Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
- drug-discovery
- quantum-chemistry
- deep-learning
- biology
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Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Message Passing Neural Networks for Molecule Property Prediction
Open Babel is a chemical toolbox designed to speak the many languages of chemical data.
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
WebGL accelerated JavaScript molecular graphics library
Python package for graph neural networks in chemistry and biology
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry
⚗ A package useful for chemistry written in Python
The Chemistry Development Kit
Molecular Processing Made Easy.
Benchmarks for generative chemistry
bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.
Parsers and algorithms for computational chemistry logfiles
Universal cheminformatics toolkit, utilities and database search tools
Descriptor computation(chemistry) and (optional) storage for machine learning
Graph-based molecule modeling toolkit for cheminformatics
Wrapper for RDKit's RunReactants to improve stereochemistry handling
Molecule Validation and Standardization
Chemical 2D structure editor application/applet based on the Chemistry Development Kit
The Massively Parallel Quantum Chemistry program, MPQC, computes properties of atoms and molecules from first principles using the time independent Schrödinger equation.
Multi-stage Riemannian flow matching for physically valid molecular docking, with GNINA scoring, PoseBusters filtering, CLI inference, and benchmarks.
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.