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benchmarking_platform

bigdata_ai_drugdiscovery

A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest.

cadd-workflows

chemo_info

crem

CReM: chemically reasonable mutations framework

cryptosite

Library for prediction of cryptic binding sites

cyclops

deeplearning-models

A collection of various deep learning architectures, models, and tips

delinker

drugex

An exploration strategy improves the diversity of de novo drug design using deep reinforcement learning

edes

emolfrag

eMolFrag is a molecular fragmentation tool based on BRICS algorithm written in Python.

eodc_code_examples

Source code for code snippets sumbitted to the Expert Opinion on Drug Discovery

esp_dnn

A Graph-Convolutional Deep Neural Network for predicting electrostatic potential surfaces

free-wilson

An implementation of the Free-Wilson SAR analysis method using the RDKit

gb-ga

Graph-based genetic algorithm

guacamol_baselines

Baselines models for GuacaMol benchmarks

molecule_generator

Code for "Multi-Objective De Novo Drug Design with Conditional Graph Generative Model" (https://arxiv.org/abs/1801.07299)

moleculekit

MoleculeKit: Your favorite molecule manipulation kit

mopac

MOPAC version 7 (public domain)

moses

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

myrepo

pdb-tools

A dependency-free cross-platform swiss army knife for PDB files.

pharmd

MD pharmacophores and virtual screening

pka

psearch

rdkit-cats2d

Modification of the code of Rajarshi Guha (which uses OECHem) to use RDKIT.

rdkit_ipynb_tools

RDKit Tools for the IPython Notebook

reinvent

Molecular De Novo design using Recurrent Neural Networks and Reinforcement Learning

release

Deep Reinforcement Learning for de-novo Drug Design