List of Molecular and Material design using Generative AI and Deep Learning

OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research

Molecular Processing Made Easy.

AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.

A Euclidean diffusion model for structure-based drug design.

Interaction Fingerprints for protein-ligand complexes and more

DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design

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.

Official code repository of < CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph >

The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)

Interface for AutoDock, molecule parameterization

TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design

A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.

Python for chemoinformatics

DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins

benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.

We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.

Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)

Mixed continous/categorical flow-matching model for de novo molecule generation.

Awesome De novo drugs design papers