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<p align="center"> <img width="400" src="assets/logo.svg" alt="logo of the awesome series of repositories maintained by Nianzu Yang"> </p> <h1 align="center"><b>Awesome-Molecular-Docking</b></h1> <p align="center"> <a href="https://awesome.re"><img src="https://awesome.re/badge.svg" alt="awesome"></a> <a href="https://github.com/Thinklab-SJTU/awesome-molecular-docking/pulls"><img src="https://img.shields.io/badge/PRs-Welcome-yellow" alt="PRs"></a> <a href="https://github.com/Thinklab-SJTU/awesome-molecular-docking/blob/master/LICENSE"><img alt="License" src="https://img.shields.io/github/license/Thinklab-SJTU/awesome-molecular-docking?color=green"></a> <a href="https://github.com/Thinklab-SJTU/awesome-molecular-docking/stargazers"><img src="https://img.shields.io/github/stars/Thinklab-SJTU/awesome-molecular-docking?color=red&label=Star" alt="Stars"></a> <!-- <a href="https://yangnianzu0515.github.io/"><img src="https://img.shields.io/badge/Nianzu-Yang-blue" alt="MyWebsite"></a> --> </p>We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.
We will update this repository regularly. :sunglasses:
If you want to add related works to this repository, please feel free to contact me via yangnianzu@sjtu.edu.cn.
Welcome to contribute to this repository! :clap:
<br> <details> <summary><b><font size='8'>Table of Contents</font></b><font size='4'> 👈 <i>click here to unfold the outlines</i></font></summary>- Related Survey
- Dataset
- Software for Docking
- Molecule-Protein Docking
- Protein-Protein Docking
- Molecular Dynamics Simulation
- Binding Site Identification
- See Also
Related Survey
- Crampon, Kevin, et al. "Machine-learning methods for ligand–protein molecular docking." Drug discovery today (2021). [Paper]
- Harmalkar, Ameya, and Jeffrey J. Gray. "Advances to tackle backbone flexibility in protein docking." Current opinion in structural biology 67 (2021): 178-186. [Paper]
Dataset
- PDBBind
- Structural Antibody Database (SAbDab)
- Database of Interacting Protein Structures (DIPS)
Software for Docking
- ATTRACT
- HDOCK
- CLUSPRO
- PATCHDOCK
Molecule-Protein Docking
- Corso, Gabriele, et al. "DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking." arXiv preprint arXiv:2210.01776 (2022). [Paper][Code]
- Zhang, Yangtian, et al. "E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking." arXiv preprint arXiv:2210.06069 (2022). [Paper]
- Lu, Wei, et al. "TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction." Advances in Neural Information Processing Systems. 2022.[Paper][Code]
- Stärk, Hannes, et al. "Equibind: Geometric deep learning for drug binding structure prediction." International Conference on Machine Learning. PMLR, 2022. [Paper][Code]
Protein-Protein Docking
- Ganea, Octavian-Eugen, et al. "Independent se (3)-equivariant models for end-to-end rigid protein docking." International Conference on Learning Representations (2022). [Paper][Code]
Antibody Design
- Luo, S., Su, Y., Peng, X., Wang, S., Peng, J., & Ma, J. Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures. In Advances in Neural Information Processing Systems. [Paper][Code]
- Jin, Wengong, Regina Barzilay, and Tommi Jaakkola. "Antibody-antigen docking and design via hierarchical structure refinement." International Conference on Machine Learning. PMLR, 2022. [Paper][Code]
Molecular Dynamics Simulation
- Fu, Xiang, et al. "Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric Machine Learning." arXiv preprint arXiv:2204.10348 (2022). [Paper][Code]
Binding Site Identification
- Freyr, et al. "Fast end-to-end learning on protein surfaces." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021. [Paper]
- Gainza, Pablo, et al. "Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning." Nature Methods 17.2 (2020): 184-192. [Paper][Code]