asarigun/pocketvina
GPU-accelerated web UI for protein-ligand docking with multi-pocket detection using PocketVina
723
asarigun/pocketvina repository overview
PocketVina
GPU-accelerated web UI for protein–ligand docking with automated multi-pocket detection.
PocketVina combines P2Rank for binding pocket prediction and QuickVina for efficient molecular docking — all accessible through a clean, browser-based interface.
It enables large-scale or interactive docking studies directly on GPU-enabled systems.
🚀 Features
- Automated pocket detection via P2Rank
- Fast molecular docking powered by QuickVina
- Web-based UI for interactive exploration
- Multi-pocket conditioning for better target coverage
- GPU acceleration for high-throughput docking
- Dockerized deployment — run anywhere with minimal setup
🧩 Getting Started
1. Pull the image
docker pull asarigun/pocketvina:latest
2. Run PocketVina Web UI
docker run --gpus all -it -p 7860:7860 asarigun/pocketvina:latest bash
python3 app/app.py
Then open http://127.0.0.1:7860/ in your browser.
Citations
If you use PocketVina-GPU in your work, please cite the following paper:
@misc{sarigun2025pocketvinaenablesscalablehighly,
title={PocketVina Enables Scalable and Highly Accurate Physically Valid Docking through Multi-Pocket Conditioning},
author={Ahmet Sarigun and Bora Uyar and Vedran Franke and Altuna Akalin},
year={2025},
eprint={2506.20043},
archivePrefix={arXiv},
primaryClass={q-bio.QM},
url={https://arxiv.org/abs/2506.20043},
}
and also cite the following papers for P2Rank and Vina families:
P2Rank
@article{krivak2018p2rank,
title = {P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure},
author = {Krivák, Radoslav and Hoksza, David},
journal = {Journal of cheminformatics},
volume = {10},
pages = {1--12},
year = {2018},
publisher = {Springer}
}
Vina Families
@article{tang2024vina,
title = {Vina-GPU 2.1: towards further optimizing docking speed and precision of AutoDock Vina and its derivatives},
author = {Tang, Shidi and Ding, Ji and Zhu, Xiangyu and Wang, Zheng and Zhao, Haitao and Wu, Jiansheng},
journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
year = {2024},
publisher = {IEEE}
}
@article{ding2023vina,
title = {Vina-GPU 2.0: further accelerating AutoDock Vina and its derivatives with graphics processing units},
author = {Ding, Ji and Tang, Shidi and Mei, Zheming and Wang, Lingyue and Huang, Qinqin and Hu, Haifeng and Ling, Ming and Wu, Jiansheng},
journal = {Journal of chemical information and modeling},
volume = {63},
number = {7},
pages = {1982--1998},
year = {2023},
publisher = {ACS Publications}
}
@article{tang2022accelerating,
title = {Accelerating autodock vina with gpus},
author = {Tang, Shidi and Chen, Ruiqi and Lin, Mengru and Lin, Qingde and Zhu, Yanxiang and Ding, Ji and Hu, Haifeng and Ling, Ming and Wu, Jiansheng},
journal = {Molecules},
volume = {27},
number = {9},
pages = {3041},
year = {2022},
publisher = {MDPI}
}
@article{trott2010autodock,
title = {AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading},
author = {Trott, Oleg and Olson, Arthur J},
journal = {Journal of computational chemistry},
volume = {31},
number = {2},
pages = {455--461},
year = {2010},
publisher = {Wiley Online Library}
}
License
MIT License
Support
For issues, please visit:
https://github.com/BIMSBbioinfo/PocketVina/issues
For discussions and questions, please visit:
https://github.com/BIMSBbioinfo/PocketVina/discussions
Acknowledgements
We thank the following projects for their open-sourcing their codes:
Tag summary
Content type
Image
Digest
sha256:3ba1d7dbe…
Size
5.8 GB
Last updated
11 months ago
docker pull asarigun/pocketvina