This repository icludes a benchmark of the OpenCADD superposition methods[1], PyMol align[2][3] as well as ChimeraX Matchmaker[4, 5].
The methods are compared by their performance of alignment of four kinase groups. The structures are queried from the Kinase-Ligand Interactions Fingerprints and Structures database (KLIFS). [6, 7, 8] The performance is measured and compared by the three quality measures SI [9, 10], MI [9, 10] and SAS [10, 11].
The jupyter notebooks [12] show the results of the benchmark. For analysing the results, the following Python libraries were mainly used:
- Pandas (V 1.3.5) [13, 14]
- Matplotlib (V 3.5.1) [15]
- Seaborn (V 0.11.2) [16]
- SciPy (V 1.7.3) [17]
- NumPy (V 1.21.5) [18]
- statsmodels (V 0.13.1) [19]
The Python version 3.8.12 was used for this project.
A more detailed analysis is performed for the alignments between TK structures and the alignments between TK and CAMK stuctures.
This benchmark is the topic of the bachelor thesis of Julian Pipart.
For the installation, Conda [20] and PyPI pip [21] are required.
-
Download the repository:
git clone https://github.com/volkamerlab/OpenCADDSuperpositionBenchmark.git -
Change the directory the OpenCADDSuperpositionBenchmark folder.
cd OpenCADDSuperpositionBenchmark -
Create the conda environment: This environment.yml is based on the environment.yml of OpenCADD and includes additions for this benchmark. It extends the OpenCADD environment file. So no additional environment for this benchmark should be required.
conda env create -f OpenCADDSuperpositionBenchmark.yml -
Follow steps below for installation of the methods.
IMPORTANT: The benchmark was performed with changes made in OpenCADD, which are in the jp-superposer-extension branch. So the guide will explain how to use this branch for recreation.
Make sure to change the directory, so you are not in the local OpenCADDSuperpositionBenchmark repository.
Therefore, the download of the git repository is required:
git clone https://github.com/volkamerlab/opencadd.git
Change the directory the OpenCADDSuperpositionBenchmark folder.
cd opencadd
Next, the branch is changed to "jp-superposer-extension":
git checkout jp-superposer-extension
MMLigner requires a rebuild, please follow steps shown below while in the "jp-superposer-extension" branch:
conda config --add channels conda-forge
conda activate base
conda install conda-build
conda build devtools/conda-recipes/mmligner/
conda activate OpenCADDBenchmark
conda install -c local mmligner pip
Afterwards the superposer module can be installed locally:
pip install .
To see if it was successful, one can check with the following command:
superposer -h
For the installation of the Open-Source PyMol, please follow the guide of the PyMolWiki:
For the installation of ChimeraX, please use their download website and follow their installation guide. (See here)
For ChimeraX Matchmaker and PyMol align separate scripts were developed to perform the alignments and parse the output, to bring it into a readable dataframe for the analysis. The alignments of the OpenCADD methods are performed in the jupyter notebooks. The paths in the scripts need to be changed appropriately for your system. Subfolders contain additional README files to explain, what data they contain.
[1] Available at: https://github.com/volkamerlab/opencadd
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Thank you to all the members of the Volkamer Lab for the great opportunity of conduction my bachelor thesis here.