Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/Thinklab-SJTU/awesome-molecular-docking

We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.
https://github.com/Thinklab-SJTU/awesome-molecular-docking

List: awesome-molecular-docking

ai-aided-drug-discovery awesome awesome-list binding bioinformatics deep-learning drug-design drug-discovery drug-protein-interactions drugai equivariant-representations generative-model geometric-deep-learning machine-learning molecular-docking molecular-dynamics optimal-transport paper-list protein-ligand-docking protein-protein-interaction

Last synced: 2 months ago
JSON representation

We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.

Lists

README 

        


  logo of the awesome series of repositories maintained by Nianzu Yang




Awesome-Molecular-Docking




    awesome

    PRs

    License

    Stars

    




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 [email protected]. 



Welcome to contribute to this repository! :clap:







Table of Contents 👈 click here to unfold the outlines



- [Related Survey](#related-survey)

- [Dataset](#dataset)

- [Software for Docking](#software-for-docking)

- [Molecule-Protein Docking](#molecule-protein-docking)

- [Protein-Protein Docking](#protein-protein-docking)

- [Molecular Dynamics Simulation](#molecular-dynamics-simulation)

- [Binding Site Identification](#binding-site-identification)

- [See Also](#see-also)







## Related Survey

- [ ] Crampon, Kevin, et al. "Machine-learning methods for ligand–protein molecular docking." Drug discovery today (2021). [[Paper](https://www.sciencedirect.com/science/article/abs/pii/S1359644621003974)]

- [ ] Harmalkar, Ameya, and Jeffrey J. Gray. "Advances to tackle backbone flexibility in protein docking." Current opinion in structural biology 67 (2021): 178-186. [[Paper](https://www.sciencedirect.com/science/article/abs/pii/S0959440X20302141?via%3Dihub)]



## 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](https://arxiv.org/abs/2210.01776)][[Code](https://github.com/gcorso/DiffDock)]

- [ ] Zhang, Yangtian, et al. "E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking." arXiv preprint arXiv:2210.06069 (2022). [[Paper](https://arxiv.org/abs/2210.06069)]

- [ ] Lu, Wei, et al. "TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction." Advances in Neural Information Processing Systems. 2022.[[Paper](https://openreview.net/forum?id=MSBDFwGYwwt)][[Code](https://github.com/luwei0917/TankBind)]

- [ ] Stärk, Hannes, et al. "Equibind: Geometric deep learning for drug binding structure prediction." International Conference on Machine Learning. PMLR, 2022. [[Paper](https://proceedings.mlr.press/v162/stark22b.html)][[Code](https://github.com/HannesStark/EquiBind)]



## 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](https://openreview.net/forum?id=GQjaI9mLet)][[Code](https://github.com/octavian-ganea/equidock_public)]



## 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](https://openreview.net/forum?id=jSorGn2Tjg)][[Code](https://github.com/luost26/diffab)]

- [ ] Jin, Wengong, Regina Barzilay, and Tommi Jaakkola. "Antibody-antigen docking and design via hierarchical structure refinement." International Conference on Machine Learning. PMLR, 2022. [[Paper](https://proceedings.mlr.press/v162/jin22a.html)][[Code](https://github.com/wengong-jin/abdockgen)]



## 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](https://arxiv.org/abs/2204.10348)][[Code](https://github.com/kyonofx/mlcgmd)]



## 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](https://openaccess.thecvf.com/content/CVPR2021/html/Sverrisson_Fast_End-to-End_Learning_on_Protein_Surfaces_CVPR_2021_paper.html)]

- [ ] Gainza, Pablo, et al. "Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning." Nature Methods 17.2 (2020): 184-192. [[Paper](https://www.nature.com/articles/s41592-019-0666-6)][[Code](https://github.com/LPDI-EPFL/masif)]



## See Also

- [awesome-python-chemistry](https://github.com/lmmentel/awesome-python-chemistry)

- [awesome-cheminformatics](https://github.com/hsiaoyi0504/awesome-cheminformatics)

- [deeplearning-biology](https://github.com/hussius/deeplearning-biology)

- [awesome-small-molecule-ml](https://github.com/benb111/awesome-small-molecule-ml)

- [Survey_AI_Drug_Discovery](https://github.com/dengjianyuan/Survey_AI_Drug_Discovery)