This repository contains code for the paper: Beyond Generative Models: Superfast Traversal, Optimization, Novelty, Exploration and Discovery (STONED) Algorithm for Molecules using SELFIES

[PNAS 2025] Code of "Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design".

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Robust representation of semantically constrained graphs, in particular for molecules in chemistry

A Euclidean diffusion model for structure-based drug design.

Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"

Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025 oral]

Benchmarks for generative chemistry

[Sci. Adv. 2026] The official repository of our paper "Steering Semi-flexible Molecular Diffusion Model for Structure-Based Drug Design with Reinforcement Learning"

Code for 10.1021/acscentsci.7b00572, now running on Keras 2.0 and Tensorflow

A powerful and flexible machine learning platform for drug discovery

The official PyTorch implementation of PGMG: A Pharmacophore-Guided Deep Learning Approach for Bioactive Molecule Generation.

PhoreGen: Pharmacophore-Oriented 3D Molecular Generation towards Efficient Feature-Customized Drug Discovery https://www.nature.com/articles/s43588-025-00850-5

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