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
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
A powerful and flexible machine learning platform for drug discovery
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
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.
A powerful and flexible machine learning platform for 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
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
Mixed continous/categorical flow-matching model for de novo molecule generation.
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
A powerful and flexible machine learning platform for drug discovery
[TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.
Merging, linking and placing compounds by stitching bound compounds together like a reanimated corpse
[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
[TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
Mixed continous/categorical flow-matching model for de novo molecule generation.
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.
Merging, linking and placing compounds by stitching bound compounds together like a reanimated corpse
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
The Ersilia Model Hub, a repository of AI/ML models for infectious and neglected disease research.
NequIP is a code for building E(3)-equivariant interatomic potentials
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
Interaction Fingerprints for protein-ligand complexes and more
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.
Codebase and CLI for PLAPT: A state-of-the-art protein-ligand binding affinity model for drug discovery
NequIP is a code for building E(3)-equivariant interatomic potentials
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
A powerful and flexible machine learning platform for drug discovery
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Universal cheminformatics toolkit, utilities and database search tools
Mixed continous/categorical flow-matching model for de novo molecule generation.
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
Codebase and CLI for PLAPT: A state-of-the-art protein-ligand binding affinity model for drug discovery
Single-Cell (Perturbation) Model Library
NVIDIA BioNeMo blueprint for generative AI-based virtual screening
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
Mixed continous/categorical flow-matching model for de novo molecule generation.
Toolkit for open antiviral drug discovery by the ASAP Discovery Consortium
An interoperable Python framework for biomolecular simulation.
A tool for creating Quantitative Structure Property/Activity Relationship (QSPR/QSAR) models.
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
Searching for structural similarities across billions of molecules in milliseconds
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Multi-target de novo molecular generator conditioned on AlphaFold's latent protein embeddings.
[TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
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!
All in one Structure-Based Virtual Screening workflow based on the concept of consensus docking.
Single-Cell (Perturbation) Model Library
[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
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
A powerful and flexible machine learning platform for drug discovery
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Mixed continous/categorical flow-matching model for de novo molecule generation.
[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models
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
Multi-target de novo molecular generator conditioned on AlphaFold's latent protein embeddings.
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
A tool for creating Quantitative Structure Property/Activity Relationship (QSPR/QSAR) models.
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.
Toolkit for open antiviral drug discovery by the ASAP Discovery Consortium
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
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...
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
An interoperable Python framework for biomolecular simulation.
Searching for structural similarities across billions of molecules in milliseconds