Popular GitHub Repositories for Molecule Generation

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

Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

DrugAssist: A Large Language Model for Molecule Optimization

[ICLR 2022] Data-Efficient Graph Grammar Learning for Molecular Generation

(differentiable) gradient-based optimization on a chemical graph for de novo molecule design/optimization (ICLR 2022)

Official Github for "Molecular generative model via retrosynthetically prepared chemical building block assembly" (Advanced Science)

Code for AAAI24 paper Text-Guided Molecule Generation with Diffusion Language Model

[NeurIPS'23] Source code of "Data-Centric Learning from Unlabeled Graphs with Diffusion Model": A data-centric transfer learning framework with diffusion model on graphs.

Multiresolution Equivariant Graph Variational Autoencoder (MGVAE) https://arxiv.org/abs/2106.00967

Active learning workflow to train and fine-tune molecular property predictors with chemist feedback for goal-oriented molecule generation.

Generative models of chemical data for PaccMann^RL

Deep Learning And Applied Artificial Intelligence Project 2019/2020 - Molecular Synthesis & Reconstruction

Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).

An attempt into Molecule Generation

OM-Diff: Inverse-design of organometallic catalysts with guided equivariant denoising diffusion

Generate SMILES using RNN and VAE models. Additionally, two reinforcement learning methods are implemented.