Popular GitHub Repositories for Organic Chemistry

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

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.

LLM Agent that leverages cheminformatics tools to provide informed responses.

Message Passing Neural Networks for Molecule Property Prediction

A deep learning package for many-body potential energy representation and molecular dynamics

SchNetPack - Deep Neural Networks for Atomistic Systems

Python package for graph neural networks in chemistry and biology

A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry

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

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

Accurate Neural Network Potential on PyTorch

bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.

Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).

Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm

Original implementation of the paper "SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery" by Shion Honda et al.

RXNMapper: Unsupervised attention-guided atom-mapping. Code complementing our Science Advances publication on "Extraction of organic chemistry grammar from unsupervised learning of chemical reactions" (https://advances.sciencemag.org/content/7/15/eabe4166).

Lanczos Network, Graph Neural Networks, Deep Graph Convolutional Networks, Deep Learning on Graph Structured Data, QM8 Quantum Chemistry Benchmark, ICLR 2019

[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Tensorflow + Molecules = TensorMol