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Deep Learning in Virtual Screening: Recent Applications and Developments

Review

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deep_learning_in_virtual_screening

Content

This repository provides

  • the code to produce all subfigures (generated programmatically), as well as
  • the final figures in the review.

The folder image_generation holds the following information:

  • ligand_encoding: scripts to produce ligand encoding examples
  • complex_encoding: scripts to produce complex encoding examples
  • review_images: composed review figures

Check out more of our work at Volkamer Lab.

Conda installation

Create a conda environment:

$ conda env create -f devtools/env.yml

Activate the environment:

$ conda activate dl-review

Install widgets:

(dl-review)$ jupyter labextension install @jupyter-widgets/jupyterlab-manager nglview-js-widgets

Run jupyter lab:

(dl-review)$ jupyter lab

Citation

Kimber, Talia B.; Chen, Yonghui; Volkamer, Andrea. 2021. "Deep Learning in Virtual Screening: Recent Applications and Developments" Int. J. Mol. Sci. 22, no. 9: 4435. https://doi.org/10.3390/ijms22094435

@article{doi:10.3390/ijms22094435,
author = {Kimber, Talia B. and Chen, Yonghui and Volkamer, Andrea},
title = {Deep Learning in Virtual Screening: Recent Applications and Developments},
journal = {International Journal of Molecular Sciences},
volume = {22},
year = {2021},
number = {9},
article-number = {4435},
url = {https://www.mdpi.com/1422-0067/22/9/4435},
ISSN = {1422-0067},
doi = {10.3390/ijms22094435}
}

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Deep learning in virtual screening, a review

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