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

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

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

Molecular Processing Made Easy.

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

Interface for AutoDock, molecule parameterization

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)

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.

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

An automated scoring function to facilitate and standardize the evaluation of goal-directed generative models for de novo molecular design

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

MaSIF-neosurf: surface-based protein design for ternary complexes.

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

Official repository for MolCRAFT series

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

Multi-domain Distribution Learning for De Novo Drug Design

A snakemake-based workflow for FEP and MM(PB/GB)SA calculations with GROMACS