Awesome-Awesome-Chemistry

A curated list of awesome chemistry resources and repositories across computational chemistry, cheminformatics, molecular simulation, machine learning for chemistry, visualization and educational material.

灵感来自于 awesome-python，旨在为化学与化学信息学相关的研究者、学生与工程师提供一个整理良好的资源列表。

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Table of contents/目录

• Awesome Chemistry repos

  • AI4Chem
  • Computational Chemistry
  • Chemistry Education.

• Chemistry Packages

  • General Chemistry
  • Machine Learning
  • Generative Molecular Design
  • Simulations
  • Molecular Visualization
  • Database Wrappers & Data
  • Learning Resources

• Contributing

• License

• See Also

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How to use / 使用方法

Browse the categories below and follow the links to the projects, libraries, datasets and tutorials. Contributions are welcome — see the Contributing section.

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General Chemistry

Packages and tools for general chemistry and cheminformatics.

• RDKit — Open-source cheminformatics. (https://github.com/rdkit/rdkit)
• Open Babel — Chemical toolbox designed to speak the many languages of chemical data. (https://github.com/openbabel/openbabel)
• OpenFF / Open Force Field Initiative — Tools and force fields for molecular simulations. (https://github.com/openforcefield)
• OpenMM — High-performance toolkit for molecular simulation. (https://github.com/openmm)

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Machine Learning

Libraries, frameworks and examples applying machine learning to chemistry.

• DeepChem — Library for deep learning in drug discovery, quantum chemistry and materials science. (https://github.com/deepchem/deepchem)
• Chemprop — Message-passing neural networks for molecular property prediction. (https://github.com/chemprop/chemprop)
• SchNetPack — Deep learning toolkit for atomistic systems. (https://github.com/atomistic-machine-learning/schnetpack)

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Generative Molecular Design

Tools and models for de novo molecule generation and molecular optimization.

• MolGAN — Generative adversarial networks for molecular graphs. (https://github.com/nicola-decao/MolGAN)
• REINVENT — Reinforcement learning for molecule generation (commercial/academic forks exist). (https://github.com/MolecularAI/reinvent)
• GuacaMol — Benchmarks and baselines for de novo molecular design. (https://github.com/aspuru-guzik-group/guacamol)

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Simulations

Classical and quantum chemistry simulation packages and workflows.

• GROMACS — Fast, versatile molecular dynamics. (https://github.com/gromacs/gromacs)
• LAMMPS — Large-scale Atomic/Molecular Massively Parallel Simulator. (https://github.com/lammps/lammps)
• Psi4 — Quantum chemistry package for ab initio calculations. (https://github.com/psi4/psi4)
• PySCF — Python-based simulations of chemistry framework. (https://github.com/pyscf/pyscf)
• ASE (Atomic Simulation Environment) — Python library for setting up, running, and analyzing atomistic simulations. (https://github.com/ase/ase)

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Molecular Visualization

Tools for viewing and preparing molecular structures.

• PyMOL — Molecular visualization system. (https://github.com/schrodinger/pymol-open-source)
• VMD — Visual Molecular Dynamics (website: http://www.ks.uiuc.edu/Research/vmd/)
• NGL Viewer — Web-based molecular visualization. (https://github.com/nglviewer/ngl)
• Mol* — Modern web-based molecular viewer (used by RCSB PDB). (https://github.com/molstar/molstar)

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Database Wrappers & Data

APIs, wrappers, and datasets commonly used in cheminformatics and computational chemistry.

• ChEMBL — Bioactive drug-like small molecules database. (https://github.com/chembl/chembl_db)
• PubChem — Chemical molecules and their activities against biological assays. (https://pubchem.ncbi.nlm.nih.gov/)
• ZINC — Free database of commercially available compounds for virtual screening. (http://zinc.docking.org/)
• PDB — Protein Data Bank for 3D structural data. (https://www.rcsb.org/)
• RDKit Data resources — example datasets and utilities. (https://github.com/rdkit/rdkit)

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Learning Resources

Tutorials, books, courses and papers to help you get started.

• "Computational Chemistry" textbooks (various authors) — Good starting references.
• "Molecular Modeling Basics" tutorials — Many university lecture notes and labs.
• DeepChem tutorials and example notebooks. (https://github.com/deepchem/deepchem/tree/master/examples)
• Psi4NumPy — Tutorials combining quantum chemistry and NumPy. (https://github.com/psi4/psi4numpy)

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Contributing / 贡献

Contributions are very welcome! To contribute:

1. Fork the repository.
2. Create a branch: git checkout -b my-feature
3. Add your resource to the appropriate section in README.md following the existing format. Include a short description and a link.
4. Open a pull request describing your change.

Please follow these guidelines when suggesting additions:

• Be respectful and add only high-quality, well-documented resources.
• Avoid link-only PRs — include a one-line description and why the resource is relevant.
• Group similar entries and keep the README organized.

If you'd like, open issues to propose larger reorganizations before submitting PRs.

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License / 许可证

This repository is maintained under the Apache License 2.0. See the LICENSE file for details.

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See Also/了解更多

• awesome-chemistry collections and related awesome lists (search "awesome chemistry" on GitHub).
• awesome lists: https://github.com/sindresorhus/awesome

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Maintainers / 联系方式

• Repository owner: @YuzeHao2023

Acknowledgements: Thanks to the open-source projects and communities that make this list possible.