-Trp,L,trp,"0,1,2,3,4,5*",2,Trp,,
+BGC0001393,orf00010,A1,FALSE,L,leu(85.0);val(75.0);ile(70.0);ala(65.0);gly(65.0),13224.0,16917.0,+,BGC0001393,"0,1,2,3,4,5,6*",5,@D-Leu,D,leu,"0,1,2,3,4,5*",3,Leu,,
+BGC0001393,orf00011,A1,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(75.0);ala(65.0),16934.0,25748.0,+,BGC0001393,"0,1,2,3,4,5,6*",6,@L-Val,L,val,"0,1,2,3,4,5*",4,Val,,
+BGC0001393,orf00011,A1,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(75.0);ala(65.0),16934.0,25748.0,+,BGC0001393,"0,1,2,3,4,5,6*",0,@D-Val,D,val,"0,1,2,3,4,5*",5,Val,,
+BGC0001393,orf00011,A1,FALSE,L,val(95.0);ile(80.0);abu(80.0);leu(75.0);ala(65.0),16934.0,25748.0,+,BGC0001393,"0,1,2,3,4,5,6*",1,@L-Val,L,val,"0,1,2,3,4,5*",6,<Val>,,
+BGC0001393,orf00013,A1,FALSE,L,cys(100.0);ser(60.0);ala(55.0);gly(55.0);thr(55.0),26468.0,28208.0,+,BGC0001393,"0,1,2,3,4,5,6*",2,@L-Cys,L,cys,"0,1,2,3,4,5*",0,Thiazolidine(Cys),,
+BGC0001402,orf00002,A1,FALSE,L,pro(70.0);dab(60.0);ala(50.0);ser(50.0);cys(45.0),2579.0,19652.0,-,BGC0001402.1,"0,1,2,3,4*",4,@L-Ser,L,ser,"0,1,2,3,4*",0,Ser,,
+BGC0001402,orf00002,A2,FALSE,L,gly(50.0);leu(50.0);ser(50.0);dab(50.0);ala(45.0),2579.0,19652.0,-,BGC0001402.1,"0,1,2,3,4*",3,@L-Abu,L,abu,"0,1,2,3,4*",1,Pro+??,,
+BGC0001402,orf00002,A3,FALSE,L,leu(85.0);ile(75.0);val(75.0);ala(70.0);ala-d(70.0),2579.0,19652.0,-,BGC0001402.1,"0,1,2,3,4*",2,@L-Cl2-Pro,L,pro+unk,"0,1,2,3,4*",2,2-amino-butyric acid(был Thr),,
+BGC0001402,orf00002,A4,FALSE,L,dab(60.0);orn(50.0);arg(45.0);asn(40.0);asp(40.0),2579.0,19652.0,-,BGC0001402.1,"0,1,2,3,4*",1,@L-Ser,L,ser,"0,1,2,3,4*",3,Ser,,
+BGC0001402,orf00002,A5,FALSE,L,ala(50.0);gly(50.0);ile(50.0);pro(50.0);val(50.0),2579.0,19652.0,-,BGC0001402.1,"0,1,2,3,4*",0,@L-bPhe,L,none,"0,1,2,3,4*",4,beta-phenylalanin,,
+BGC0001406,orf00020,A1,FALSE,L,asp(95.0);asn(85.0);gln(60.0);glu(60.0);hty(60.0),24833.0,39140.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",0,@L-Asp,L,asp,"10,9,8,7,6,5,4,3,2*,1,0",0,Asp,,
+BGC0001406,orf00020,A2,FALSE,L,ser(95.0);hpg(65.0);thr(60.0);dpg(60.0);dhpg(55.0),24833.0,39140.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",1,@L-Ser,L,ser,"10,9,8,7,6,5,4,3,2*,1,0",1,Ser,,
+BGC0001406,orf00020,A3,FALSE,L,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),24833.0,39140.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",2,@L-aThr/Thr,L,thr,"10,9,8,7,6,5,4,3,2*,1,0",2,Thr,,
+BGC0001406,orf00020,A4,FALSE,D,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),24833.0,39140.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",3,@L-aThr/Thr,L,thr,"10,9,8,7,6,5,4,3,2*,1,0",3,allo-Thr,,
+BGC0001406,orf00021,A1,FALSE,L,ser(95.0);thr(65.0);allothr(65.0);hpg(65.0);dab(60.0),39136.0,56611.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",4,@L-Ala,L,ala,"10,9,8,7,6,5,4,3,2*,1,0",4,Ala,,
+BGC0001406,orf00021,A2,FALSE,L,gly(95.0);ala(75.0);ile(70.0);leu(65.0);val(65.0),39136.0,56611.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",5,Gly,NA,gly,"10,9,8,7,6,5,4,3,2*,1,0",5,Gly,,
+BGC0001406,orf00021,A3,FALSE,L,pro(95.0);pip(75.0);ser(55.0);ala(50.0);cys(50.0),39136.0,56611.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",6,@L-3OH-Pro,L,pro+unk,"10,9,8,7,6,5,4,3,2*,1,0",6,trans-3-Hyp,,
+BGC0001406,orf00021,A4,FALSE,L,hty(60.0);vol(50.0);bmt(50.0);apa(50.0);cit(50.0),39136.0,56611.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",7,dh-Trp,NA,trp+unk,"10,9,8,7,6,5,4,3,2*,1,0",7,Z-delta-Trp,,
+BGC0001406,orf00021,A5,FALSE,D,tyr(70.0);bht(70.0);ile(55.0);leu(55.0);val(55.0),39136.0,56611.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",8,@L-X0,L,none,"10,9,8,7,6,5,4,3,2*,1,0",8,beta-Metyl-Trp,,
+BGC0001406,orf00022,A1,FALSE,L,end(50.0);bmt(40.0);hse(40.0);met(30.0);b-ala(30.0),56610.0,63810.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",9,@L-3OH-Leu,L,leu+unk,"10,9,8,7,6,5,4,3,2*,1,0",9,erythro-Hyl,,
+BGC0001406,orf00022,A2,FALSE,L,pro(80.0);pip(65.0);ala(55.0);ser(55.0);ala-d(45.0),56610.0,63810.0,+,BGC0001406,"#,0,1,2,3,4,5,6,7,8,9",10,@L-3OH-Pro,L,pro+unk,"10,9,8,7,6,5,4,3,2*,1,0",10,cis-3-Hyp,,
+BGC0001414,orf00009,A1,TRUE,L,thr(85.0);allothr(80.0);ser(65.0);hpg(60.0);dht(60.0),8500.0,31885.0,-,BGC0001414,"#,0,1,2,3,4,5,6,7,8",-,-,-,-,"9,8,7,6,5,4,3,2*,1,0",0,Ac-Val,,
+BGC0001414,orf00009,A2,FALSE,L,pro(90.0);pip(75.0);leu(50.0);ahp(50.0);ala(45.0),8500.0,31885.0,-,BGC0001414,"#,0,1,2,3,4,5,6,7,8",1,@L-4Me-Pro,L,pro+MT,"9,8,7,6,5,4,3,2*,1,0",1,Pro,,
+BGC0001414,orf00009,A3,TRUE,L,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),8500.0,31885.0,-,BGC0001414,"#,0,1,2,3,4,5,6,7,8",2,@L-NMe-Thr,L,thr+MT,"9,8,7,6,5,4,3,2*,1,0",2,NMe-Thr,,
+BGC0001414,orf00009,A4,FALSE,L,phe(75.0);tyr(75.0);bht(70.0);trp(65.0);leu(60.0),8500.0,31885.0,-,BGC0001414,"#,0,1,2,3,4,5,6,7,8",3,@L-Leu,L,leu,"9,8,7,6,5,4,3,2*,1,0",3,Leu,,
+BGC0001414,orf00009,A5,FALSE,L,pro(90.0);pip(75.0);leu(50.0);ahp(50.0);ala(45.0),8500.0,31885.0,-,BGC0001414,"#,0,1,2,3,4,5,6,7,8",4,@L-4Me-Pro,L,pro+MT,"9,8,7,6,5,4,3,2*,1,0",4,MePro,,
+BGC0001414,orf00009,A6,FALSE,L,phe(75.0);tyr(75.0);bht(70.0);trp(65.0);leu(60.0),8500.0,31885.0,-,BGC0001414,"#,0,1,2,3,4,5,6,7,8",5,@L-Leu,L,leu,"9,8,7,6,5,4,3,2*,1,0",5,Leu,,
+BGC0001414,orf00018,A1,TRUE,L,thr(85.0);allothr(80.0);ser(65.0);hpg(60.0);dht(60.0),39708.0,52146.0,+,BGC0001414,"#,0,1,2,3,4,5,6,7,8",6,@L-NMe-Val,L,val+MT,"9,8,7,6,5,4,3,2*,1,0",6,NMe-Val,,
+BGC0001414,orf00018,A2,FALSE,L,pro(100.0);pip(70.0);ala(55.0);ala-d(50.0);gly(50.0),39708.0,52146.0,+,BGC0001414,"#,0,1,2,3,4,5,6,7,8",7,@L-Pro,L,pro,"9,8,7,6,5,4,3,2*,1,0",7,Pro,,
+BGC0001414,orf00018,A3,TRUE,D,phe(75.0);tyr(75.0);bht(70.0);trp(65.0);leu(60.0),39708.0,52146.0,+,BGC0001414,"#,0,1,2,3,4,5,6,7,8",8,@L-NMe-Leu,L,leu+MT,"9,8,7,6,5,4,3,2*,1,0",8,Leu,,
+BGC0001414,orf00019,A1,FALSE,L,gly(95.0);ala(70.0);ile(65.0);val(65.0);leu(60.0),52142.0,56117.0,+,BGC0001414,"#,0,1,2,3,4,5,6,7,8",9,Gly,NA,gly,"9,8,7,6,5,4,3,2*,1,0",9,Gly,,
+BGC0001448,orf00004,A1,FALSE,L,arg(50.0);gln(50.0);asp(45.0);glu(45.0);orn(45.0),2470.0,5602.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",0,@D-bMe-Asp,D,asp+MT,,,,,
+BGC0001448,orf00014,A1,FALSE,L,asp(90.0);asn(85.0);gln(65.0);glu(65.0);orn(50.0),15318.0,24513.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",1,@L-L-Dbu/Dbu,L,none,,,,,
+BGC0001448,orf00014,A2,FALSE,D,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),15318.0,24513.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",2,@D-Val,D,val,,,,,
+BGC0001448,orf00015,A1,FALSE,L,glu(65.0);arg(55.0);asp(55.0);gln(55.0);lys(50.0),24509.0,41396.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",3,@L-Lys,L,lys,,,,,
+BGC0001448,orf00015,A2,FALSE,L,asp(90.0);asn(85.0);gln(60.0);glu(60.0);hty(60.0),24509.0,41396.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",4,@L-OH-Asp,L,asp+unk,,,,,
+BGC0001448,orf00015,A3,FALSE,L,asp(90.0);asn(85.0);gln(60.0);glu(60.0);hty(60.0),24509.0,41396.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",5,@L-Asp,L,asp,,,,,
+BGC0001448,orf00015,A4,FALSE,L,gly(100.0);ala(80.0);leu(70.0);ile(65.0);val(65.0),24509.0,41396.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",6,Gly,NA,gly,,,,,
+BGC0001448,orf00015,A5,FALSE,D,asp(90.0);asn(85.0);gln(65.0);glu(65.0);orn(50.0),24509.0,41396.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",7,@L-bMe-Asp,L,asp+MT,,,,,
+BGC0001448,orf00016,A1,FALSE,L,val(100.0);ile(85.0);leu(80.0);abu(80.0);ala(65.0),41400.0,48243.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",8,@L-Val,L,val,,,,,
+BGC0001448,orf00016,A2,FALSE,L,pro(80.0);pip(75.0);leu(50.0);met(50.0);ala(45.0),41400.0,48243.0,+,BGC0001448,"#,0,1,2,3,4,5,6,7,8",9,@L-4Me-Pro,L,pro+MT,,,,,
+BGC0001469,-,-,,,,,,,BGC0001469,"0,1,2,3,4,5,6*",4,@D-Phe,D,phe,,,,,
+BGC0001469,orf00004,A1,FALSE,D,ser(90.0);hse(60.0);ala(55.0);cys(55.0);leu(55.0),4131.0,21873.0,-,BGC0001469,"0,1,2,3,4,5,6*",6,@D-Ala,D,ala,"0,1,2,3,4,5,6*",0,D-Phe?,,Phe
+BGC0001469,orf00004,A2,FALSE,L,cys(100.0);ser(60.0);ala(55.0);gly(55.0);thr(50.0),4131.0,21873.0,-,BGC0001469,"0,1,2,3,4,5,6*",0,dhCys,NA,cys+unk,"0,1,2,3,4,5,6*",1,L-heterocycl-Cys,Heterocyclization (cyclodehydration),Cys
+BGC0001469,orf00004,A3,FALSE,L,cys(100.0);ser(60.0);ala(55.0);gly(55.0);thr(50.0),4131.0,21873.0,-,BGC0001469,"0,1,2,3,4,5,6*",1,dhCys,NA,cys+unk,"0,1,2,3,4,5,6*",2,L-heterocycl-Cys,Heterocyclization (cyclodehydration),Cys
+BGC0001469,orf00004,A4,FALSE,L,cys(100.0);ser(60.0);ala(55.0);gly(55.0);thr(50.0),4131.0,21873.0,-,BGC0001469,"0,1,2,3,4,5,6*",2,dhCys,NA,cys+unk,"0,1,2,3,4,5,6*",3,L-heterocycl-Cys,Heterocyclization (cyclodehydration),Cys
+BGC0001469,orf00004,A5,FALSE,L,cys(100.0);ser(60.0);ala(55.0);gly(55.0);thr(50.0),4131.0,21873.0,-,BGC0001469,"0,1,2,3,4,5,6*",3,@L-Cys,L,cys,"0,1,2,3,4,5,6*",4,L-heterocycl-Cys,Heterocyclization (cyclodehydration),Cys
+BGC0001469,orf00005,A1,FALSE,L,ile(100.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),21889.0,25180.0,-,BGC0001469,"0,1,2,3,4,5,6*",5,@L-Ile/aIle,L,ile,"0,1,2,3,4,5,6*",6,L-Ile,,Ile
+BGC0001532,orf00001,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),45.0,1980.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",1,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",0,Bmt,,
+BGC0001532,orf00002,A1,FALSE,L,phe(75.0);met(70.0);trp(70.0);tyr(70.0);bht(65.0),1982.0,9575.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",2,Leu,NA,leu,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",1,Val,,
+BGC0001532,orf00002,A2,FALSE,D,leu(75.0);ile(70.0);hty(70.0);ala(65.0);ala-d(65.0),1982.0,9575.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",3,@D-Orn,D,orn,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",2,Lys,,
+BGC0001532,orf00003,A1,FALSE,L,ile(100.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),9621.0,23457.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",4,@L-Ile/aIle,L,ile,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",3,Ile,,
+BGC0001532,orf00003,A2,FALSE,L,ile(100.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),9621.0,23457.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",5,@L-Val,L,val,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",4,Val,,
+BGC0001532,orf00003,A3,FALSE,L,ile(85.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),9621.0,23457.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",6,@L-Val,L,val,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",5,Val,,
+BGC0001532,orf00003,A4,FALSE,D,leu(75.0);hty(70.0);ala(65.0);ala-d(65.0);ile(65.0),9621.0,23457.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",7,Lys,NA,lys,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",6,Lys,,
+BGC0001532,orf00004,A1,FALSE,L,ile(85.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),23474.0,37274.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",8,@L-Val,L,val,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",7,Val,,
+BGC0001532,orf00004,A2,FALSE,L,ile(85.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),23474.0,37274.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",9,Leu,NA,leu,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",8,Leu,,
+BGC0001532,orf00004,A3,,,leu(75.0);hty(70.0);ala(65.0);ala-d(65.0);ile(65.0),23474.0,37274.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",10,Lys,NA,lys,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",9,Lys,,
+BGC0001532,orf00004,A4,,,bht(75.0);phe(70.0);trp(70.0);tyr(70.0);vol(60.0),23474.0,37274.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",11,@D-Tyr,D,tyr,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",10,Phe,,
+BGC0001532,orf00005,A1,FALSE,L,leu(100.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),37358.0,44777.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",12,Leu,NA,leu,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",11,Leu,,
+BGC0001532,orf00005,A2,FALSE,L,ile(85.0);leu(80.0);val(75.0);ala(70.0);abu(70.0),37358.0,44777.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",-,-,-,-,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",12,Val,,
+BGC0001532,orf00009,A1,FALSE,L,tcl(50.0);met(30.0);sal(30.0);hyv(30.0);hty(30.0),48298.0,53542.0,+,BGC0001532,"#,0,1,2,3,4,5,6,7,8,9,10,11,12",13,Valol,NA,vol,"0,1,2,3,4,5,6,7,8,9,10,11,12,13",13,akV,,
+BGC0001565,orf00008,A1,FALSE,L,ala-d(90.0);pro(75.0);ala(70.0);leu(70.0);val(65.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",2,@D-Ala,D,ala,"0,1,2,3,4,5,6,7,8,9,10*",0,Ala,,
+BGC0001565,orf00008,A10,TRUE,L,leu(95.0);val(75.0);ala-d(70.0);ile(70.0);bmt(70.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",0,@L-NMe-Leu,L,leu+MT,"0,1,2,3,4,5,6,7,8,9,10*",9,MeLeu,,
+BGC0001565,orf00008,A11,FALSE,L,ala(90.0);pro(75.0);val(70.0);gly(65.0);leu(65.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",1,@L-Ala,L,ala,"0,1,2,3,4,5,6,7,8,9,10*",10,Ala,,
+BGC0001565,orf00008,A2,TRUE,L,leu(95.0);val(75.0);ala-d(70.0);ile(70.0);bmt(70.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",3,@L-NMe-Leu,L,leu+MT,"0,1,2,3,4,5,6,7,8,9,10*",1,MeLeu,,
+BGC0001565,orf00008,A3,TRUE,L,leu(95.0);val(75.0);ala-d(70.0);ile(70.0);bmt(70.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",4,@L-NMe-Leu,L,leu+MT,"0,1,2,3,4,5,6,7,8,9,10*",2,MeLeu,,
+BGC0001565,orf00008,A4,TRUE,L,val(95.0);leu(75.0);ala(70.0);abu(70.0);gly(65.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",5,@L-NMe-Val,L,val+MT,"0,1,2,3,4,5,6,7,8,9,10*",3,MeVal,,
+BGC0001565,orf00008,A5,TRUE,L,bmt(100.0);phe(75.0);trp(70.0);tyr(70.0);bht(70.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",6,@L-NMe-Bmt,L,bmt+MT,"0,1,2,3,4,5,6,7,8,9,10*",4,MeBmt,,
+BGC0001565,orf00008,A6,FALSE,L,abu(85.0);ile(70.0);leu(70.0);val(65.0);ala(60.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",7,@L-aThr/Thr,L,thr,"0,1,2,3,4,5,6,7,8,9,10*",5,Abu/Thr,,
+BGC0001565,orf00008,A7,TRUE,L,gly(75.0);pro(65.0);val(50.0);ser(45.0);pip(45.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",8,NMe-Gly,NA,gly+MT,"0,1,2,3,4,5,6,7,8,9,10*",6,MeGly,,
+BGC0001565,orf00008,A8,TRUE,L,leu(95.0);val(75.0);ala-d(70.0);ile(70.0);bmt(70.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",9,@L-NMe-Leu,L,leu+MT,"0,1,2,3,4,5,6,7,8,9,10*",7,MeLeu,,
+BGC0001565,orf00008,A9,FALSE,L,val(95.0);leu(75.0);pro(75.0);ala(70.0);abu(70.0),9188.0,55022.0,-,BGC0001565,"0,1,2,3,4,5,6,7,8,9,10*",10,@L-Val,L,val,"0,1,2,3,4,5,6,7,8,9,10*",8,Val,,
+BGC0001569,orf00012,A1,FALSE,L,ser(70.0);thr(70.0);allothr(65.0);dhpg(55.0);dhp(55.0),9609.0,17448.0,-,BGC0001569,"0,1,2,3,4,5*",2,@L-Orn,L,orn,,,,,
+BGC0001569,orf00012,A2,FALSE,D,asn(100.0);asp(90.0);glu(65.0);gln(60.0);cha(60.0),9609.0,17448.0,-,BGC0001569,"0,1,2,3,4,5*",3,OH-Asn,NA,asn+unk,,,,,
+BGC0001569,orf00013,A1,FALSE,L,ahp(70.0);hty(60.0);apa(60.0);ala(50.0);gly(50.0),17570.0,31769.0,-,BGC0001569,"0,1,2,3,4,5*",4,@L-Trp,L,trp,,,,,
+BGC0001569,orf00013,A2,FALSE,D,val(100.0);ile(85.0);leu(80.0);abu(80.0);ala(65.0),17570.0,31769.0,-,BGC0001569,"0,1,2,3,4,5*",5,@D-Val,D,val,,,,,
+BGC0001569,orf00013,A3,FALSE,D,leu(65.0);val(55.0);gly(50.0);ile(50.0);met(50.0),17570.0,31769.0,-,BGC0001569,"0,1,2,3,4,5*",0,@D-Leu,D,leu,,,,,
+BGC0001569,orf00013,A4,FALSE,L,val(85.0);leu(80.0);abu(75.0);ile(70.0);cha(70.0),17570.0,31769.0,-,BGC0001569,"0,1,2,3,4,5*",1,@L-Ile/aIle,L,ile,,,,,
+BGC0001582,orf00013,A1,TRUE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",-,-,-,-,"12,11,10,9,8,7,6,5,4,3*,2,1,0",0,N-Me-Val,,
+BGC0001582,orf00013,A10,TRUE,L,hty(60.0);met(50.0);dht(50.0);hse(50.0);apa(50.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",9,@L-X0,L,none,"12,11,10,9,8,7,6,5,4,3*,2,1,0",9,N-Me-4-OMe-L-Trp,,
+BGC0001582,orf00013,A11,FALSE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",10,@L-Val,L,val,"12,11,10,9,8,7,6,5,4,3*,2,1,0",10,Val,,
+BGC0001582,orf00013,A12,FALSE,L,phe(100.0);tyr(85.0);bht(85.0);trp(80.0);bmt(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",11,@L-Ph-Ser,L,none,"12,11,10,9,8,7,6,5,4,3*,2,1,0",11,Ph-L-Ser,,
+BGC0001582,orf00013,A13,FALSE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",12,@L-Val,L,val,"12,11,10,9,8,7,6,5,4,3*,2,1,0",12,Val,,
+BGC0001582,orf00013,A2,FALSE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",1,@L-Val,L,val,"12,11,10,9,8,7,6,5,4,3*,2,1,0",1,Val,,
+BGC0001582,orf00013,A3,TRUE,L,val(90.0);leu(80.0);abu(80.0);ile(75.0);ala(65.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",2,@L-NMe-aIle/NMe-Ile,L,ile+MT,"12,11,10,9,8,7,6,5,4,3*,2,1,0",2,allo-Ile,,
+BGC0001582,orf00013,A4,FALSE,L,thr(100.0);allothr(90.0);ser(80.0);dht(80.0);hpg(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",3,@L-aThr/Thr,L,thr,"12,11,10,9,8,7,6,5,4,3*,2,1,0",3,NMe-Thr,,
+BGC0001582,orf00013,A5,TRUE,L,thr(100.0);allothr(90.0);ser(80.0);dht(80.0);hpg(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",4,@L-NMe-Thr,L,thr+MT,"12,11,10,9,8,7,6,5,4,3*,2,1,0",4,Thr,,
+BGC0001582,orf00013,A6,FALSE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",5,@L-Val,L,val,"12,11,10,9,8,7,6,5,4,3*,2,1,0",5,Val,,
+BGC0001582,orf00013,A7,TRUE,L,leu(75.0);gly(70.0);val(70.0);ala(65.0);ala-d(65.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",6,@L-NMe-Leu,L,leu+MT,"12,11,10,9,8,7,6,5,4,3*,2,1,0",6,Leu,,
+BGC0001582,orf00013,A8,FALSE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",7,@L-Val,L,val,"12,11,10,9,8,7,6,5,4,3*,2,1,0",7,Val,,
+BGC0001582,orf00013,A9,TRUE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),18666.0,64407.0,-,BGC0001582,"#,0,1,2,3,4,5,6,7,8,9,10,11",8,@L-NMe-Val,L,val+MT,"12,11,10,9,8,7,6,5,4,3*,2,1,0",8,N-Me-Val,,
+BGC0001614,orf00005,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),4810.0,15850.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",5,dhAbu,NA,abu+unk,"9,8,7,6,5,4,3,2*,1,0",8,N-Me-Thr,,
+BGC0001614,orf00005,A2,FALSE,D,glu(80.0);gln(75.0);asn(65.0);asp(60.0);arg(55.0),4810.0,15850.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",6,Gln,NA,gln,"9,8,7,6,5,4,3,2*,1,0",7,Gly,,
+BGC0001614,orf00005,A3,FALSE,L,gly(95.0);ala(70.0);ile(65.0);val(65.0);leu(60.0),4810.0,15850.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",7,Gly,NA,gly,"9,8,7,6,5,4,3,2*,1,0",6,Gln,,
+BGC0001614,orf00006,A1,FALSE,D,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),15873.0,24963.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",3,aThr/Thr,NA,thr,"9,8,7,6,5,4,3,2*,1,0",5,Dhb,,
+BGC0001614,orf00006,A2,FALSE,D,tyr(100.0);bht(90.0);phe(80.0);uda(70.0);trp(65.0),15873.0,24963.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",4,Tyr,NA,tyr,"9,8,7,6,5,4,3,2*,1,0",4,Tyr,,
+BGC0001614,orf00013,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),30540.0,36987.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",1,aThr/Thr,NA,thr,"9,8,7,6,5,4,3,2*,1,0",3,Thr,,
+BGC0001614,orf00013,A2,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),30540.0,36987.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",2,aThr/Thr,NA,thr,"9,8,7,6,5,4,3,2*,1,0",2,Thr,,
+BGC0001614,orf00015,A1,TRUE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),39401.0,47882.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",8,NMe-Thr,NA,thr+MT,"9,8,7,6,5,4,3,2*,1,0",1,Thr,,
+BGC0001614,orf00015,A2,FALSE,L,gln(95.0);glu(75.0);asn(60.0);asp(60.0);arg(55.0),39401.0,47882.0,-,BGC0001614,"#,0,1,2,3,4,5,6,7,8",9,Gln,NA,gln,"9,8,7,6,5,4,3,2*,1,0",0,Dhh,,
+BGC0001628,-,-,,,,,,,BGC0001628.1,"#,0,1,2,3,4,5,6",0,Pha,NA,phe-ac,,,,,
+BGC0001628,orf00005,A1,FALSE,L,val(100.0);abu(90.0);ile(75.0);leu(70.0);ala(60.0),5222.0,12920.0,+,BGC0001628.1,"#,0,1,2,3,4,5,6",1,@L-Val,L,val,"0,1,2,3,4,5,6",0,Val,,
+BGC0001628,orf00005,A2,FALSE,D,asn(90.0);asp(90.0);gln(65.0);glu(65.0);arg(50.0),5222.0,12920.0,+,BGC0001628.1,"#,0,1,2,3,4,5,6",2,@D-Asp,D,asp,"0,1,2,3,4,5,6",1,Asp,,
+BGC0001628,orf00006,A1,FALSE,L,ala(95.0);gly(75.0);val(75.0);ala-d(70.0);ile(65.0),12931.0,20539.0,+,BGC0001628.1,"#,0,1,2,3,4,5,6",3,@L-Ala,L,ala,"0,1,2,3,4,5,6",2,Ala,,
+BGC0001628,orf00006,A2,FALSE,D,phe(75.0);bht(75.0);trp(70.0);tyr(70.0);phg(60.0),12931.0,20539.0,+,BGC0001628.1,"#,0,1,2,3,4,5,6",4,@D-3OH-Leu,D,leu+unk,"0,1,2,3,4,5,6",3,Leu,,
+BGC0001628,orf00007,A1,FALSE,L,ala(80.0);gly(70.0);ala-d(65.0);ile(65.0);leu(65.0),20599.0,32077.0,+,BGC0001628.1,"#,0,1,2,3,4,5,6",5,Gly,NA,gly,"0,1,2,3,4,5,6",4,Gly,,
+BGC0001628,orf00007,A2,FALSE,D,ala(95.0);gly(75.0);val(75.0);ala-d(70.0);ile(65.0),20599.0,32077.0,+,BGC0001628.1,"#,0,1,2,3,4,5,6",6,@D-Ala,D,ala,"0,1,2,3,4,5,6",5,Ala,,
+BGC0001628,orf00007,A3,FALSE,L,phe(80.0);trp(75.0);met(70.0);tyr(70.0);bht(70.0),20599.0,32077.0,+,BGC0001628.1,"#,0,1,2,3,4,5,6",7,@L-Phe,L,phe,"0,1,2,3,4,5,6",6,Phe,,
+BGC0001657,orf00004,A1,FALSE,L,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),5994.0,33765.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",1,@L-aThr/Thr,L,thr,"0,1,2,3,4,5,6,7,8,9,10,11*",0,Thr,,
+BGC0001657,orf00004,A2,FALSE,D,cit(70.0);arg(60.0);glu(60.0);lys(60.0);uda(60.0),5994.0,33765.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",2,@D-Arg,D,arg,"0,1,2,3,4,5,6,7,8,9,10,11*",1,Arg,,
+BGC0001657,orf00004,A3,FALSE,L,ser(100.0);thr(65.0);hpg(65.0);allothr(60.0);dpg(60.0),5994.0,33765.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",3,@L-Ser,L,ser,"0,1,2,3,4,5,6,7,8,9,10,11*",2,Ser,,
+BGC0001657,orf00004,A4,FALSE,L,gly(100.0);ala(75.0);leu(65.0);val(65.0);ile(60.0),5994.0,33765.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",4,Gly,NA,gly,"0,1,2,3,4,5,6,7,8,9,10,11*",3,Gly,,
+BGC0001657,orf00004,A5,TRUE,D,phe(95.0);tyr(85.0);bht(80.0);trp(75.0);uda(70.0),5994.0,33765.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",5,@D-NMe-Phe,D,phe+MT,"0,1,2,3,4,5,6,7,8,9,10,11*",4,Phe,,
+BGC0001657,orf00004,A6,FALSE,L,phe(75.0);bht(75.0);tyr(70.0);trp(65.0);phg(60.0),5994.0,33765.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",6,@L-Leu,L,leu,"0,1,2,3,4,5,6,7,8,9,10,11*",5,Leu,,
+BGC0001657,orf00004,A7,FALSE,D,asp(80.0);asn(70.0);arg(60.0);glu(60.0);lys(60.0),5994.0,33765.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",7,@D-Arg,D,arg,"0,1,2,3,4,5,6,7,8,9,10,11*",6,Arg,,
+BGC0001657,orf00005,A1,FALSE,L,glu(60.0);arg(55.0);asp(55.0);lys(55.0);orn(55.0),33745.0,53263.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",8,@L-Glu,L,glu,"0,1,2,3,4,5,6,7,8,9,10,11*",7,Glu,,
+BGC0001657,orf00005,A2,FALSE,D,gln(95.0);glu(75.0);asn(60.0);asp(60.0);aad(55.0),33745.0,53263.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",9,@D-Gln,D,gln,"0,1,2,3,4,5,6,7,8,9,10,11*",8,Gln,,
+BGC0001657,orf00005,A3,FALSE,D,leu(75.0);val(70.0);gly(65.0);ile(65.0);ala(60.0),33745.0,53263.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",10,@D-Trp,D,trp,"0,1,2,3,4,5,6,7,8,9,10,11*",9,Trp,,
+BGC0001657,orf00005,A4,FALSE,L,val(100.0);ile(85.0);abu(80.0);leu(75.0);ala(60.0),33745.0,53263.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",11,@L-Ile/aIle,L,ile,"0,1,2,3,4,5,6,7,8,9,10,11*",10,Val/Ile,,
+BGC0001657,orf00005,A5,FALSE,L,thr(100.0);allothr(95.0);dht(90.0);ser(80.0);dhpg(60.0),33745.0,53263.0,+,BGC0001657,"#,0,1,2,3,4,5,6,7,8,9,10,11",12,@L-aThr/Thr,L,thr,"0,1,2,3,4,5,6,7,8,9,10,11*",11,Thr,,
+BGC0001796,orf00010,A1,FALSE,D,asp(65.0);glu(65.0);asn(60.0);gln(60.0);apa(60.0),7736.0,27020.0,-,BGC0001796,"#,0,1,2,3",0,@D-Tyr,D,tyr,"0,1,2,3,4",0,Phe,,
+BGC0001796,orf00010,A2,FALSE,L,ser(100.0);thr(65.0);hpg(65.0);allothr(60.0);dpg(60.0),7736.0,27020.0,-,BGC0001796,"#,0,1,2,3",1,@L-Ser,L,ser,"0,1,2,3,4",1,Ser,,
+BGC0001796,orf00010,A3,FALSE,D,leu(60.0);met(60.0);bmt(60.0);ala(55.0);ser(55.0),7736.0,27020.0,-,BGC0001796,"#,0,1,2,3",2,@D-Leu,D,leu,"0,1,2,3,4",2,Leu,,
+BGC0001796,orf00010,A4,FALSE,L,gln(75.0);glu(70.0);asn(60.0);asp(60.0);aad(55.0),7736.0,27020.0,-,BGC0001796,"#,0,1,2,3",3,@L-Trp,L,trp,"0,1,2,3,4",3,Phe,,
+BGC0001796,orf00010,A5,FALSE,L,arg(50.0);glu(50.0);orn(50.0);dab(50.0);hty(50.0),7736.0,27020.0,-,BGC0001796,"#,0,1,2,3",4,@L-Arg,L,arg,"0,1,2,3,4",4,Phe,,
+BGC0001822,orf00002,A1,FALSE,L,ser(95.0);hpg(70.0);dpg(65.0);thr(60.0);cys(55.0),1362.0,16062.0,+,BGC0001822,"#,0,1,2,3,4,5,6,7",1,Ala,NA,ala,"0,1,2,3,4,5,6,7,8,9*",2,Ala,thr+dehydration,
+BGC0001822,orf00002,A2,FALSE,D,leu(95.0);ile(75.0);val(75.0);ala-d(70.0);abu(70.0),1362.0,16062.0,+,BGC0001822,"#,0,1,2,3,4,5,6,7",2,Leu,NA,leu,"0,1,2,3,4,5,6,7,8,9*",3,Leu,none,
+BGC0001822,orf00003,A1,FALSE,L,ala(50.0);gly(50.0);met(50.0);pro(50.0);ser(50.0),16073.0,22562.0,+,BGC0001822,"#,0,1,2,3,4,5,6,7",3,X0,NA,none,"0,1,2,3,4,5,6,7,8,9*",4,Pro*,ile,
+BGC0001822,orf00003,A2,FALSE,L,cys(100.0);ser(60.0);ala(55.0);gly(55.0);thr(50.0),16073.0,22562.0,+,BGC0001822,"#,0,1,2,3,4,5,6,7",4,Cys,NA,cys,"0,1,2,3,4,5,6,7,8,9*",5,???,b_ala,
+BGC0001822,orf00004,A1,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),22558.0,32521.0,+,BGC0001822,"#,0,1,2,3,4,5,6,7",5,dhAbu,NA,abu+unk,"0,1,2,3,4,5,6,7,8,9*",6,dhAbu,none,
+BGC0001822,orf00004,A2,FALSE,L,pro(85.0);pip(85.0);ala(50.0);ala-d(50.0);cys(50.0),22558.0,32521.0,+,BGC0001822,"#,0,1,2,3,4,5,6,7",6,Hpr,NA,pip,"0,1,2,3,4,5,6,7,8,9*",7,Hpr,ile,
+BGC0001822,orf00004,A3,FALSE,L,thr(100.0);allothr(100.0);dht(100.0);ser(80.0);dhpg(60.0),22558.0,32521.0,+,BGC0001822,"#,0,1,2,3,4,5,6,7",7,aThr/Thr,NA,thr,"0,1,2,3,4,5,6,7,8,9*",8,Thr,thr,
+BGC0001822,orf00005,A1,TRUE,L,val(100.0);ile(85.0);leu(80.0);abu(80.0);ala(65.0),32517.0,37905.0,+,BGC0001822,"#,0,1,2,3,4,5,6,7",8,NMe-Val,NA,val+MT,"0,1,2,3,4,5,6,7,8,9*",9,NMe-Val,pip,
\ No newline at end of file
diff --git a/nerpa.py b/nerpa.py
index 83d1f17..5e3e34a 100755
--- a/nerpa.py
+++ b/nerpa.py
@@ -18,6 +18,7 @@
 import nerpa_utils
 import handle_rban
 import logger
+import src.markov_probability_model.main
 
 # for detecting and processing antiSMASH v.5 output
 site.addsitedir(os.path.join(nerpa_init.python_modules_dir, 'NRPSPredictor_utils'))
@@ -59,6 +60,23 @@ def parse_args(log):
     advanced_input_group.add_argument("--force-existing-outdir", dest="output_dir_reuse", action="store_true", default=False,
                                       help="don't crash if the output dir already exists")
 
+    alternative_model_group = parser.add_argument_group(
+        'Alternative model parameters',
+        'Additionally use Hidden Markov Model for calculating probabilities and compare results')
+    alternative_model_group.add_argument("--use_alternative_model", type=bool, default=False,
+                                         help="use additional model or not")
+    alternative_model_group.add_argument("--algo", nargs='+',
+                                         help="list of algorithms to use for alignment",
+                                         default=['viterbi', 'global_viterbi', 'maximum_accuracy', 'maximum_posterior_decoding'])
+    alternative_model_group.add_argument("--use_bw", type=bool, default=False,
+                                         help="use Baum-Welch for parameters estimation or not")
+    alternative_model_group.add_argument("--bw_iters", type=int, default=10,
+                                         help="number of Baum-Welch iterations")
+    alternative_model_group.add_argument("--log_alignments", type=bool, default=False,
+                                         help="pretty log alignments with marginal probabilities or not")
+    alternative_model_group.add_argument("--topk", type=list, default=[1, 3, 5, 10],
+                                         help="k value for top-k-matching in computing results")
+
     # parser.add_argument("--insertion", help="insertion score [default=-2.8]", default=-2.8, action="store")
     # parser.add_argument("--deletion", help="deletion score [default=-5]", default=-5, action="store")
     parser.add_argument('--rban-monomers-db', dest='rban_monomers', type=str, default=None,
@@ -321,6 +339,13 @@ def run(args, log):
                "--threads", str(args.threads)]
     log.info("\n======= Nerpa matching")
     nerpa_utils.sys_call(command, log, cwd=output_dir)
+    if args.use_alternative_model:
+        src.markov_probability_model.main.run(
+            data_dir=output_dir, prob_gen_filepath=os.path.join(nerpa_init.configs_dir, 'prob_gen.cfg'),
+            results_dir=os.path.join(output_dir, 'markov_probability_model_results'),
+            mibig_path=os.path.join(nerpa_init.nerpa_root_dir, 'data', 'mibig.csv'),
+            pool_sz=args.threads, algo=args.algo, use_bw=args.use_bw, bw_iters=args.bw_iters,
+            log_alignments=args.log_alignments, topk=args.topk)
     log.info("RESULTS:")
     log.info("Main report is saved to " + os.path.join(output_dir, 'report.csv'), indent=1)
     log.info("Detailed reports are saved to " + output_dir, indent=1)
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..8f0fb29
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,6 @@
+pandas
+typing
+numpy
+prettytable
+tqdm
+matplotlib
diff --git a/src/markov_probability_model/base/alphabet.py b/src/markov_probability_model/base/alphabet.py
new file mode 100644
index 0000000..108ad8f
--- /dev/null
+++ b/src/markov_probability_model/base/alphabet.py
@@ -0,0 +1,57 @@
+import abc
+from typing import List, NewType, TypeVar, Optional
+
+
+class Symbol(abc.ABC):
+    def __init__(self, name: str, modification: Optional[str], methylation: bool):
+        self.name = name
+        self.modification = modification
+        self.methylation = methylation
+
+    def __str__(self) -> str:
+        res = ''
+        if self.modification is not None:
+            res += self.modification + '-'
+        if self.methylation:
+            res += 'NMe-'
+        res += self.name
+        return res
+
+    def __eq__(self, other):
+        return str(self) == str(other)
+
+    def __hash__(self):
+        return hash(str(self))
+
+    def __repr__(self):
+        return str(self)
+
+
+class Gap(Symbol):
+    def __init__(self):
+        super().__init__('-', None, False)
+
+
+class Aminoacid(Symbol):
+    pass
+
+
+class ScoredAminoacid(Symbol):
+    def __init__(self, init_name: str, modification: Optional[str], methylation: bool):
+        super().__init__(init_name.split('(')[0], modification, methylation)
+        self._score_str: str = init_name.split('(')[1].split(')')[0]
+        self.score: float = float(self._score_str)
+
+    def __str__(self):
+        return super().__str__() + '(' + self._score_str + ')'
+
+
+AlignedAminoacid = TypeVar('AlignedAminoacid', Aminoacid, Gap)
+
+AlignedScoredAminoacid = TypeVar('AlignedScoredAminoacid', ScoredAminoacid, Gap)
+
+Alphabet = NewType('Alphabet', List[Symbol])
+
+AminoacidAlphabet = NewType('AminoacidAlphabet', List[Aminoacid])
+
+ScoredAminoacidAlphabet = NewType('ScoredAminoacidAlphabet', List[ScoredAminoacid])
diff --git a/src/markov_probability_model/base/base_sequence_id_resolver.py b/src/markov_probability_model/base/base_sequence_id_resolver.py
new file mode 100644
index 0000000..cd6a88a
--- /dev/null
+++ b/src/markov_probability_model/base/base_sequence_id_resolver.py
@@ -0,0 +1,35 @@
+import abc
+import re
+from typing import NewType, List
+
+SequenceId = NewType('SequenceId', str)
+BaseSequenceId = NewType('BaseSequenceId', str)
+
+
+class BaseSequenceIdResolver(abc.ABC):
+    @abc.abstractmethod
+    def resolve(self, sequence_id: SequenceId) -> SequenceId:
+        pass
+
+
+class SimpleBaseSequenceIdResolver(BaseSequenceIdResolver):
+    def __init__(self):
+        self._regexps: List[str] = [
+            r'BGC[0-9]{7}',
+            r'NPA[0-9]{6}',
+            r'[A-Z]{3}[0-9]{5}_variant',
+            r'[A-Z]{3}[0-9]{2}-[A-Z]{1}_variant',
+            r'antimarin[0-9]{4}_[0-9]{4,5}_variant',
+            r'streptomedb.[0-9]{2,4}_variant',
+            r'mibig_[0-9]{3}_variant',
+        ]
+
+    def resolve(self, sequence_id: SequenceId) -> SequenceId:
+        for seq_re in self._regexps:
+            matches = re.findall(seq_re, str(sequence_id))
+            if len(matches) > 0:
+                res = matches[0]
+                if res.endswith('_variant'):
+                    return res[:-len('_variant')]
+                return res
+        raise IndexError(f'Cannot resolve base for {sequence_id}')
diff --git a/src/markov_probability_model/base/sequence.py b/src/markov_probability_model/base/sequence.py
new file mode 100644
index 0000000..b973a9b
--- /dev/null
+++ b/src/markov_probability_model/base/sequence.py
@@ -0,0 +1,38 @@
+from src.markov_probability_model.base.base_sequence_id_resolver import SequenceId, BaseSequenceIdResolver, \
+    SimpleBaseSequenceIdResolver
+from src.markov_probability_model.base.alphabet import Aminoacid, ScoredAminoacid, AlignedAminoacid, \
+    AlignedScoredAminoacid
+from typing import List, Optional, Generic, TypeVar
+
+S = TypeVar('S')
+
+
+class Sequence(Generic[S]):
+    def __init__(self, sequence_id: SequenceId, symbols: List[S],
+                 base_seq_id_resolver: Optional[BaseSequenceIdResolver] = SimpleBaseSequenceIdResolver()):
+        self.sequence_id = sequence_id
+        self.symbols = symbols
+        self._base_seq_id_resolver = base_seq_id_resolver
+
+    @property
+    def base_sequence_id(self):
+        return self._base_seq_id_resolver.resolve(self.sequence_id)
+
+    def __len__(self):
+        return len(self.symbols)
+
+
+class AminoacidSequence(Sequence[Aminoacid]):
+    pass
+
+
+class ScoredAminoacidSequence(Sequence[ScoredAminoacid]):
+    pass
+
+
+class AlignedAminoacidSequence(Sequence[AlignedAminoacid]):
+    pass
+
+
+class AlignedScoredAminoacidSequence(Sequence[AlignedScoredAminoacid]):
+    pass
diff --git a/src/markov_probability_model/base/utils.py b/src/markov_probability_model/base/utils.py
new file mode 100644
index 0000000..a256158
--- /dev/null
+++ b/src/markov_probability_model/base/utils.py
@@ -0,0 +1,31 @@
+import numpy as np
+
+from typing import List
+
+
+def my_log(a):
+    if a == 0:
+        return -np.inf
+    return np.log(a)
+
+
+def my_exp(a):
+    if a == -np.inf:
+        return 0
+    res = np.exp(a)
+    if isinstance(res, np.ndarray):
+        return res[0]
+    return res
+
+
+def log_add_exp(l: List[float]):
+    l = list(filter(lambda x: x != -np.inf, l))
+    if len(l) == 0:
+        return -np.inf
+    if len(l) == 1:
+        return l[0]
+    l = sorted(l)
+    res = np.logaddexp(l[0], l[1])
+    for i in l[2:]:
+        res = np.logaddexp(res, i)
+    return res
\ No newline at end of file
diff --git a/src/markov_probability_model/data_loader/alignments_loader.py b/src/markov_probability_model/data_loader/alignments_loader.py
new file mode 100644
index 0000000..bccb280
--- /dev/null
+++ b/src/markov_probability_model/data_loader/alignments_loader.py
@@ -0,0 +1,30 @@
+import abc
+
+from typing import List, TypeVar
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.data_loader.data_loader import PairwiseAlignmentDataLoader, TwoSequenceListsData
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence
+from src.markov_probability_model.base.alphabet import Gap, Aminoacid, ScoredAminoacid
+
+
+class AlignmentsLoader(PairwiseAlignmentDataLoader):
+    @abc.abstractmethod
+    def load_alignments(self) -> List[PairwiseAlignmentOutputWithLogs]:
+        pass
+
+    def load_data(self) -> TwoSequenceListsData:
+        alignments = self.load_alignments()
+        seqs1: List[AminoacidSequence] = []
+        seqs2: List[ScoredAminoacidSequence] = []
+        for alignment in alignments:
+            s1: List[Aminoacid] = []
+            for s in alignment.aligned_sequence1.symbols:
+                if s != Gap():
+                    s1.append(s)
+            seqs1.append(AminoacidSequence(alignment.aligned_sequence1.sequence_id, s1))
+            s2: List[ScoredAminoacid] = []
+            for s in alignment.aligned_sequence2.symbols:
+                if s != Gap():
+                    s2.append(s)
+            seqs2.append(ScoredAminoacidSequence(alignment.aligned_sequence2.sequence_id, s2))
+        return TwoSequenceListsData(seqs1, seqs2)
diff --git a/src/markov_probability_model/data_loader/data_loader.py b/src/markov_probability_model/data_loader/data_loader.py
new file mode 100644
index 0000000..8d23d70
--- /dev/null
+++ b/src/markov_probability_model/data_loader/data_loader.py
@@ -0,0 +1,22 @@
+import abc
+
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence
+from typing import List, Generic, TypeVar
+
+D = TypeVar('D')
+
+
+class DataLoader(abc.ABC, Generic[D]):
+    @abc.abstractmethod
+    def load_data(self) -> D:
+        pass
+
+
+class TwoSequenceListsData:
+    def __init__(self, sequences1: List[AminoacidSequence], sequences2: List[ScoredAminoacidSequence]):
+        self.sequences1 = sequences1
+        self.sequences2 = sequences2
+
+
+class PairwiseAlignmentDataLoader(DataLoader[TwoSequenceListsData], abc.ABC):
+    pass
diff --git a/src/markov_probability_model/data_loader/fdr_loader.py b/src/markov_probability_model/data_loader/fdr_loader.py
new file mode 100644
index 0000000..a7e5e8d
--- /dev/null
+++ b/src/markov_probability_model/data_loader/fdr_loader.py
@@ -0,0 +1,69 @@
+import abc
+import pandas as pd
+import os
+import copy
+
+from src.markov_probability_model.pairwise_alignment.fdr import FdrData, FdrParameters, FdrGenerator
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import ScoredPairwiseAlignmentOutput
+from src.markov_probability_model.base.sequence import AlignedAminoacidSequence, AlignedScoredAminoacidSequence
+from src.markov_probability_model.base.base_sequence_id_resolver import SequenceId
+from typing import List, Dict
+
+
+class FdrLoader(abc.ABC):
+    @abc.abstractmethod
+    def load_fdr(self) -> List[Dict[str, FdrData]]:
+        pass
+
+
+class FdrGeneratorFromReport(FdrLoader):
+    def __init__(self, data_dir: str, fdr_parameters: List[FdrParameters]):
+        self._data_dir = data_dir
+        self._fdr_parameters = copy.deepcopy(fdr_parameters)
+        for f in self._fdr_parameters:
+            f.pairs_df_logpath = None
+            f.best_pairs_df_logpath = None
+
+    def load_fdr(self) -> List[Dict[str, FdrData]]:
+        report = pd.read_csv(os.path.join(self._data_dir, 'report.csv'))
+        alignments: List[ScoredPairwiseAlignmentOutput] = [
+            self.NerpaFdrAlignment(score, seq1, seq2.split('/')[-1])
+            for score, seq1, seq2 in zip(report['score'], report['mol id'], report['prediction id'])
+        ]
+        fdrs = FdrGenerator(alignments, self._fdr_parameters).generate_fdr()
+        return [{'NERPA': f} for f in fdrs]
+
+    class NerpaFdrAlignment(ScoredPairwiseAlignmentOutput):
+        def __init__(self, score: float, sequence_id1: SequenceId, sequence_id2: SequenceId):
+            super().__init__(AlignedAminoacidSequence(sequence_id1, []),
+                             AlignedScoredAminoacidSequence(sequence_id2, []))
+            self._score = score
+
+        def score(self) -> float:
+            return self._score
+
+
+class CsvFdrLoader(FdrLoader):
+    def __init__(self, data_dir: str, fdr_parameters: List[FdrParameters]):
+        self._data_dir = data_dir
+        self._fdr_parameters = fdr_parameters
+
+    def load_fdr(self) -> List[Dict[str, FdrData]]:
+        return [self._load_single_fdr(p) for p in self._fdr_parameters]
+
+    def _load_single_fdr(self, p: FdrParameters) -> Dict[str, FdrData]:
+        t = pd.read_csv(os.path.join(
+            self._data_dir, f'FDR_top{p.topk}_{p.relative_to}_scores_with_garlic.csv'))
+        return {'NERPA': FdrData(_fdr_row_to_array(t['FDR Nerpa'])),
+                'GARLIC': FdrData(_fdr_row_to_array(t['FDR Garlic']))}
+
+
+def _fdr_row_to_array(row, max_len=500) -> List[float]:
+    a = []
+    for c in row:
+        if c == '-':
+            break
+        a.append(float(c))
+    if len(a) > max_len:
+        a = a[:max_len]
+    return list(a)
diff --git a/src/markov_probability_model/data_loader/mibig_alignments_loader.py b/src/markov_probability_model/data_loader/mibig_alignments_loader.py
new file mode 100644
index 0000000..f38f8be
--- /dev/null
+++ b/src/markov_probability_model/data_loader/mibig_alignments_loader.py
@@ -0,0 +1,65 @@
+import pandas
+
+from src.markov_probability_model.data_loader.alignments_loader import AlignmentsLoader, PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.base.alphabet import Aminoacid, ScoredAminoacid, Gap
+from src.markov_probability_model.base.sequence import AlignedAminoacidSequence, AlignedScoredAminoacidSequence
+from typing import List, Tuple, Optional
+
+
+class MibigAlignmentsLoader(AlignmentsLoader):
+    def __init__(self, mibig_filepath: str):
+        self._mibig_filepath = mibig_filepath
+
+    def load_alignments(self) -> List[PairwiseAlignmentOutputWithLogs]:
+        mibig = pandas.read_csv(self._mibig_filepath)
+        outp: List[PairwiseAlignmentOutputWithLogs] = []
+        for bgc, alignment_data in mibig.groupby(mibig['BGC']):
+            sequence, prediction = [], []
+            for seq_symbol, base_seq_symbol, pred_symbols, e_domain, m_domain in zip(alignment_data['rBan AA-ID'],
+                                                                                     alignment_data['rBan AA'],
+                                                                                     alignment_data['PRED_TOP5'],
+                                                                                     alignment_data['L-/D- (E domain)'],
+                                                                                     alignment_data['M domain']):
+                if pandas.isna(seq_symbol) or seq_symbol == '-':
+                    s1 = '-'
+                    sequence.append(Gap())
+                else:
+                    s1, modification1, methylation1 = _simplify_seq_symbol(seq_symbol, base_seq_symbol)
+                    sequence.append(Aminoacid(s1, modification1, methylation1))
+
+                if pandas.isna(pred_symbols) or pred_symbols == '-':
+                    prediction.append(Gap())
+                else:
+                    s2 = _choose_pred_symbol(pred_symbols, s1)
+                    modification2: str = None if pandas.isna(e_domain) or e_domain == '-' else '@' + e_domain
+                    methylation2: bool = False if pandas.isna(m_domain) or m_domain == '-' else (
+                                m_domain.lower() == 'true')
+                    prediction.append(ScoredAminoacid(s2, modification2, methylation2))
+
+            outp.append(PairwiseAlignmentOutputWithLogs(
+                AlignedAminoacidSequence(bgc, sequence), AlignedScoredAminoacidSequence(bgc, prediction), logs=''))
+        return outp
+
+
+def _simplify_base_seq_symbol(s: str) -> str:
+    return s.split('+')[0]
+
+
+def _simplify_seq_symbol(s: str, base_s: str) -> Tuple[str, Optional[str], bool]:
+    modification = None
+    if '@L' in s:
+        modification = '@L'
+    elif '@D' in s:
+        modification = '@D'
+    return _simplify_base_seq_symbol(base_s), modification, ('NMe' in s)
+
+
+def _choose_pred_symbol(pred_symbols, seq_symbol) -> str:
+    if pandas.isna(pred_symbols):
+        return '-'
+    pred_symbols = pred_symbols.split(';')
+    base_symbols, scores = zip(*[(s.split('(')[0], float(s.split('(')[1].split(')')[0])) for s in pred_symbols])
+    max_score_base_symbols = [base_symbols[i] for i in range(len(base_symbols)) if scores[i] == scores[0]]
+    if seq_symbol in max_score_base_symbols:
+        return pred_symbols[max_score_base_symbols.index(seq_symbol)]
+    return pred_symbols[0]
diff --git a/src/markov_probability_model/data_loader/pickle_data_loader.py b/src/markov_probability_model/data_loader/pickle_data_loader.py
new file mode 100644
index 0000000..f9d2ee9
--- /dev/null
+++ b/src/markov_probability_model/data_loader/pickle_data_loader.py
@@ -0,0 +1,33 @@
+import pickle
+import os
+
+from src.markov_probability_model.data_loader.data_loader import PairwiseAlignmentDataLoader, TwoSequenceListsData
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence, SequenceId
+from src.markov_probability_model.base.alphabet import Aminoacid, ScoredAminoacid
+from typing import List
+
+
+class PickleDataLoader(PairwiseAlignmentDataLoader):
+    def __init__(self, data_dir: str):
+        self._data_dir = data_dir
+
+    def load_data(self) -> TwoSequenceListsData:
+        structures = self._load_sequences1()
+        predictions = self._load_sequences2()
+        return TwoSequenceListsData(structures, predictions)
+
+    def _load_sequences1(self) -> List[AminoacidSequence]:
+        structs = pickle.load(open(os.path.join(self._data_dir, 'structures.pickle'), 'rb'))
+        structures: List[AminoacidSequence] = []
+        for bgc, struct in structs.items():
+            structures.append(AminoacidSequence(bgc, [Aminoacid(s.lower(), None, False) for s in struct]))
+        return structures
+
+    def _load_sequences2(self) -> List[ScoredAminoacidSequence]:
+        pred = pickle.load(open(os.path.join(self._data_dir, 'pred_score.pickle'), 'rb'))
+        predictions: List[ScoredAminoacidSequence] = []
+        for bgc, prs in pred.items():
+            for i, pr in enumerate(prs):
+                predictions.append(ScoredAminoacidSequence(
+                    SequenceId(f'{bgc}_{i}'), [ScoredAminoacid(s.lower(), None, False) for s in pr]))
+        return predictions
diff --git a/src/markov_probability_model/data_loader/raw_data_parser.py b/src/markov_probability_model/data_loader/raw_data_parser.py
new file mode 100644
index 0000000..e283516
--- /dev/null
+++ b/src/markov_probability_model/data_loader/raw_data_parser.py
@@ -0,0 +1,85 @@
+import os
+import re
+import sys
+
+from src.markov_probability_model.data_loader.data_loader import PairwiseAlignmentDataLoader, TwoSequenceListsData
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence, SequenceId
+from src.markov_probability_model.base.alphabet import Aminoacid, ScoredAminoacid, AminoacidAlphabet
+from typing import List, Tuple, Optional
+
+
+class RawDataParser(PairwiseAlignmentDataLoader):
+    def __init__(self, data_dir: str, old_omega_a: AminoacidAlphabet):
+        self._data_dir = data_dir
+        self._old_omega_a = old_omega_a
+
+    def load_data(self) -> TwoSequenceListsData:
+        structures = self._load_sequences1()
+        predictions = self._load_sequences2()
+        return TwoSequenceListsData(structures, predictions)
+
+    def _load_sequences1(self) -> List[AminoacidSequence]:
+        structures: List[AminoacidSequence] = []
+        with open(os.path.join(self._data_dir, 'structures.info'), 'r') as f:
+            lines = [l.rstrip() for l in f.readlines() if len(l) > 0]
+            for l in lines:
+                bgc_name = SequenceId(l.split()[0])
+                bgc_symbols = l.split()[1].split(';')[0].split(',')
+                bgc_symbols = list(map(lambda x: _parse_symbol(x, self._old_omega_a), bgc_symbols))
+                structures.append(
+                    AminoacidSequence(bgc_name,
+                                      [Aminoacid(s, modification, methylation) for s, modification, methylation in
+                                       bgc_symbols]))
+        return structures
+
+    def _load_sequences2(self) -> List[ScoredAminoacidSequence]:
+        pred: List[ScoredAminoacidSequence] = []
+        path = os.path.join(self._data_dir, 'predictions')
+        for subdir, _, files in os.walk(path):
+            if subdir != path:
+                continue
+            for file in files:
+                pred_name = SequenceId(file)
+                with open(os.path.join(subdir, file), 'r') as f:
+                    lines = f.readlines()
+                pred_symbols = []
+                for l in lines:
+                    l_split = l.split()
+                    base_name = l_split[2].split(';')[0]
+                    modification = '@D' if 'd-' in l_split[1].lower() else '@L'
+                    methylation = ('+mt' in l_split[1].lower())
+                    pred_symbols.append(ScoredAminoacid(base_name, modification, methylation))
+                pred.append(ScoredAminoacidSequence(pred_name, pred_symbols))
+        return pred
+
+
+def _parse_base_symbol(y: str, old_omega_a: AminoacidAlphabet) -> str:
+    x = y.lower()
+    for p in sorted(re.findall(r'[a-z]+', x), key=lambda a: -len(a)):
+        if p in [a.name for a in old_omega_a] and p not in ['dhpg']:
+            return p
+    if x[-2:] in ['x0', 'x1', 'x2', 'x3', 'x4']:
+        return 'none'
+    if x[-4:] in ['mabu', 'adda', 'dhpg']:
+        return x.lower()[-4:-1]
+    if x[-4:] in ['bala', 'bphe', 'corn'] or x[-5:] in ['dhabu', 'bhend', 'dhcys']:
+        return x.lower()[-3:]
+    if x[-5:] in ['valol']:
+        return 'val'
+    res = sorted(re.findall(r'[a-z]+', x), key=lambda a: -len(a))[0]
+    if res in ['put', 'end', 'hva', 'dbu', 'piz', 'hmp', 'hpr', 'dov', 'pha', 'suc', 'eta', 'hyv', 'dpb', 'ahp',
+               'uda', 'cha', 'bht', 'dhb', 'cit', 'hty', 'tcl', 'met']:
+        return res
+    sys.stderr.write(f'No alphabet symbol for {x}, returning none\n')
+    return 'none'
+
+
+def _parse_symbol(y: str, old_omega_a: AminoacidAlphabet) -> Tuple[str, Optional[str], bool]:
+    name = _parse_base_symbol(y, old_omega_a)
+    modification: Optional[str] = None
+    if '@L' in y:
+        modification = '@L'
+    elif '@D' in y:
+        modification = '@D'
+    methylation: bool = ('NMe' in y) or len(re.findall(r'[0-9]Me', y)) > 0
+    return name, modification, methylation
diff --git a/src/markov_probability_model/hmm/hmm.py b/src/markov_probability_model/hmm/hmm.py
new file mode 100644
index 0000000..e877b19
--- /dev/null
+++ b/src/markov_probability_model/hmm/hmm.py
@@ -0,0 +1,34 @@
+from typing import TypeVar, Generic, NewType, Dict, List
+
+S = TypeVar('S')
+O = TypeVar('O')
+
+Prob = NewType('Prob', float)
+
+
+class HMM(Generic[S, O]):
+    def __init__(self, start_probs: Dict[S, Prob],
+                 transition_probs: Dict[S, Dict[S, Prob]],
+                 observation_probs: Dict[S, Dict[O, Prob]]):
+        self._start_probs = start_probs
+        self._transition_probs = transition_probs
+        self._observation_probs = observation_probs
+
+    @property
+    def states(self) -> List[S]:
+        return list(self._start_probs.keys())
+
+    def observations(self, s: S) -> List[O]:
+        return list(self._observation_probs[s].keys())
+
+    def start_prob(self, s: S) -> Prob:
+        return self._start_probs[s]
+
+    def transition_prob(self, frm: S, to: S) -> Prob:
+        return self._transition_probs[frm][to]
+
+    def observation_prob(self, s: S, o: O) -> Prob:
+        return self._observation_probs[s][o]
+
+    def state_index(self, s: S) -> int:
+        return self.states.index(s)
diff --git a/src/markov_probability_model/hmm/pairwise_alignment_hmm.py b/src/markov_probability_model/hmm/pairwise_alignment_hmm.py
new file mode 100644
index 0000000..6529966
--- /dev/null
+++ b/src/markov_probability_model/hmm/pairwise_alignment_hmm.py
@@ -0,0 +1,98 @@
+import numpy as np
+
+from src.markov_probability_model.hmm.hmm import HMM, Prob
+from src.markov_probability_model.base.alphabet import AminoacidAlphabet, ScoredAminoacidAlphabet, Symbol, Gap, \
+    Aminoacid, ScoredAminoacid
+from typing import Dict, NewType
+
+
+class PairwiseAlignmentHMMParameters:
+    def __init__(self,
+                 omega_a: AminoacidAlphabet, omega_b: ScoredAminoacidAlphabet,
+                 mu: np.ndarray, tau: np.ndarray,
+                 p: Dict[Aminoacid, Dict[ScoredAminoacid, Prob]],
+                 q_a: Dict[Aminoacid, Prob], q_b: Dict[ScoredAminoacid, Prob]):
+        if mu.shape != (3,) or tau.shape != (3, 3):
+            raise IndexError(f'Expected 3 HMM states for mu = {mu} and tau = {tau}')
+        self.omega_a = omega_a
+        self.omega_b = omega_b
+        self.mu = mu
+        self.tau = tau
+        self.p = p
+        self.q_a = q_a
+        self.q_b = q_b
+
+    def log_to(self, log_filepath):
+        with open(log_filepath, 'w') as log:
+            print('Omega_a: {}'.format(self.omega_a), file=log)
+            print('', file=log)
+            print('Omega_b: {}'.format(self.omega_b), file=log)
+            print(file=log)
+            print('Tau: {}'.format(self.tau), file=log)
+            print('Mu: {}'.format(self.mu), file=log)
+            # print(file=log)
+            # print('P example:', file=log)
+            # for a in [Aminoacid('arg', '@L', False)]:
+            #     for b in [ScoredAminoacid('arg(100.0)', '@L', False),
+            #               ScoredAminoacid('arg(80.0)', '@L', False),
+            #               ScoredAminoacid('arg(70.0)', '@L', False),
+            #               ScoredAminoacid('arg(60.0)', '@L', False),
+            #               ScoredAminoacid('ala(100.0)', '@L', False),
+            #               ScoredAminoacid('ala(80.0)', '@L', False),
+            #               ScoredAminoacid('ala(70.0)', '@L', False),
+            #               ScoredAminoacid('ala(60.0)', '@L', False)]:
+            #         print(f'\tp[{a}][{b}] = {self.p[a][b]}', file=log)
+            print(file=log)
+            print('p: {}'.format(self.p), file=log)
+            print(file=log)
+            print('q_a: {}'.format(self.q_a), file=log)
+            print('q_b: {}'.format(self.q_b), file=log)
+
+
+PairwiseAlignmentHmmState = NewType('PairwiseAlignmentHmmState', str)
+
+
+class PairwiseAlignmentHmmObservation:
+    def __init__(self, first: Symbol, second: Symbol):
+        self.first = first
+        self.second = second
+
+    def __hash__(self):
+        return hash(str(self))
+
+    def __str__(self):
+        return str(self.first) + '-' + str(self.second)
+
+    def __repr__(self):
+        return str(self)
+
+    def __eq__(self, other):
+        return str(self) == str(other)
+
+
+class PairwiseAlignmentHmm(HMM[PairwiseAlignmentHmmState, PairwiseAlignmentHmmObservation]):
+    def __init__(self, params: PairwiseAlignmentHMMParameters):
+        self._params = params
+        self.M = PairwiseAlignmentHmmState('M')
+        self.A = PairwiseAlignmentHmmState('A')
+        self.B = PairwiseAlignmentHmmState('B')
+        states = [self.M, self.A, self.B]
+        start_probs: Dict[PairwiseAlignmentHmmState, Prob] = dict(zip(states, list(params.mu)))
+        transition_probs: Dict[PairwiseAlignmentHmmState, Dict[PairwiseAlignmentHmmState, Prob]] = {}
+        for i, frm in enumerate(states):
+            transition_probs[frm] = {}
+            for j, to in enumerate(states):
+                transition_probs[frm][to] = params.tau[i][j]
+        observation_probs: Dict[PairwiseAlignmentHmmState, Dict[PairwiseAlignmentHmmObservation, Prob]] = {}
+        for st in states:
+            observation_probs[st] = {}
+        for a in params.omega_a:
+            observation_probs[self.A][PairwiseAlignmentHmmObservation(a, Gap())] = params.q_a[a]
+            for b in params.omega_b:
+                observation_probs[self.M][PairwiseAlignmentHmmObservation(a, b)] = params.p[a][b]
+                observation_probs[self.B][PairwiseAlignmentHmmObservation(Gap(), b)] = params.q_b[b]
+        super().__init__(start_probs, transition_probs, observation_probs)
+
+    @property
+    def parameters(self):
+        return self._params
diff --git a/src/markov_probability_model/main.py b/src/markov_probability_model/main.py
new file mode 100644
index 0000000..259e38e
--- /dev/null
+++ b/src/markov_probability_model/main.py
@@ -0,0 +1,119 @@
+import os
+import argparse
+
+from src.markov_probability_model.data_loader.mibig_alignments_loader import MibigAlignmentsLoader, \
+    PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.data_loader.data_loader import TwoSequenceListsData
+from src.markov_probability_model.data_loader.raw_data_parser import RawDataParser
+from src.markov_probability_model.data_loader.fdr_loader import FdrGeneratorFromReport
+from src.markov_probability_model.parameters.ml_parameters_estimator import MaxLikelihoodParametersEstimator
+from src.markov_probability_model.parameters.baum_welch_parameters_estimator import BaumWelchParametersEstimator
+from src.markov_probability_model.parameters.utils import get_alphabets_from_alignments
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHmm, PairwiseAlignmentHMMParameters
+from src.markov_probability_model.pairwise_alignment.algo.viterbi import Viterbi, ViterbiOutput
+from src.markov_probability_model.pairwise_alignment.algo.maximum_posterior_decoding import \
+    MaximumPosteriorDecodingOutput, MaximumPosteriorDecoding
+from src.markov_probability_model.pairwise_alignment.algo.maximum_accuracy import MaximumAccuracyOutput, MaximumAccuracy
+from src.markov_probability_model.pairwise_alignment.algo.global_viterbi import GlobalViterbi, GlobalViterbiOutput
+from src.markov_probability_model.pairwise_alignment.score_augmentations import NullHypothesisScoreAugmentator, \
+    IdentityScoreAugmentator
+from src.markov_probability_model.pairwise_alignment.alignment_generator import AllPairsAlignmentGenerator
+from src.markov_probability_model.pairwise_alignment.fdr import FdrGenerator, FdrParameters, plot_fdrs, FdrData
+from src.markov_probability_model.pairwise_alignment.logger import HtmlAlignmentsLogger
+from typing import List, Dict
+
+
+def run(data_dir: str, prob_gen_filepath: str,
+        results_dir: str, mibig_path: str, pool_sz: int, algo: List[str],
+        use_bw: bool, bw_iters: int, log_alignments: bool, topk: List[int]):
+    print('Starting alignments generation using Hidden Markov Model...')
+    print(f'Generating results for {data_dir}')
+
+    res_parameters_folder = os.path.join(results_dir, 'parameters')
+    res_fdr_folder = os.path.join(results_dir, 'fdr')
+    res_alignments_folder = os.path.join(results_dir, 'alignments')
+    for folder in [res_parameters_folder, res_fdr_folder, res_alignments_folder]:
+        if not os.path.exists(folder):
+            os.makedirs(folder)
+
+    print(' Loading Mibig alignments...')
+    ground_truth_alignments: List[PairwiseAlignmentOutputWithLogs] = \
+        MibigAlignmentsLoader(mibig_path).load_alignments()
+
+    print(' Loading data...')
+    data: TwoSequenceListsData = RawDataParser(
+        data_dir, get_alphabets_from_alignments(ground_truth_alignments)[0]).load_data()
+
+    print(' Estimating parameters...')
+    parameters: PairwiseAlignmentHMMParameters = \
+        MaxLikelihoodParametersEstimator(ground_truth_alignments, data, prob_gen_filepath,
+                                         log_dir=res_parameters_folder).calculate_parameters()
+
+    if use_bw:
+        parameters = BaumWelchParametersEstimator(ground_truth_alignments, data, prob_gen_filepath,
+                                                  init_params=parameters, n_iterations=bw_iters,
+                                                  recalculate_transition_probs=False,
+                                                  log_dir=res_parameters_folder,
+                                                  pool_sz=pool_sz).calculate_parameters()
+
+    hmm = PairwiseAlignmentHmm(parameters)
+
+    fdr_parameters: List[FdrParameters] = [
+        FdrParameters(topk, rt, None, None) for topk in topk for rt in ['mol', 'genome']]
+    all_fdr: List[Dict[str, FdrData]] = FdrGeneratorFromReport(data_dir, fdr_parameters).load_fdr()
+
+    assert len(algo) > 0
+    for algo in algo:
+        print(f' Generating {algo} alignments...')
+        score_augmentator = {'viterbi': NullHypothesisScoreAugmentator,
+                             'global_viterbi': NullHypothesisScoreAugmentator,
+                             'maximum_posterior_decoding': IdentityScoreAugmentator,
+                             'maximum_accuracy': IdentityScoreAugmentator}[algo]()
+        sequence_aligner = {'viterbi': Viterbi, 'global_viterbi': GlobalViterbi,
+                            'maximum_posterior_decoding': MaximumPosteriorDecoding,
+                            'maximum_accuracy': MaximumAccuracy}[algo](hmm, score_augmentator)
+        alignment_type = {'viterbi': ViterbiOutput, 'global_viterbi': GlobalViterbiOutput,
+                          'maximum_posterior_decoding': MaximumPosteriorDecodingOutput,
+                          'maximum_accuracy': MaximumAccuracyOutput}[algo]
+        logger = None
+        if log_alignments:
+            logger = HtmlAlignmentsLogger(os.path.join(res_alignments_folder, algo))
+        alignments = AllPairsAlignmentGenerator[alignment_type](
+            data, sequence_aligner, logger=logger, pool_sz=pool_sz).generate_alignments()
+
+        print(f' Generating {algo} FDR...')
+        fdr_parameters: List[FdrParameters] = [
+            FdrParameters(k, rt,
+                          os.path.join(res_fdr_folder, f'pairs_{algo}_{rt}.csv'),
+                          os.path.join(res_fdr_folder, f'best_pairs_{algo}_{rt}_top{k}.csv'),
+                          ) for k in topk for rt in ['mol', 'genome']
+        ]
+        algo_fdrs: List[FdrData] = FdrGenerator(alignments, fdr_parameters).generate_fdr()
+        for i, fdr in enumerate(algo_fdrs):
+            all_fdr[i][algo] = fdr
+
+    print(' Saving FDRs...')
+    plot_fdrs(fdr_parameters, all_fdr, save_dir=res_fdr_folder)
+
+    print(' Done!')
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--data_dir', type=str, default='data/sequences/res_small_with_modifications')
+    parser.add_argument('--results_dir', type=str, default='results/res_small')
+    parser.add_argument('--mibig_path', type=str, default='data/sequences/mibig.csv')
+    parser.add_argument('--pool_sz', type=int, default=4)
+
+    parser.add_argument('--algo', nargs='+',
+                        default=['viterbi', 'global_viterbi', 'maximum_accuracy', 'maximum_posterior_decoding'])
+    parser.add_argument('--use_bw', type=bool, default=False)
+    parser.add_argument('--bw_iters', type=int, default=10)  # 10-15 is enough
+    parser.add_argument('--log_alignments', type=bool, default=False)
+
+    parser.add_argument('--topk', type=list, default=[1, 3, 5, 10])
+
+    args = parser.parse_args()
+
+    run(args.data_dir, 'data/parameters/prob_gen.cfg', args.results_dir, args.mibig_path, args.pool_sz,
+        args.algo, args.use_bw, args.bw_iters, args.log_alignments, args.topk)
diff --git a/src/markov_probability_model/pairwise_alignment/algo/global_viterbi.py b/src/markov_probability_model/pairwise_alignment/algo/global_viterbi.py
new file mode 100644
index 0000000..4a97ee0
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/algo/global_viterbi.py
@@ -0,0 +1,39 @@
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import ScoredPairwiseAlignmentOutput, \
+    PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence, \
+    AlignedAminoacidSequence, AlignedScoredAminoacidSequence
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHmm
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseSequenceAligner
+from src.markov_probability_model.pairwise_alignment.score_augmentations import ScoreAugmentator
+from src.markov_probability_model.pairwise_alignment.algo.utils import calculate_log_alpha
+from src.markov_probability_model.pairwise_alignment.algo.viterbi import Viterbi, ViterbiOutput
+from src.markov_probability_model.base.utils import log_add_exp
+
+
+class GlobalViterbiOutput(PairwiseAlignmentOutputWithLogs, ScoredPairwiseAlignmentOutput):
+    def __init__(self, aligned_sequence1: AlignedAminoacidSequence, aligned_sequence2: AlignedScoredAminoacidSequence,
+                 global_viterbi_score: float, logs: str = ''):
+        super(GlobalViterbiOutput, self).__init__(aligned_sequence1, aligned_sequence2, logs)
+        self.global_viterbi_score = global_viterbi_score
+
+    def score(self):
+        return self.global_viterbi_score
+
+
+class GlobalViterbi(PairwiseSequenceAligner[GlobalViterbiOutput]):
+    def __init__(self, hmm: PairwiseAlignmentHmm, sa: ScoreAugmentator):
+        self._hmm = hmm
+        self._sa = sa
+        self._viterbi = Viterbi(hmm, sa)
+
+    def align(self, seq1: AminoacidSequence, seq2: ScoredAminoacidSequence) -> GlobalViterbiOutput:
+        hmm = self._hmm
+        n, m, k = len(seq1.symbols), len(seq2.symbols), len(hmm.states)
+
+        alpha = calculate_log_alpha(seq1, seq2, hmm)
+        score = log_add_exp([alpha[n, m, x] for x in range(k)])
+        o: ViterbiOutput = self._viterbi.align(seq1, seq2)
+
+        return GlobalViterbiOutput(o.aligned_sequence1, o.aligned_sequence2,
+                                   self._sa.recalculate_score(score, seq1, seq2, hmm.parameters),
+                                   logs=o.logs)
diff --git a/src/markov_probability_model/pairwise_alignment/algo/maximum_accuracy.py b/src/markov_probability_model/pairwise_alignment/algo/maximum_accuracy.py
new file mode 100644
index 0000000..acb8555
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/algo/maximum_accuracy.py
@@ -0,0 +1,97 @@
+import numpy as np
+
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import ScoredPairwiseAlignmentOutput, \
+    PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence, \
+    AlignedAminoacidSequence, AlignedScoredAminoacidSequence
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHmm
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseSequenceAligner
+from src.markov_probability_model.pairwise_alignment.score_augmentations import ScoreAugmentator
+from src.markov_probability_model.pairwise_alignment.algo.utils import calculate_log_alpha, calculate_log_beta, \
+    calculate_marginal_prob, log_marginal_prob_for_alignment
+from src.markov_probability_model.base.alphabet import AlignedAminoacid, AlignedScoredAminoacid, Gap
+from typing import List
+
+
+class MaximumAccuracyOutput(PairwiseAlignmentOutputWithLogs, ScoredPairwiseAlignmentOutput):
+    def __init__(self, aligned_sequence1: AlignedAminoacidSequence, aligned_sequence2: AlignedScoredAminoacidSequence,
+                 mpd_score: float, logs: str):
+        super(MaximumAccuracyOutput, self).__init__(aligned_sequence1, aligned_sequence2, logs)
+        self.mpd_score = mpd_score
+
+    def score(self):
+        return self.mpd_score
+
+
+class MaximumAccuracy(PairwiseSequenceAligner[MaximumAccuracyOutput]):
+    def __init__(self, hmm: PairwiseAlignmentHmm, sa: ScoreAugmentator):
+        self._hmm = hmm
+        self._sa = sa
+
+    def align(self, seq1: AminoacidSequence, seq2: ScoredAminoacidSequence) -> MaximumAccuracyOutput:
+        hmm = self._hmm
+        n, m, k = len(seq1.symbols), len(seq2.symbols), len(hmm.states)
+
+        alpha = calculate_log_alpha(seq1, seq2, hmm)
+        beta = calculate_log_beta(seq1, seq2, hmm)
+        marginal_prob = calculate_marginal_prob(seq1, seq2, hmm, alpha, beta)
+
+        d = {hmm.M: (1, 1), hmm.A: (1, 0), hmm.B: (0, 1)}
+        max_accuracy = np.full((n + 1, m + 1, k), None)
+        max_accuracy[0, 0] = 0
+        prev_state = np.full((n + 1, m + 1, k), None)
+        for i in range(n + 1):
+            for j in range(m + 1):
+                for v in range(k):
+                    di, dj = d[hmm.states[v]]
+                    if di > i or dj > j:
+                        continue
+                    for prev in range(k):
+                        score = marginal_prob[i, j, v]
+                        if max_accuracy[i - di, j - dj, prev] is None:
+                            continue
+                        new_score = score + max_accuracy[i - di, j - dj, prev]
+                        if max_accuracy[i, j, v] is None or max_accuracy[i, j, v] < new_score:
+                            max_accuracy[i, j, v] = new_score
+                            prev_state[i, j, v] = prev
+
+        def log_calculate_score(v, i, j):
+            if v == 0:
+                return 'P_M({}, {}) = {}'.format(i, j, marginal_prob[i, j, v])
+            else:
+                return ''
+
+        i, j, v = n, m, 0
+        max_score = max_accuracy[i, j, v]
+        for tmp_v in range(k):
+            if max_accuracy[i, j, tmp_v] > max_accuracy[i, j, v]:
+                v = tmp_v
+                max_score = max_accuracy[i, j, tmp_v]
+        states = []
+        logs = []
+        while prev_state[i, j, v] is not None:
+            states.append(v)
+            logs.append(log_calculate_score(v, i, j))
+            di, dj = d[hmm.states[v]]
+            prev = prev_state[i, j, v]
+            v, i, j = prev, i - di, j - dj
+        logs.reverse()
+        states.reverse()
+        assert i == 0 and j == 0, 'Internal error'
+
+        aligned1: List[AlignedAminoacid] = []
+        aligned2: List[AlignedScoredAminoacid] = []
+        for st in states:
+            di, dj = d[hmm.states[st]]
+            aligned1.append(Gap() if di == 0 else seq1.symbols[i])
+            aligned2.append(Gap() if dj == 0 else seq2.symbols[j])
+            i += di
+            j += dj
+
+        aligned_seq1: AlignedAminoacidSequence = AlignedAminoacidSequence(seq1.sequence_id, aligned1)
+        aligned_seq2: AlignedScoredAminoacidSequence = AlignedScoredAminoacidSequence(seq2.sequence_id, aligned2)
+        logs.append('Marginal probs:')
+        logs.append(' '.join(map(str, log_marginal_prob_for_alignment(aligned_seq1, aligned_seq2, hmm, marginal_prob))))
+        return MaximumAccuracyOutput(aligned_seq1, aligned_seq2,
+                                     self._sa.recalculate_score(max_score, seq1, seq2, hmm.parameters),
+                                     logs='\n'.join(logs))
diff --git a/src/markov_probability_model/pairwise_alignment/algo/maximum_posterior_decoding.py b/src/markov_probability_model/pairwise_alignment/algo/maximum_posterior_decoding.py
new file mode 100644
index 0000000..8bcd250
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/algo/maximum_posterior_decoding.py
@@ -0,0 +1,102 @@
+import numpy as np
+
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import ScoredPairwiseAlignmentOutput, \
+    PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence, \
+    AlignedAminoacidSequence, AlignedScoredAminoacidSequence
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHmm
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseSequenceAligner
+from src.markov_probability_model.pairwise_alignment.score_augmentations import ScoreAugmentator
+from src.markov_probability_model.pairwise_alignment.algo.utils import calculate_log_alpha, calculate_log_beta, \
+    calculate_marginal_prob, log_marginal_prob_for_alignment
+from src.markov_probability_model.base.alphabet import AlignedAminoacid, AlignedScoredAminoacid, Gap
+from typing import List
+
+
+class MaximumPosteriorDecodingOutput(PairwiseAlignmentOutputWithLogs, ScoredPairwiseAlignmentOutput):
+    def __init__(self, aligned_sequence1: AlignedAminoacidSequence, aligned_sequence2: AlignedScoredAminoacidSequence,
+                 mpd_score: float, logs: str):
+        super(MaximumPosteriorDecodingOutput, self).__init__(aligned_sequence1, aligned_sequence2, logs)
+        self.mpd_score = mpd_score
+
+    def score(self):
+        return self.mpd_score
+
+
+class MaximumPosteriorDecoding(PairwiseSequenceAligner[MaximumPosteriorDecodingOutput]):
+    def __init__(self, hmm: PairwiseAlignmentHmm, sa: ScoreAugmentator):
+        self._hmm = hmm
+        self._sa = sa
+
+    def align(self, seq1: AminoacidSequence, seq2: ScoredAminoacidSequence) -> MaximumPosteriorDecodingOutput:
+        hmm = self._hmm
+        n, m, k = len(seq1.symbols), len(seq2.symbols), len(hmm.states)
+
+        alpha = calculate_log_alpha(seq1, seq2, hmm)
+        beta = calculate_log_beta(seq1, seq2, hmm)
+        marginal_prob = calculate_marginal_prob(seq1, seq2, hmm, alpha, beta)
+
+        d = {hmm.M: (1, 1), hmm.A: (1, 0), hmm.B: (0, 1)}
+        max_accuracy = np.full((n + 1, m + 1, k), None)
+        max_accuracy[0, 0] = 0
+        prev_state = np.full((n + 1, m + 1, k), None)
+        for i in range(n + 1):
+            for j in range(m + 1):
+                for v in range(k):
+                    di, dj = d[hmm.states[v]]
+                    if di > i or dj > j:
+                        continue
+                    for prev in range(k):
+                        score = marginal_prob[i, j, v] if v == 0 else \
+                            marginal_prob[i, :, v].sum() if v == 1 else marginal_prob[:, j, v].sum()
+                        new_score = max_accuracy[i - di, j - dj, prev]
+                        if new_score is None:
+                            continue
+                        new_score += score
+                        if max_accuracy[i, j, v] is None or max_accuracy[i, j, v] < new_score:
+                            max_accuracy[i, j, v] = new_score
+                            prev_state[i, j, v] = prev
+
+        def log_calculate_score(v, i, j):
+            if v == 0:
+                return 'P_M({}, {}) = {}'.format(i, j, marginal_prob[i, j, v])
+            elif v == 1:
+                return 'P_A({}) = {}'.format(i, marginal_prob[i, :, v].sum())
+            else:
+                return 'P_B({}) = {}'.format(j, marginal_prob[:, j, v].sum())
+
+        i, j, v = n, m, 0
+        max_score = max_accuracy[i, j, v]
+        for tmp_v in range(k):
+            if max_accuracy[i, j, tmp_v] > max_accuracy[i, j, v]:
+                v = tmp_v
+                max_score = max_accuracy[i, j, tmp_v]
+        states = []
+        logs = []
+        while prev_state[i, j, v] is not None:
+            states.append(v)
+            logs.append(log_calculate_score(v, i, j))
+            di, dj = d[hmm.states[v]]
+            prev = prev_state[i, j, v]
+            v, i, j = prev, i - di, j - dj
+        logs.reverse()
+        states.reverse()
+        assert i == 0 and j == 0, 'Internal error'
+
+        aligned1: List[AlignedAminoacid] = []
+        aligned2: List[AlignedScoredAminoacid] = []
+        for st in states:
+            di, dj = d[hmm.states[st]]
+            aligned1.append(Gap() if di == 0 else seq1.symbols[i])
+            aligned2.append(Gap() if dj == 0 else seq2.symbols[j])
+            i += di
+            j += dj
+
+        aligned_seq1: AlignedAminoacidSequence = AlignedAminoacidSequence(seq1.sequence_id, aligned1)
+        aligned_seq2: AlignedScoredAminoacidSequence = AlignedScoredAminoacidSequence(seq2.sequence_id, aligned2)
+        logs.append('Marginal probs:')
+        logs.append(' '.join(map(str, log_marginal_prob_for_alignment(aligned_seq1, aligned_seq2, hmm, marginal_prob))))
+        return MaximumPosteriorDecodingOutput(AlignedAminoacidSequence(seq1.sequence_id, aligned1),
+                                              AlignedScoredAminoacidSequence(seq2.sequence_id, aligned2),
+                                              self._sa.recalculate_score(max_score, seq1, seq2, hmm.parameters),
+                                              logs='\n'.join(logs))
diff --git a/src/markov_probability_model/pairwise_alignment/algo/utils.py b/src/markov_probability_model/pairwise_alignment/algo/utils.py
new file mode 100644
index 0000000..10f4fc0
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/algo/utils.py
@@ -0,0 +1,115 @@
+import numpy as np
+
+from src.markov_probability_model.base.alphabet import Gap
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence, AlignedAminoacid, \
+    AlignedScoredAminoacid, AlignedAminoacidSequence, AlignedScoredAminoacidSequence
+from src.markov_probability_model.base.utils import my_log, log_add_exp, my_exp
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHmm, \
+    PairwiseAlignmentHmmObservation
+from typing import Tuple, Optional, List
+
+
+def _get_symbols(seq1: AminoacidSequence, seq2: ScoredAminoacidSequence, i: int, j: int, di: int, dj: int) -> \
+        Tuple[AlignedAminoacid, AlignedScoredAminoacid]:
+    return Gap() if di == 0 else seq1.symbols[i - 1], Gap() if dj == 0 else seq2.symbols[j - 1]
+
+
+def calculate_log_alpha(seq1: AminoacidSequence, seq2: ScoredAminoacidSequence,
+                        hmm: PairwiseAlignmentHmm) -> np.ndarray:
+    n, m = len(seq1), len(seq2)
+
+    alpha = np.full((n + 1, m + 1, len(hmm.states)), -np.inf)
+    d = {hmm.M: (1, 1), hmm.A: (1, 0), hmm.B: (0, 1)}
+    for v in hmm.states:
+        di, dj = d[v]
+        symb1, symb2 = _get_symbols(seq1, seq2, di, dj, di, dj)
+        alpha[di, dj, hmm.state_index(v)] = my_log(hmm.start_prob(v)) + my_log(
+            hmm.observation_prob(v, PairwiseAlignmentHmmObservation(symb1, symb2)))
+    for i in range(n + 1):
+        for j in range(m + 1):
+            for v in hmm.states:
+                di, dj = d[v]
+                if i < di or j < dj:
+                    continue
+                symb1, symb2 = _get_symbols(seq1, seq2, i, j, di, dj)
+                s = []
+                for prev in hmm.states:
+                    s.append(alpha[i - di, j - dj, hmm.state_index(prev)] + my_log(hmm.transition_prob(prev, v)))
+
+                alpha[i, j, hmm.state_index(v)] = log_add_exp([
+                    alpha[i, j, hmm.state_index(v)],
+                    my_log(hmm.observation_prob(v, PairwiseAlignmentHmmObservation(symb1, symb2))) + log_add_exp(s)])
+    return alpha
+
+
+def calculate_log_beta(seq1: AminoacidSequence, seq2: ScoredAminoacidSequence, hmm: PairwiseAlignmentHmm) -> np.ndarray:
+    n, m = len(seq1), len(seq2)
+
+    beta = np.full((n + 1, m + 1, len(hmm.states)), -np.inf)
+    for v in hmm.states:
+        beta[n, m, hmm.state_index(v)] = 0
+    d = {hmm.M: (1, 1), hmm.A: (1, 0), hmm.B: (0, 1)}
+    for i in range(n, -1, -1):
+        for j in range(m, -1, -1):
+            if i == 0 and j == 0:
+                continue
+            for v in hmm.states:
+                for nxt in hmm.states:
+                    di, dj = d[nxt]
+                    if i + di > n or j + dj > m:
+                        continue
+                    symb1, symb2 = _get_symbols(seq1, seq2, i + di, j + dj, di, dj)
+                    beta[i, j, hmm.state_index(v)] = log_add_exp([
+                        beta[i, j, hmm.state_index(v)],
+                        beta[i + di, j + dj, hmm.state_index(nxt)] +
+                        my_log(hmm.observation_prob(nxt, PairwiseAlignmentHmmObservation(symb1, symb2))) +
+                        my_log(hmm.transition_prob(v, nxt))])
+    return beta
+
+
+def calculate_log_marginal_prob(seq1: AminoacidSequence, seq2: ScoredAminoacidSequence, hmm: PairwiseAlignmentHmm,
+                                alpha: np.ndarray, beta: np.ndarray) -> np.ndarray:
+    n, m, k = len(seq1), len(seq2), len(hmm.states)
+    sum_alpha = log_add_exp([alpha[n, m, x] for x in range(k)])
+    marginal_prob = np.zeros((n + 1, m + 1, k))
+    for i in range(n + 1):
+        for j in range(m + 1):
+            for s in range(k):
+                marginal_prob[i, j, s] = alpha[i, j, s] + beta[i, j, s] - sum_alpha
+    return marginal_prob
+
+
+def calculate_marginal_prob(seq1: AminoacidSequence, seq2: ScoredAminoacidSequence, hmm: PairwiseAlignmentHmm,
+                            alpha: np.ndarray, beta: np.ndarray) -> np.ndarray:
+    log_marginal_prob = calculate_log_marginal_prob(seq1, seq2, hmm, alpha, beta)
+    n, m, k = log_marginal_prob.shape
+    marginal_prob = np.array(
+        [[[my_exp(log_marginal_prob[i, j, p]) for p in range(k)] for j in range(m)] for i in range(n)])
+    return marginal_prob
+
+
+def _get_sequence_from_aligned(sequence):
+    return [a for a in sequence.symbols if a != Gap()]
+
+
+def log_marginal_prob_for_alignment(sequence1: AlignedAminoacidSequence, sequence2: AlignedScoredAminoacidSequence,
+                                    hmm: PairwiseAlignmentHmm,
+                                    marginal_prob: Optional[np.ndarray] = None) -> List[float]:
+    if marginal_prob is None:
+        seq1 = AminoacidSequence(sequence1.sequence_id, _get_sequence_from_aligned(sequence1))
+        seq2 = ScoredAminoacidSequence(sequence2.sequence_id, _get_sequence_from_aligned(sequence2))
+        alpha = calculate_log_alpha(seq1, seq2, hmm)
+        beta = calculate_log_beta(seq1, seq2, hmm)
+        marginal_prob = calculate_marginal_prob(seq1, seq2, hmm, alpha, beta)
+
+    d = {hmm.M: (1, 1), hmm.A: (1, 0), hmm.B: (0, 1)}
+    i, j = 0, 0
+    probs: List[float] = []
+    for k in range(len(sequence1)):
+        symb1: AlignedAminoacid = sequence1.symbols[k]
+        symb2: AlignedScoredAminoacid = sequence2.symbols[k]
+        state = hmm.A if symb2 == Gap() else hmm.B if symb1 == Gap() else hmm.M
+        i += d[state][0]
+        j += d[state][1]
+        probs.append(marginal_prob[i, j, hmm.state_index(state)])
+    return probs
diff --git a/src/markov_probability_model/pairwise_alignment/algo/viterbi.py b/src/markov_probability_model/pairwise_alignment/algo/viterbi.py
new file mode 100644
index 0000000..cc4d096
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/algo/viterbi.py
@@ -0,0 +1,127 @@
+import numpy as np
+import copy
+
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import ScoredPairwiseAlignmentOutput, \
+    PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence, \
+    AlignedAminoacidSequence, AlignedScoredAminoacidSequence
+from src.markov_probability_model.base.alphabet import Gap, Symbol, AlignedAminoacid, AlignedScoredAminoacid
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHmm, \
+    PairwiseAlignmentHmmObservation, PairwiseAlignmentHmmState
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseSequenceAligner
+from src.markov_probability_model.pairwise_alignment.score_augmentations import ScoreAugmentator
+from src.markov_probability_model.pairwise_alignment.algo.utils import log_marginal_prob_for_alignment, \
+    calculate_log_alpha
+from typing import List
+from src.markov_probability_model.base.utils import my_log, log_add_exp
+
+
+class ViterbiOutput(PairwiseAlignmentOutputWithLogs, ScoredPairwiseAlignmentOutput):
+    def __init__(self, aligned_sequence1: AlignedAminoacidSequence, aligned_sequence2: AlignedScoredAminoacidSequence,
+                 viterbi_score: float, logs: str):
+        super(ViterbiOutput, self).__init__(aligned_sequence1, aligned_sequence2, logs)
+        self.viterbi_score = viterbi_score
+
+    def score(self):
+        return self.viterbi_score
+
+
+class Viterbi(PairwiseSequenceAligner[ViterbiOutput]):
+    def __init__(self, hmm: PairwiseAlignmentHmm, sa: ScoreAugmentator):
+        self._hmm = hmm
+        self._sa = sa
+
+    def align(self, seq1: AminoacidSequence, seq2: ScoredAminoacidSequence) -> ViterbiOutput:
+        hmm = self._hmm
+        n, m, k = len(seq1.symbols), len(seq2.symbols), len(hmm.states)
+
+        f = np.full((n + 1, m + 1, k), None)
+        prev_state = np.full((n + 1, m + 1, k), None)
+
+        d = {hmm.M: (1, 1), hmm.A: (1, 0), hmm.B: (0, 1)}
+
+        for st in hmm.states:
+            i, j = d[st]
+            s1 = seq1.symbols[0] if i == 1 else Gap()
+            s2 = seq2.symbols[0] if j == 1 else Gap()
+            f[i, j, hmm.state_index(st)] = \
+                my_log(hmm.start_prob(st)) + my_log(hmm.observation_prob(st, PairwiseAlignmentHmmObservation(s1, s2)))
+
+        for i in range(n + 1):
+            for j in range(m + 1):
+                for st in hmm.states:
+                    di, dj = d[st]
+                    if i < di or j < dj:
+                        continue
+                    for frm in hmm.states:
+                        s1 = seq1.symbols[i - 1] if di == 1 else Gap()
+                        s2 = seq2.symbols[j - 1] if dj == 1 else Gap()
+                        sc = my_log(hmm.transition_prob(frm, st)) + my_log(
+                            hmm.observation_prob(st, PairwiseAlignmentHmmObservation(s1, s2)))
+                        frm_idx = hmm.state_index(frm)
+                        st_idx: int = hmm.state_index(st)
+                        if f[i - di, j - dj, frm_idx] is None:
+                            continue
+                        if f[i, j, st_idx] is None or \
+                                f[i, j, st_idx] < f[i - di, j - dj, frm_idx] + sc:
+                            f[i, j, st_idx] = f[i - di, j - dj, frm_idx] + sc
+                            prev_state[i, j, st_idx] = copy.deepcopy(frm)
+
+        i, j, best_st, best_score = n, m, hmm.M, -np.inf
+        for st in hmm.states:
+            if f[i, j, hmm.state_index(st)] > best_score:
+                best_st, best_score = st, f[i, j, hmm.state_index(st)]
+        states = [best_st]
+        while prev_state[i, j, hmm.state_index(best_st)] is not None:
+            prev_st = prev_state[i, j, hmm.state_index(best_st)]
+            states.append(prev_st)
+            i -= d[best_st][0]
+            j -= d[best_st][1]
+            best_st = prev_st
+
+        states.reverse()
+        assert i <= 1 and j <= 1, "Internal error"
+
+        def _log_observation_score(state: PairwiseAlignmentHmmState, symb1: Symbol, symb2: Symbol):
+            name = 'P' if state == hmm.M else 'Q_a' if state == hmm.A else 'Q_b'
+            return 'log({}({}, {})) = log({}) = {}'.format(
+                name, symb1, symb2, hmm.observation_prob(state, PairwiseAlignmentHmmObservation(symb1, symb2)),
+                my_log(hmm.observation_prob(state, PairwiseAlignmentHmmObservation(symb1, symb2))))
+
+        def _log_start_score(state: PairwiseAlignmentHmmState):
+            return 'log(Mu({})) = log({}) = {}'.format(state, hmm.start_prob(state),
+                                                       my_log(hmm.start_prob(state)))
+
+        def _log_transition_score(prev: PairwiseAlignmentHmmState, nxt: PairwiseAlignmentHmmState):
+            return 'log(Tau({} -> {})) = log({}) = {}'.format(prev, nxt, hmm.transition_prob(prev, nxt),
+                                                              my_log(hmm.transition_prob(prev, nxt)))
+
+        i, j = 0, 0
+        aligned1: List[AlignedAminoacid] = []
+        aligned2: List[AlignedScoredAminoacid] = []
+        logs = []
+        for prev_state, st in zip([None] + states[:-1], states):
+            s1 = Gap() if d[st][0] == 0 else seq1.symbols[i]
+            s2 = Gap() if d[st][1] == 0 else seq2.symbols[j]
+            if prev_state is None:
+                logs.append(_log_start_score(st))
+            else:
+                logs.append(_log_transition_score(prev_state, st))
+            logs.append(_log_observation_score(st, s1, s2))
+            aligned1.append(s1)
+            aligned2.append(s2)
+            i += d[st][0]
+            j += d[st][1]
+
+        aligned_seq1: AlignedAminoacidSequence = AlignedAminoacidSequence(seq1.sequence_id, aligned1)
+        aligned_seq2: AlignedScoredAminoacidSequence = AlignedScoredAminoacidSequence(seq2.sequence_id, aligned2)
+
+        # alpha = calculate_log_alpha(seq1, seq2, hmm)
+        # score = log_add_exp([alpha[n, m, x] for x in range(k)])
+        # best_score -= score  # - P(Q)
+
+        # logs.append('Marginal probs:')
+        # logs.append(' '.join(map(str, log_marginal_prob_for_alignment(aligned_seq1, aligned_seq2, hmm))))
+        return ViterbiOutput(aligned_seq1, aligned_seq2,
+                             self._sa.recalculate_score(best_score, seq1, seq2, hmm.parameters),
+                             logs='\n'.join(logs))
diff --git a/src/markov_probability_model/pairwise_alignment/alignment_generator.py b/src/markov_probability_model/pairwise_alignment/alignment_generator.py
new file mode 100644
index 0000000..112c626
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/alignment_generator.py
@@ -0,0 +1,43 @@
+import abc
+
+from typing import List, TypeVar, Generic, Optional
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseAlignmentOutputWithLogs, \
+    PairwiseSequenceAligner
+from src.markov_probability_model.data_loader.data_loader import TwoSequenceListsData
+from src.markov_probability_model.base.sequence import AminoacidSequence
+from src.markov_probability_model.pairwise_alignment.logger import AlignmentsLogger
+from multiprocessing import Pool
+from tqdm import tqdm
+
+
+class AlignmentGenerator(abc.ABC):
+    @abc.abstractmethod
+    def generate_alignments(self) -> List[PairwiseAlignmentOutputWithLogs]:
+        pass
+
+
+O = TypeVar('O')
+
+
+class AllPairsAlignmentGenerator(AlignmentGenerator, Generic[O]):
+    def __init__(self, data: TwoSequenceListsData, sequence_aligner: PairwiseSequenceAligner[O],
+                 logger: Optional[AlignmentsLogger[O]] = None, pool_sz: int = 1):
+        self._data = data
+        self._sequence_aligner = sequence_aligner
+        self._logger = logger
+        self._pool_sz = pool_sz
+
+    def generate_alignments(self) -> List[O]:
+        with Pool(self._pool_sz) as p:
+            alignment_lists: List[List[O]] = list(
+                tqdm(p.imap(self._generate_alignments_for_seq1, self._data.sequences1),
+                     total=len(self._data.sequences1)))
+        return [alignment for alignments in alignment_lists for alignment in alignments]
+
+    def _generate_alignments_for_seq1(self, seq1: AminoacidSequence) -> List[O]:
+        alignments: List[O] = []
+        for seq2 in self._data.sequences2:
+            alignments.append(self._sequence_aligner.align(seq1, seq2))
+            if self._logger is not None:
+                self._logger.log_alignment(alignments[-1])
+        return alignments
diff --git a/src/markov_probability_model/pairwise_alignment/fdr.py b/src/markov_probability_model/pairwise_alignment/fdr.py
new file mode 100644
index 0000000..cedda5f
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/fdr.py
@@ -0,0 +1,95 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import os
+
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import ScoredPairwiseAlignmentOutput
+from typing import List, NewType, Optional, Dict
+from collections import defaultdict
+
+
+class FdrParameters:
+    def __init__(self, topk: int, relative_to: str,
+                 pairs_df_logpath: Optional[str], best_pairs_df_logpath: Optional[str]):
+        self.topk = topk
+        self.relative_to = relative_to
+        self.pairs_df_logpath = pairs_df_logpath
+        self.best_pairs_df_logpath = best_pairs_df_logpath
+
+    def __str__(self):
+        return f'{self.relative_to}_top{self.topk}'
+
+
+FdrData = NewType('FdrData', List[float])
+
+
+class FdrGenerator:
+    def __init__(self, alignments: List[ScoredPairwiseAlignmentOutput], fdr_parameters: List[FdrParameters]):
+        self._fdr_parameters: List[FdrParameters] = fdr_parameters
+        self._alignments: List[ScoredPairwiseAlignmentOutput] = sorted(alignments, key=lambda x: -x.score())
+
+    def generate_fdr(self) -> List[FdrData]:
+        return [self._generate_single_fdr(p) for p in self._fdr_parameters]
+
+    def _generate_single_fdr(self, p: FdrParameters) -> FdrData:
+        groups: Dict[List[ScoredPairwiseAlignmentOutput]] = defaultdict(list)
+        for alignment in self._alignments:
+            base_struct_id = alignment.aligned_sequence1.base_sequence_id if p.relative_to == 'mol' else \
+                alignment.aligned_sequence2.base_sequence_id
+            groups[base_struct_id].append(alignment)
+        groups_list: List[List[ScoredPairwiseAlignmentOutput]] = list(groups.values())
+        groups_list.sort(key=lambda x: -x[0].score())
+
+        if p.pairs_df_logpath is not None:
+            pd.DataFrame({
+                'Seq1': [a.aligned_sequence1.sequence_id for g in groups_list for a in g],
+                'Seq2': [a.aligned_sequence2.sequence_id for g in groups_list for a in g],
+                'Score': [a.score() for g in groups_list for a in g],
+                'Aligned1': [' '.join(map(str, a.aligned_sequence1.symbols)) for g in groups_list for a in g],
+                'Aligned2': [' '.join(map(str, a.aligned_sequence2.symbols)) for g in groups_list for a in g],
+            }).to_csv(p.pairs_df_logpath)
+
+        correct: int = 0
+        incorrect: int = 0
+        fdr: List[float] = []
+        result_alignments: List[ScoredPairwiseAlignmentOutput] = []
+        for alignments in groups_list:
+            cut_alignments: List[ScoredPairwiseAlignmentOutput] = alignments[:min(len(alignments), p.topk)]
+            while len(alignments) > len(cut_alignments) and \
+                    cut_alignments[-1].score() == alignments[len(cut_alignments)].score():
+                cut_alignments.append(alignments[len(cut_alignments)])
+            res: ScoredPairwiseAlignmentOutput = cut_alignments[0]
+            for a in cut_alignments:
+                if a.aligned_sequence1.base_sequence_id == a.aligned_sequence2.base_sequence_id:
+                    res = a
+                    break
+            result_alignments.append(res)
+            if res.aligned_sequence1.base_sequence_id == res.aligned_sequence2.base_sequence_id:
+                correct += 1
+            else:
+                incorrect += 1
+            fdr.append(incorrect / (correct + incorrect))
+
+        if p.best_pairs_df_logpath is not None:
+            pd.DataFrame({
+                'Seq1': [a.aligned_sequence1.sequence_id for a in result_alignments],
+                'Seq2': [a.aligned_sequence2.sequence_id for a in result_alignments],
+                'Score': [a.score() for a in result_alignments],
+                'Aligned1': [' '.join(map(str, a.aligned_sequence1.symbols)) for a in result_alignments],
+                'Aligned2': [' '.join(map(str, a.aligned_sequence2.symbols)) for a in result_alignments],
+            }).to_csv(p.best_pairs_df_logpath)
+
+        return FdrData(fdr)
+
+
+def plot_fdrs(fdr_parameters: List[FdrParameters], fdrs: List[Dict[str, FdrData]], save_dir: str):
+    if not os.path.exists(save_dir):
+        os.makedirs(save_dir)
+    for i, p in enumerate(fdr_parameters):
+        plt.title(f'FDR_{str(p)}')
+        legends: List[str] = []
+        for name, others_fdr in fdrs[i].items():
+            plt.plot(range(len(others_fdr)), others_fdr)
+            legends.append(name)
+        plt.legend(legends)
+        plt.savefig(os.path.join(save_dir, f'FDR_{str(p)}.png'))
+        plt.clf()
diff --git a/src/markov_probability_model/pairwise_alignment/logger.py b/src/markov_probability_model/pairwise_alignment/logger.py
new file mode 100644
index 0000000..27b644c
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/logger.py
@@ -0,0 +1,59 @@
+import abc
+import os
+
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.base.sequence import SequenceId
+from src.markov_probability_model.base.alphabet import AlignedScoredAminoacid, Gap
+from typing import TypeVar, Generic
+
+O = TypeVar('O')
+
+
+class AlignmentsLogger(Generic[O]):
+    @abc.abstractmethod
+    def log_alignment(self, alignment: O):
+        pass
+
+
+class HtmlAlignmentsLogger(AlignmentsLogger[PairwiseAlignmentOutputWithLogs]):
+    def __init__(self, log_dir: str):
+        self._log_dir = log_dir
+        if not os.path.exists(log_dir):
+            os.makedirs(log_dir)
+
+    @staticmethod
+    def _get_colour_by_score(score: float):
+        if score > 90.0:
+            return 'green'
+        elif score > 60.0:
+            return 'yellow'
+        else:
+            return 'red'
+
+    def _get_string_for_output(self, s: AlignedScoredAminoacid) -> str:
+        if s == Gap():
+            return '<td>' + str(s) + '</td>'
+        return '<td>' + str(s).split('(')[0] + \
+               '<font style="background-color:%s;">%s<font></td>' % (
+                   self._get_colour_by_score(s.score), s.score)
+
+    def log_alignment(self, alignment: PairwiseAlignmentOutputWithLogs):
+        id1: SequenceId = alignment.aligned_sequence1.sequence_id
+        id2: SequenceId = alignment.aligned_sequence2.sequence_id
+        logpath = os.path.join(self._log_dir, f'{id1}_{id2}.html')
+
+        with open(logpath, 'w') as f:
+            f.write('<html><body>')
+            f.write(f'</br><h1>{id1} & {id2}</h1>')
+            f.write('<table>')
+            f.write('<tr>')
+            for ind in range(len(alignment)):
+                f.write(f'<td><font style="-color:black;">{str(alignment.aligned_sequence1.symbols[ind])}<font></td>')
+            f.write('<tr/>')
+            for ind in range(len(alignment)):
+                f.write(self._get_string_for_output(alignment.aligned_sequence2.symbols[ind]))
+            f.write('</tr>')
+            f.write('</table>')
+            f.write('</br>')
+            f.write('<p> Logs: </p>' + ''.join('<p>&emsp;' + p + '</p>' for p in alignment.logs.split('\n')))
+            f.write('</body></html>')
diff --git a/src/markov_probability_model/pairwise_alignment/score_augmentations.py b/src/markov_probability_model/pairwise_alignment/score_augmentations.py
new file mode 100644
index 0000000..62f7f6f
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/score_augmentations.py
@@ -0,0 +1,25 @@
+import abc
+
+from src.markov_probability_model.base.utils import my_log
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHMMParameters
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence
+
+
+class ScoreAugmentator(abc.ABC):
+    @abc.abstractmethod
+    def recalculate_score(self, score: float, seq1: AminoacidSequence, seq2: ScoredAminoacidSequence,
+                          params: PairwiseAlignmentHMMParameters) -> float:
+        pass
+
+
+class IdentityScoreAugmentator(ScoreAugmentator):
+    def recalculate_score(self, score: float, seq1: AminoacidSequence, seq2: ScoredAminoacidSequence,
+                          params: PairwiseAlignmentHMMParameters) -> float:
+        return score
+
+
+class NullHypothesisScoreAugmentator(ScoreAugmentator):
+    def recalculate_score(self, score: float, seq1: AminoacidSequence, seq2: ScoredAminoacidSequence,
+                          params: PairwiseAlignmentHMMParameters) -> float:
+        score -= sum(my_log(params.q_a[a]) for a in seq1.symbols) + sum(my_log(params.q_b[b]) for b in seq2.symbols)
+        return score
diff --git a/src/markov_probability_model/pairwise_alignment/sequence_aligner.py b/src/markov_probability_model/pairwise_alignment/sequence_aligner.py
new file mode 100644
index 0000000..94b7fae
--- /dev/null
+++ b/src/markov_probability_model/pairwise_alignment/sequence_aligner.py
@@ -0,0 +1,38 @@
+import abc
+
+from src.markov_probability_model.base.sequence import AlignedAminoacidSequence, AlignedScoredAminoacidSequence, \
+    AminoacidSequence, ScoredAminoacidSequence
+from typing import TypeVar, Generic
+
+
+class PairwiseAlignmentOutput:
+    def __init__(self, aligned_sequence1: AlignedAminoacidSequence,
+                 aligned_sequence2: AlignedScoredAminoacidSequence):
+        self.aligned_sequence1 = aligned_sequence1
+        self.aligned_sequence2 = aligned_sequence2
+        assert len(self.aligned_sequence1) == len(self.aligned_sequence2)
+
+    def __len__(self):
+        return len(self.aligned_sequence1)
+
+
+class PairwiseAlignmentOutputWithLogs(PairwiseAlignmentOutput):
+    def __init__(self, aligned_sequence1: AlignedAminoacidSequence,
+                 aligned_sequence2: AlignedScoredAminoacidSequence, logs: str):
+        super().__init__(aligned_sequence1, aligned_sequence2)
+        self.logs = logs
+
+
+class ScoredPairwiseAlignmentOutput(abc.ABC, PairwiseAlignmentOutput):
+    @abc.abstractmethod
+    def score(self):
+        pass
+
+
+O = TypeVar('O')
+
+
+class PairwiseSequenceAligner(abc.ABC, Generic[O]):
+    @abc.abstractmethod
+    def align(self, seq1: AminoacidSequence, seq2: ScoredAminoacidSequence) -> O:
+        pass
diff --git a/src/markov_probability_model/parameters/baum_welch_parameters_estimator.py b/src/markov_probability_model/parameters/baum_welch_parameters_estimator.py
new file mode 100644
index 0000000..0ba42b6
--- /dev/null
+++ b/src/markov_probability_model/parameters/baum_welch_parameters_estimator.py
@@ -0,0 +1,251 @@
+import numpy as np
+import os
+
+from src.markov_probability_model.parameters.parameters_calculator import ParametersCalculator
+from src.markov_probability_model.data_loader.alignments_loader import PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.data_loader.data_loader import TwoSequenceListsData
+from src.markov_probability_model.base.alphabet import Gap, AminoacidAlphabet, ScoredAminoacidAlphabet
+from src.markov_probability_model.base.sequence import AminoacidSequence, ScoredAminoacidSequence
+from src.markov_probability_model.base.utils import my_log, my_exp, log_add_exp
+from src.markov_probability_model.parameters.utils import estimate_p_with_modifications, parse_nerpa_config, \
+    estimate_qa_qb, array_to_dict, same_modifications, generate_p_score, generate_p_mods
+from src.markov_probability_model.pairwise_alignment.algo.utils import calculate_log_alpha, calculate_log_beta
+from src.markov_probability_model.parameters.utils import get_alphabets_from_data, get_names_alphabet
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHmm, \
+    PairwiseAlignmentHmmObservation, PairwiseAlignmentHMMParameters
+from typing import List, Optional, Dict, Tuple
+from tqdm import tqdm
+from multiprocessing import Pool
+
+PSEUDOCOUNT = 1e-7
+
+
+def _calculate_a(seqs1: List[AminoacidSequence], seqs2: List[ScoredAminoacidSequence],
+                 gammas: List[np.ndarray], epss: List[np.ndarray], hmm: PairwiseAlignmentHmm):
+    a = np.full((len(hmm.states), len(hmm.states)), 0.0)
+    for i in range(len(hmm.states)):
+        for j in range(len(hmm.states)):
+            a[i, j] = my_exp(log_add_exp([eps[t, s, i, j] + gamma[t, s, i]
+                                          for seq1, seq2, eps, gamma in zip(seqs1, seqs2, epss, gammas)
+                                          for t in range(len(seq1) + 1) for s in range(len(seq2) + 1)]))
+        a[i, :] /= a[i, :].sum()
+    return a
+
+
+def _calculate_gamma(seq1: AminoacidSequence, seq2: ScoredAminoacidSequence, hmm: PairwiseAlignmentHmm,
+                     alpha: np.ndarray, beta: np.ndarray) -> np.ndarray:
+    n, m = len(seq1), len(seq2)
+    gamma = np.full((n + 1, m + 1, len(hmm.states)), -np.inf)
+    sum_ = log_add_exp([alpha[n, m, hmm.state_index(i)] for i in hmm.states])
+    for t in range(n + 1):
+        for s in range(m + 1):
+            for i in hmm.states:
+                gamma[t, s, hmm.state_index(i)] = \
+                    alpha[t, s, hmm.state_index(i)] + beta[t, s, hmm.state_index(i)] - sum_
+    return gamma
+
+
+def _calculate_eps(seq1: AminoacidSequence, seq2: ScoredAminoacidSequence, hmm: PairwiseAlignmentHmm,
+                   alpha: np.ndarray, beta: np.ndarray) -> np.ndarray:
+    d = {hmm.M: (1, 1), hmm.A: (1, 0), hmm.B: (0, 1)}
+    n, m = len(seq1), len(seq2)
+    eps = np.full((n + 1, m + 1, len(hmm.states), len(hmm.states)), -np.inf)
+    for t in range(n + 1):
+        for s in range(m + 1):
+            for x in hmm.states:
+                for y in hmm.states:
+                    di, dj = d[y]
+                    if t + di > n or s + dj > m:
+                        continue
+                    if beta[t, s, hmm.state_index(x)] == -np.inf:
+                        continue
+                    if alpha[t, s, hmm.state_index(x)] == -np.inf:
+                        continue
+                    symb1 = Gap() if di == 0 else seq1.symbols[t + di - 1]
+                    symb2 = Gap() if dj == 0 else seq2.symbols[s + dj - 1]
+                    eps[t, s, hmm.state_index(x), hmm.state_index(y)] = \
+                        my_log(hmm.observation_prob(y, PairwiseAlignmentHmmObservation(symb1, symb2))) + my_log(
+                            hmm.transition_prob(x, y)) + beta[t + di, s + dj, hmm.state_index(y)] - beta[
+                            t, s, hmm.state_index(x)]
+    return eps
+
+
+def _calculate_pi(gammas: List[np.ndarray], hmm: PairwiseAlignmentHmm):
+    d = {hmm.M: (1, 1), hmm.A: (1, 0), hmm.B: (0, 1)}
+    pi = np.full((len(hmm.states),), 0.0)
+    for v in hmm.states:
+        di, dj = d[v]
+        pi[hmm.state_index(v)] = my_exp(log_add_exp([
+            gamma[di, dj, hmm.state_index(v)] for gamma in gammas]))
+    for v in hmm.states:
+        pi[hmm.state_index(v)] /= len(gammas)
+    return pi
+
+
+def _estimate_f(alphabet: List[str],
+                seqs1: List[AminoacidSequence], seqs2: List[ScoredAminoacidSequence],
+                gammas: List[np.ndarray], hmm: PairwiseAlignmentHmm,
+                modification1, methylation1, modification2, methylation2) -> Dict[str, float]:
+    res: Dict[str, float] = {a: my_log(PSEUDOCOUNT) for a in alphabet}
+    div_term = my_log(len(alphabet) * PSEUDOCOUNT)
+    for seq1, seq2, gam in zip(seqs1, seqs2, gammas):
+        for t in range(1, len(seq1) + 1):
+            for s in range(1, len(seq2) + 1):
+                cur_gam = gam[t, s, hmm.state_index(hmm.M)]
+                if seq1.symbols[t - 1].name != seq2.symbols[s - 1]:
+                    continue
+                if same_modifications(seq1.symbols[t - 1], modification1, methylation1) and \
+                        same_modifications(seq2.symbols[s - 1], modification2, methylation2):
+                    res[seq1.symbols[t - 1].name] = log_add_exp([res[seq1.symbols[t - 1].name], cur_gam])
+                div_term = log_add_exp([div_term, cur_gam])
+    for a in alphabet:
+        res[a] = my_exp(res[a] - div_term)
+    return res
+
+
+def _estimate_g(alphabet: List[str],
+                seqs1: List[AminoacidSequence], seqs2: List[ScoredAminoacidSequence],
+                gammas: List[np.ndarray], hmm: PairwiseAlignmentHmm,
+                modification, methylation) -> Dict[str, float]:
+    res: Dict[str, float] = {a: my_log(PSEUDOCOUNT) for a in alphabet}
+    div_term = my_log(len(alphabet) * PSEUDOCOUNT)
+    for seq1, seq2, gam in zip(seqs1, seqs2, gammas):
+        for t in range(1, len(seq1) + 1):
+            for s in range(1, len(seq2) + 1):
+                cur_gam = gam[t, s, hmm.state_index(hmm.M)]
+                if seq1.symbols[t - 1].name == seq2.symbols[s - 1].name:
+                    continue
+                if same_modifications(seq1.symbols[t - 1], modification, methylation):
+                    res[seq1.symbols[t - 1].name] = log_add_exp([res[seq1.symbols[t - 1].name], cur_gam])
+                if same_modifications(seq2.symbols[s - 1], modification, methylation):
+                    res[seq2.symbols[s - 1].name] = log_add_exp([res[seq2.symbols[s - 1].name], cur_gam])
+                div_term = log_add_exp([div_term, cur_gam])
+    for a in alphabet:
+        res[a] = my_exp(res[a] - div_term)
+    return res
+
+
+class BaumWelchParametersEstimator(ParametersCalculator):
+    def __init__(self, alignments: List[PairwiseAlignmentOutputWithLogs],
+                 data: TwoSequenceListsData,
+                 nerpa_cfg_path: str,
+                 init_params: PairwiseAlignmentHMMParameters,
+                 n_iterations: int,
+                 recalculate_transition_probs: bool = True,
+                 log_dir: Optional[str] = None,
+                 pool_sz: int = 1):
+        self._alignments = alignments
+        self._data = data
+        self._nerpa_cfg = parse_nerpa_config(nerpa_cfg_path)
+        self._cur_params = init_params
+        self._hmm = PairwiseAlignmentHmm(self._cur_params)
+        self._n_iterations = n_iterations
+        self._cur_iter = 0
+        self._recalculate_transition_probs = recalculate_transition_probs
+        self._log_dir = log_dir
+        self._omega_a, self._omega_b = get_alphabets_from_data(self._data, self._alignments)
+        self._alphabet: List[str] = get_names_alphabet(self._omega_a, self._omega_b)
+        self._pool_sz = pool_sz
+        print('Will use Baum-Welch parameters estimator')
+
+    def calculate_parameters(self) -> PairwiseAlignmentHMMParameters:
+        for _ in range(self._n_iterations):
+            print(f'Iteration {self._cur_iter}')
+            new_params = self._calculate_parameters_on_iteration()
+            d = _calculate_distance(new_params, self._cur_params)
+            print(f' distance = {d}')
+            self._cur_params = new_params
+            self._hmm = PairwiseAlignmentHmm(self._cur_params)
+        return self._cur_params
+
+    def _calculate_alpha_beta_gamma_eps(self, alignment: PairwiseAlignmentOutputWithLogs) -> Tuple:
+        seq1 = AminoacidSequence(alignment.aligned_sequence1.sequence_id,
+                                 [i for i in alignment.aligned_sequence1.symbols if i != Gap()])
+        seq2 = ScoredAminoacidSequence(alignment.aligned_sequence2.sequence_id,
+                                       [i for i in alignment.aligned_sequence2.symbols if i != Gap()])
+        alpha = calculate_log_alpha(seq1, seq2, self._hmm)
+        beta = calculate_log_beta(seq1, seq2, self._hmm)
+        gamma = _calculate_gamma(seq1, seq2, self._hmm, alpha, beta)
+        eps = _calculate_eps(seq1, seq2, self._hmm, alpha, beta)
+        return seq1, seq2, alpha, beta, gamma, eps
+
+    def _calculate_f(self, case: Tuple[str, bool, str, bool, List, List, List[np.ndarray]]):
+        modification1, methylation1, modification2, methylation2, seqs1, seqs2, gammas = case
+        return _estimate_f(self._alphabet, seqs1, seqs2, gammas, self._hmm,
+                           modification1, methylation1, modification2, methylation2)
+
+    def _calculate_g(self, case: Tuple[str, bool, List, List, List[np.ndarray]]):
+        modification, methylation, seqs1, seqs2, gammas = case
+        return _estimate_g(self._alphabet, seqs1, seqs2, gammas, self._hmm, modification, methylation)
+
+    def _calculate_parameters_on_iteration(self) -> PairwiseAlignmentHMMParameters:
+        self._cur_iter += 1
+
+        alignments: List[PairwiseAlignmentOutputWithLogs] = [a for a in self._alignments if
+                                                             _check_observation(a, self._omega_a, self._omega_b)]
+        with Pool(self._pool_sz) as p:
+            prob_data: List[Tuple] = list(
+                tqdm(p.imap(self._calculate_alpha_beta_gamma_eps, alignments),
+                     total=len(alignments), desc='Calculating marginal probs'))
+
+        seqs1, seqs2, alphas, betas, gammas, epss = map(list, zip(*prob_data))
+        if self._recalculate_transition_probs:
+            mu, tau = np.array(_calculate_pi(gammas, self._hmm)), np.array(
+                _calculate_a(seqs1, seqs2, gammas, epss, self._hmm))
+        else:
+            mu, tau = self._cur_params.mu, self._cur_params.tau
+
+        # 1. Estimate g(a, mod1, meth1, mod2, meth2) = P(a, mod1, meth1, mod2, meth2 | mismatch)
+        # 2. Estimate f(a, mod1, meth1, mod2, meth2) = P(a, mod1, meth1, mod2, meth2 | match)
+        f = {}
+        f_cases = [(modification1, methylation1, modification2, methylation2, seqs1, seqs2, gammas)
+                   for modification1 in ['@D', '@L']
+                   for methylation1 in [False, True]
+                   for modification2 in ['@D', '@L']
+                   for methylation2 in [False, True]]
+        with Pool(self._pool_sz) as p:
+            f_data: List[Tuple] = list(
+                tqdm(p.imap(self._calculate_f, f_cases),
+                     total=len(f_cases), desc='Estimating f'))
+        for i, (modification1, methylation1, modification2, methylation2, _, _, _) in enumerate(f_cases):
+            f[(modification1, methylation1, modification2, methylation2)] = f_data[i]
+
+        g = {}
+        g_cases = [(modification, methylation, seqs1, seqs2, gammas)
+                   for modification in ['@D', '@L']
+                   for methylation in [False, True]]
+        with Pool(self._pool_sz) as p:
+            g_data: List[Tuple] = list(
+                tqdm(p.imap(self._calculate_g, g_cases),
+                     total=len(g_cases), desc='Estimating g'))
+        for i, (modification, methylation, _, _, _) in enumerate(g_cases):
+            g[(modification, methylation)] = g_data[i]
+
+        p_score = generate_p_score(self._nerpa_cfg, self._data)
+        p_mods = generate_p_mods(self._data)
+        p = estimate_p_with_modifications(self._omega_a, self._omega_b, self._nerpa_cfg, f, g, p_score, p_mods)
+        q_a, q_b = estimate_qa_qb(p)
+        p, q_a, q_b = array_to_dict(self._omega_a, self._omega_b, p, q_a, q_b)
+        res = PairwiseAlignmentHMMParameters(self._omega_a, self._omega_b, mu=mu, tau=tau, p=p, q_a=q_a, q_b=q_b)
+        if self._log_dir is not None:
+            res.log_to(os.path.join(self._log_dir, f'baum_welch_parameters_iter{self._cur_iter}.txt'))
+        return res
+
+
+def _calculate_distance(p1: PairwiseAlignmentHMMParameters, p2: PairwiseAlignmentHMMParameters) -> float:
+    p = np.array([[p1.p[a][b] - p2.p[a][b] for b in p1.omega_b] for a in p1.omega_a])
+    q_a = np.array([p1.q_a[a] - p2.q_a[a] for a in p1.omega_a])
+    q_b = np.array([p1.q_b[b] - p2.q_b[b] for b in p1.omega_b])
+    return np.linalg.norm(p1.mu - p2.mu) + np.linalg.norm(p1.tau - p2.tau) + np.linalg.norm(p) + np.linalg.norm(
+        q_a) + np.linalg.norm(q_b)
+
+
+def _check_observation(alignment: PairwiseAlignmentOutputWithLogs, omega_a: AminoacidAlphabet,
+                       omega_b: ScoredAminoacidAlphabet) -> bool:
+    for s in alignment.aligned_sequence1.symbols:
+        if s != Gap() and s.name not in [a.name for a in omega_a]:
+            return False
+    for s in alignment.aligned_sequence2.symbols:
+        if s != Gap() and s.name not in [b.name for b in omega_b]:
+            return False
+    return True
diff --git a/src/markov_probability_model/parameters/ml_parameters_estimator.py b/src/markov_probability_model/parameters/ml_parameters_estimator.py
new file mode 100644
index 0000000..318739d
--- /dev/null
+++ b/src/markov_probability_model/parameters/ml_parameters_estimator.py
@@ -0,0 +1,145 @@
+import numpy as np
+import os
+
+from src.markov_probability_model.base.alphabet import Aminoacid, ScoredAminoacid, AlignedAminoacid, \
+    AlignedScoredAminoacid, Gap
+from src.markov_probability_model.parameters.utils import same_modifications, estimate_p_with_modifications
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseAlignmentOutputWithLogs
+from src.markov_probability_model.data_loader.data_loader import TwoSequenceListsData
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHMMParameters
+from src.markov_probability_model.parameters.utils import parse_nerpa_config, get_alphabets_from_data, estimate_qa_qb, \
+    array_to_dict, get_names_alphabet, generate_p_score, generate_p_mods
+from typing import List, Optional, Tuple, Dict
+from collections import defaultdict
+
+
+class MaxLikelihoodParametersEstimator:
+    def __init__(self, alignments: List[PairwiseAlignmentOutputWithLogs],
+                 data: TwoSequenceListsData, nerpa_cfg_path: str,
+                 estimate_transition_probs: bool = False,
+                 log_dir: Optional[str] = None):
+        self._alignments = alignments
+        self._data = data
+        self._nerpa_cfg = parse_nerpa_config(nerpa_cfg_path)
+        self._estimate_transition_probs = estimate_transition_probs
+        self._log_dir = log_dir
+
+    def calculate_parameters(self) -> PairwiseAlignmentHMMParameters:
+        if self._estimate_transition_probs:
+            tau, mu = estimate_tau_mu(self._alignments)
+        else:
+            tau, mu = get_tau_mu_from_nerpa_cfg(self._nerpa_cfg)
+        omega_a, omega_b = get_alphabets_from_data(self._data, self._alignments)
+        p = self._estimate_p(omega_a, omega_b)
+        q_a, q_b = estimate_qa_qb(p)
+        p, q_a, q_b = array_to_dict(omega_a, omega_b, p, q_a, q_b)
+        res = PairwiseAlignmentHMMParameters(omega_a, omega_b, mu, tau, p, q_a, q_b)
+        if self._log_dir is not None:
+            res.log_to(os.path.join(self._log_dir, 'max_likelihood_parameters.txt'))
+        return res
+
+    def _estimate_p(self, omega_a: List[Aminoacid], omega_b: List[ScoredAminoacid]) -> np.ndarray:
+        observations = [(alignment.aligned_sequence1.symbols[i],
+                         alignment.aligned_sequence2.symbols[i])
+                        for alignment in self._alignments
+                        for i in range(len(alignment.aligned_sequence1))]
+        # 1. Estimate g(a, mod, meth) = P(a, mod, meth | match)
+        # 2. Estimate f(a, mod1, meth1, mod2, meth2) = P(a, mod1, meth1, mod2, meth2 | mismatch)
+        f, g = {}, {}
+        for modification1 in ['@L', '@D']:
+            for methylation1 in [True, False]:
+                g[(modification1, methylation1)] = \
+                    estimate_g(omega_a, omega_b, observations, modification1, methylation1)
+                for modification2 in ['@L', '@D']:
+                    for methylation2 in [True, False]:
+                        f[(modification1, methylation1, modification2, methylation2)] = \
+                            estimate_f(omega_a, omega_b, observations,
+                                       modification1, methylation1, modification2, methylation2)
+        # 3. Assign p
+        p_score = generate_p_score(self._nerpa_cfg, self._data)
+        p_mods = generate_p_mods(self._data)
+        p = estimate_p_with_modifications(omega_a, omega_b, self._nerpa_cfg, f, g, p_score, p_mods)
+        return p
+
+
+def estimate_f(omega_a: List[Aminoacid], omega_b: List[ScoredAminoacid],
+               observations: List[Tuple[AlignedAminoacid, AlignedScoredAminoacid]],
+               modification1, methylation1, modification2, methylation2) -> Dict[str, float]:
+    alphabet: List[str] = get_names_alphabet(omega_a, omega_b)
+    met = {a: 1 for a in alphabet}
+    div_term = len(alphabet)
+    for s1, s2 in observations:
+        if s1 == Gap() or s2 == Gap():
+            continue
+        if s1.name not in alphabet or s2.name not in alphabet:
+            continue
+        if s1.name != s2.name:
+            continue
+        if same_modifications(s1, modification1, methylation1) and same_modifications(s2, modification2, methylation2):
+            met[s1.name] += 1
+        div_term += 1
+    f: Dict[str, float] = defaultdict(float)
+    for a, met_a in met.items():
+        f[a] = met_a / div_term
+    return f
+
+
+def estimate_g(omega_a: List[Aminoacid], omega_b: List[ScoredAminoacid],
+               observations: List[Tuple[AlignedAminoacid, AlignedScoredAminoacid]],
+               modification, methylation) -> Dict[str, float]:
+    alphabet: List[str] = get_names_alphabet(omega_a, omega_b)
+    met = {a: 1 for a in alphabet}
+    div_term = len(alphabet)
+    for s1, s2 in observations:
+        if s1 == Gap() or s2 == Gap():
+            continue
+        if s1.name not in alphabet or s2.name not in alphabet:
+            continue
+        if s1.name == s2.name:
+            continue
+        if same_modifications(s1, modification, methylation):
+            met[s1.name] += 1
+        if same_modifications(s2, modification, methylation):
+            met[s2.name] += 1
+        div_term += 2
+    g: Dict[str, float] = defaultdict(float)
+    for a, met_a in met.items():
+        g[a] = met_a / div_term
+    return g
+
+
+def _get_state_from_observation(symb1: AlignedAminoacid, symb2: AlignedScoredAminoacid):
+    if symb1 != Gap() and symb2 != Gap():
+        return 0
+    elif symb2 == Gap():
+        return 1
+    else:
+        return 2
+
+
+def estimate_tau_mu(alignments: List[PairwiseAlignmentOutputWithLogs]) -> Tuple[np.ndarray, np.ndarray]:
+    tau = np.ones((3, 3))
+    mu = np.ones((3,))
+
+    for alignment in alignments:
+        states: List[int] = []
+        for pos in range(len(alignment.aligned_sequence1)):
+            symb1: AlignedAminoacid = alignment.aligned_sequence1.symbols[pos]
+            symb2: AlignedScoredAminoacid = alignment.aligned_sequence2.symbols[pos]
+            states.append(_get_state_from_observation(symb1, symb2))
+        mu[states[0]] += 1
+        for i in range(1, len(states)):
+            tau[states[i - 1], states[i]] += 1
+
+    tau = tau / tau.sum(axis=1)
+    mu = mu / mu.sum()
+    return tau, mu
+
+
+def get_tau_mu_from_nerpa_cfg(nerpa_cfg: Dict) -> Tuple[np.ndarray, np.ndarray]:
+    tau = np.ones((3, 3))
+    tau[0, 1] = tau[1, 1] = tau[2, 1] = np.exp(nerpa_cfg['insertion'])
+    tau[0, 2] = tau[1, 2] = tau[2, 2] = np.exp(nerpa_cfg['deletion'])
+    tau = tau / tau.sum(axis=1)
+    mu = tau.mean(axis=0)
+    return tau, mu
diff --git a/src/markov_probability_model/parameters/parameters_calculator.py b/src/markov_probability_model/parameters/parameters_calculator.py
new file mode 100644
index 0000000..a079a8e
--- /dev/null
+++ b/src/markov_probability_model/parameters/parameters_calculator.py
@@ -0,0 +1,9 @@
+import abc
+
+from src.markov_probability_model.hmm.pairwise_alignment_hmm import PairwiseAlignmentHMMParameters
+
+
+class ParametersCalculator(abc.ABC):
+    @abc.abstractmethod
+    def calculate_parameters(self) -> PairwiseAlignmentHMMParameters:
+        pass
diff --git a/src/markov_probability_model/parameters/utils.py b/src/markov_probability_model/parameters/utils.py
new file mode 100644
index 0000000..9eca1da
--- /dev/null
+++ b/src/markov_probability_model/parameters/utils.py
@@ -0,0 +1,145 @@
+import numpy as np
+
+from src.markov_probability_model.base.alphabet import Aminoacid, ScoredAminoacid, Gap, AminoacidAlphabet, \
+    ScoredAminoacidAlphabet, Symbol
+from src.markov_probability_model.data_loader.data_loader import TwoSequenceListsData
+from src.markov_probability_model.pairwise_alignment.sequence_aligner import PairwiseAlignmentOutput
+from typing import Tuple, List, Dict
+from collections import defaultdict
+
+
+def get_alphabets_from_data(data: TwoSequenceListsData, alignments: List[PairwiseAlignmentOutput]) -> Tuple[
+    AminoacidAlphabet, ScoredAminoacidAlphabet]:
+    omega_a: List[Aminoacid] = [symb for sequence in data.sequences1 for symb in sequence.symbols if symb != Gap()] + \
+                               [s for a in alignments for s in a.aligned_sequence1.symbols if s != Gap()]
+    omega_b: List[ScoredAminoacid] = [symb for sequence in data.sequences2
+                                      for symb in sequence.symbols if symb != Gap()] + \
+                                     [s for a in alignments for s in a.aligned_sequence2.symbols if s != Gap()]
+    return AminoacidAlphabet(list(set(omega_a))), ScoredAminoacidAlphabet(list(set(omega_b)))
+
+
+def get_alphabets_from_alignments(data: List[PairwiseAlignmentOutput]) \
+        -> Tuple[AminoacidAlphabet, ScoredAminoacidAlphabet]:
+    omega_a: List[Aminoacid] = [symb for alignment in data for symb in alignment.aligned_sequence1.symbols
+                                if symb != Gap()]
+    omega_b: List[ScoredAminoacid] = [symb for alignment in data
+                                      for symb in alignment.aligned_sequence2.symbols if symb != Gap()]
+    return AminoacidAlphabet(list(set(omega_a))), ScoredAminoacidAlphabet(list(set(omega_b)))
+
+
+def parse_nerpa_config(cfg_path: str) -> Dict:
+    with open(cfg_path, 'r') as f:
+        lines = f.readlines()
+    cfg = {'insertion': float(lines[0].rstrip().split(' ')[1]), 'deletion': float(lines[1].rstrip().split(' ')[1]),
+           'Scores': [float(l) for l in lines[2].rstrip().split(' ')[1:] if len(l) != 0],
+           'ProbGenCorrect': [float(l) for l in lines[3].rstrip().split(' ')[1:] if len(l) != 0],
+           'ProbGenIncorrect': [float(l) for l in lines[4].rstrip().split(' ')[1:] if len(l) != 0]}
+    return cfg
+
+
+def _estimate_p_match(a: Aminoacid, b: ScoredAminoacid, nerpa_cfg: Dict, f: Dict,
+                      p_score: Dict, mods_prob: Dict) -> float:
+    if a.modification is None:
+        a_mods_prob = mods_prob.copy()
+    else:
+        a_mods_prob = defaultdict(int)
+        a_mods_prob[a.modification] = 1.0
+    if b.modification is None:
+        b_mods_prob = mods_prob.copy()
+    else:
+        b_mods_prob = defaultdict(int)
+        b_mods_prob[b.modification] = 1.0
+    f_ = sum(f[(mod_a, a.methylation, mod_b, b.methylation)][a.name] * a_mods_prob[mod_a] * b_mods_prob[mod_b]
+             for mod_a in ['@L', '@D'] for mod_b in ['@L', '@D'])
+    return f_ * get_prob_gen(nerpa_cfg, b.score, p_score, correct=True)
+
+
+def _estimate_p_miss(a: Aminoacid, b: ScoredAminoacid, nerpa_cfg: Dict, g: Dict,
+                     p_score: Dict, mods_prob: Dict) -> float:
+    if a.modification is not None:
+        g_a = g[(a.modification, a.methylation)][a.name]
+    else:
+        g_a = sum(g[(mod, a.methylation)][a.name] * mods_prob[mod] for mod in ['@L', '@D'])
+    if b.modification is not None:
+        g_b = g[(b.modification, b.methylation)][b.name]
+    else:
+        g_b = sum(g[(mod, b.methylation)][b.name] * mods_prob[mod] for mod in ['@L', '@D'])
+    return g_a * g_b * get_prob_gen(nerpa_cfg, b.score, p_score, correct=False)
+
+
+def estimate_p_with_modifications(omega_a: List[Aminoacid], omega_b: List[ScoredAminoacid],
+                                  nerpa_cfg: Dict, f: Dict, g: Dict, p_score: Dict, mods_prob: Dict):
+    # Estimate p(a, b).
+    # Model:
+    #  p(@N-a, @M-a(score)) = f(a, N, M) * prob_gen_correct(score) * P(score)
+    #  p(@N-a, @M-b(score)) = g(a, N) * g(b, M) * prob_gen_incorrect(score) * P(score)
+    p = np.zeros((len(omega_a), len(omega_b)))
+    for i, a in enumerate(omega_a):
+        for j, b in enumerate(omega_b):
+            if a.name == b.name:
+                p[i, j] = _estimate_p_match(a, b, nerpa_cfg, f, p_score, mods_prob)
+            else:
+                p[i, j] = _estimate_p_miss(a, b, nerpa_cfg, g, p_score, mods_prob)
+    p /= p.sum()
+    return p
+
+
+def estimate_qa_qb(p: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
+    return p.sum(axis=1), p.sum(axis=0)
+
+
+def array_to_dict(omega_a: AminoacidAlphabet, omega_b: ScoredAminoacidAlphabet, p: np.ndarray, q_a: np.ndarray,
+                  q_b: np.ndarray) -> Tuple[Dict, Dict, Dict]:
+    p = {a: {b: p[i, j] for j, b in enumerate(omega_b)} for i, a in enumerate(omega_a)}
+    q_a = {a: q_a[i] for i, a in enumerate(omega_a)}
+    q_b = {b: q_b[i] for i, b in enumerate(omega_b)}
+    return p, q_a, q_b
+
+
+def _truncate_score_to_nerpa_cfg(config: Dict, score: float):
+    for i in range(len(config['Scores'])):
+        if config['Scores'][i] <= score:
+            return config['Scores'][i]
+
+
+def get_prob_gen(config: Dict, score: float, p_score: Dict, correct: bool):
+    score = _truncate_score_to_nerpa_cfg(config, score)
+    for i in range(len(config['Scores'])):
+        if config['Scores'][i] == score:
+            return np.exp(config['ProbGenCorrect' if correct else 'ProbGenIncorrect'][i]) * \
+                   p_score[_truncate_score_to_nerpa_cfg(config, score)]
+
+
+def same_modifications(x: Symbol, mod: str, methylation: bool) -> bool:
+    return x.modification == mod and x.methylation == methylation
+
+
+def get_names_alphabet(omega_a: AminoacidAlphabet, omega_b: ScoredAminoacidAlphabet) -> List[str]:
+    return list(set([a.name for a in omega_a] + [b.name for b in omega_b]))
+
+
+def generate_p_score(config, data: TwoSequenceListsData) -> Dict[int, int]:
+    p_score = defaultdict(float)
+    div_term = 0
+    for seq in data.sequences2:
+        for symb in seq.symbols:
+            score = int(_truncate_score_to_nerpa_cfg(config, symb.score))
+            p_score[score] += 1
+            div_term += 1
+    return {score: p / div_term for score, p in p_score.items()}
+
+
+def generate_p_mods(data: TwoSequenceListsData) -> Dict[str, int]:
+    p_mods = defaultdict(float)
+    div_term = 0
+    for seq in data.sequences1:
+        for symb in seq.symbols:
+            if symb.modification is not None:
+                div_term += 1
+                p_mods[symb.modification] += 1
+    for seq in data.sequences2:
+        for symb in seq.symbols:
+            if symb.modification is not None:
+                div_term += 1
+                p_mods[symb.modification] += 1
+    return {mod: p / div_term for mod, p in p_mods.items()}