Trending repositories for topic drug-discovery
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
Single-Cell (Perturbation) Model Library
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
DrugHIVE: Structure-based drug design with a deep hierarchical generative model
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Single-Cell (Perturbation) Model Library
DrugHIVE: Structure-based drug design with a deep hierarchical generative model
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
Single-Cell (Perturbation) Model Library
Python package for graph neural networks in chemistry and biology
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Searching for structural similarities across billions of molecules in milliseconds
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025]
Official implementation of DrugGEN: Target Specific De Novo Design of Drug Candidate Molecules with Graph Transformer-based Generative Adversarial Networks
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
Single-Cell (Perturbation) Model Library
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
Searching for structural similarities across billions of molecules in milliseconds
DrugHIVE: Structure-based drug design with a deep hierarchical generative model
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025]
Official implementation of DrugGEN: Target Specific De Novo Design of Drug Candidate Molecules with Graph Transformer-based Generative Adversarial Networks
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development
A powerful cheminformatics and molecule rendering toolbelt for JavaScript, powered by RDKit .
A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
A powerful and flexible machine learning platform for drug discovery
DrugHIVE: Structure-based drug design with a deep hierarchical generative model
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Searching for structural similarities across billions of molecules in milliseconds
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
NequIP is a code for building E(3)-equivariant interatomic potentials
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
The Ersilia Model Hub, a repository of AI/ML models for infectious and neglected disease research.
Universal cheminformatics toolkit, utilities and database search tools
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025]
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
DrugHIVE: Structure-based drug design with a deep hierarchical generative model
Searching for structural similarities across billions of molecules in milliseconds
Single-Cell (Perturbation) Model Library
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025]
The official repository for the book "Machine Learning for Drug Discovery" (Manning Publications)
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
NVIDIA BioNeMo blueprint for generative AI-based virtual screening
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
HydrAMP: a deep generative model for antimicrobial peptide discovery
The Ersilia Model Hub, a repository of AI/ML models for infectious and neglected disease research.
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
The official codebase of peptidy, a peptide processing tool for machine learning.
Implementation of DiffDock-Pocket: Diffusion for Pocket-Level Docking with Side Chain Flexibility
Official implementation of DrugGEN: Target Specific De Novo Design of Drug Candidate Molecules with Graph Transformer-based Generative Adversarial Networks
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025]
NVIDIA BioNeMo blueprint for generative AI-based virtual screening
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
Uncover meaningful structures of latent spaces learned by generative models with flows!
[TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
NequIP is a code for building E(3)-equivariant interatomic potentials
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
A powerful and flexible machine learning platform for drug discovery
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Mixed continous/categorical flow-matching model for de novo molecule generation.
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
Mixed continous/categorical flow-matching model for de novo molecule generation.
Codebase and CLI for PLAPT: A state-of-the-art protein-ligand binding affinity model for drug discovery
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025]
The official repository for the book "Machine Learning for Drug Discovery" (Manning Publications)
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
Searching for structural similarities across billions of molecules in milliseconds
Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
This is a curated list of research papers, resources and tools related to using Graph Neural Networks (GNNs) for drug discovery.
Multi-target de novo molecular generator conditioned on AlphaFold's latent protein embeddings.
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
Toolkit for open antiviral drug discovery by the ASAP Discovery Consortium
A tool for creating Quantitative Structure Property/Activity Relationship (QSPR/QSAR) models.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
rDock is a fast and versatile Open Source docking program that can be used to dock small molecules against proteins and nucleic acids. It is designed for High Throughput Virtual Screening (HTVS) campa...