drug-discovery
There are 547 repositories under drug-discovery topic.
NVIDIA/DeepLearningExamples
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
deepchem/deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
chemprop/chemprop
Message Passing Neural Networks for Molecule Property Prediction
DeepGraphLearning/torchdrug
A powerful and flexible machine learning platform for drug discovery
a-r-j/graphein
Protein Graph Library
mims-harvard/TDC
Therapeutics Commons: Artificial Intelligence Foundation for Therapeutic Science
kexinhuang12345/DeepPurpose
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
molecularsets/moses
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
AstraZeneca/chemicalx
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
BioPandas/biopandas
Working with molecular structures in pandas DataFrames
awslabs/dgl-lifesci
Python package for graph neural networks in chemistry and biology
Mariewelt/OpenChem
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
gnina/gnina
A deep learning framework for molecular docking
mir-group/nequip
NequIP is a code for building E(3)-equivariant interatomic potentials
HannesStark/EquiBind
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
junxia97/awesome-pretrain-on-molecules
[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models
datamol-io/datamol
Molecular Processing Made Easy.
isayev/ReLeaSE
Deep Reinforcement Learning for de-novo Drug Design
chemosim-lab/ProLIF
Interaction Fingerprints for protein-ligand complexes and more
mir-group/allegro
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
JuDFTteam/best-of-atomistic-machine-learning
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Acellera/htmd
HTMD: Programming Environment for Molecular Discovery
AngelRuizMoreno/Jupyter_Dock
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.
MolecularAI/REINVENT4
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
rdk/p2rank
P2Rank: Protein-ligand binding site prediction tool based on machine learning. Stand-alone command line program / Java library for predicting ligand binding pockets from protein structure.
octavian-ganea/equidock_public
EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
mattragoza/LiGAN
Deep generative models of 3D grids for structure-based drug discovery
Acellera/moleculekit
MoleculeKit: Your favorite molecule manipulation kit
ersilia-os/ersilia
The Ersilia Model Hub, a repository of AI/ML models for infectious and neglected disease research.
chao1224/MoleculeSTM
Multi-modal Molecule Structure-text Model for Text-based Editing and Retrieval, Nat Mach Intell 2023 (https://www.nature.com/articles/s42256-023-00759-6)
pcko1/Deep-Drug-Coder
A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.
benb111/awesome-small-molecule-ml
A curated list of resources for machine learning for small-molecule drug discovery
atomicarchitects/equiformer
[ICLR'23 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
AstraZeneca/awesome-drug-discovery-knowledge-graphs
A collection of research papers, datasets and software related to knowledge graphs for drug discovery. Accompanies the paper "A review of biomedical datasets relating to drug discovery: a knowledge graph perspective" (Briefings in Bioinformatics, 2022)
choderalab/yank
An open, extensible Python framework for GPU-accelerated alchemical free energy calculations.
MinkaiXu/GeoLDM
Geometric Latent Diffusion Models for 3D Molecule Generation