Citing and acknowledgements¶
Citing PocketVina¶
If you use PocketVina in your work, please cite:
@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},
}
Tools PocketVina builds on¶
Please also cite the tools that PocketVina uses:
P2Rank¶
P2Rank finds the pockets of each protein.
@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 family¶
The docking engine is based on QuickVina2-GPU-2.1, part of Vina-GPU 2.1. Its roots are Vina-GPU 2.0, Vina-GPU 2022, AutoDock Vina and QuickVina 2.
@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}
}
@article{alhossary2015quickvina2,
title = {Fast, accurate, and reliable molecular docking with QuickVina 2},
author = {Alhossary, Amr and Handoko, Stephanus Daniel and Mu, Yuguang and Kwoh, Chee-Keong},
journal = {Bioinformatics},
volume = {31},
number = {13},
pages = {2214--2216},
year = {2015},
doi = {10.1093/bioinformatics/btv082}
}
Mol*, MolViewSpec and 3Dmol.js¶
Mol* draws the 3D page of show(). MolViewSpec and 3Dmol.js draw the single-pose views of pocketvina.viz.
@article{sehnal2021molstar,
title = {Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures},
author = {Sehnal, David and Bittrich, Sebastian and Deshpande, Mandar and Svobodov{\'a}, Radka and Berka, Karel and Bazgier, V{\'a}clav and Velankar, Sameer and Burley, Stephen K and Ko{\v{c}}a, Jaroslav and Rose, Alexander S},
journal = {Nucleic Acids Research},
volume = {49},
number = {W1},
pages = {W431--W437},
year = {2021},
doi = {10.1093/nar/gkab314}
}
@article{bittrich2024molviewspec,
title = {Describing and Sharing Molecular Visualizations Using the MolViewSpec Toolkit},
author = {Bittrich, Sebastian and Midlik, Adam and Varadi, Mihaly and Velankar, Sameer and Burley, Stephen K and Young, Jasmine Y and Sehnal, David and Vallat, Brinda},
journal = {Current Protocols},
volume = {4},
pages = {e1099},
year = {2024},
doi = {10.1002/cpz1.1099}
}
@article{rego2015threedmol,
title = {3Dmol.js: molecular visualization with WebGL},
author = {Rego, Nicholas and Koes, David},
journal = {Bioinformatics},
volume = {31},
number = {8},
pages = {1322--1324},
year = {2015},
doi = {10.1093/bioinformatics/btu829}
}
PoseBusters¶
PoseBusters checks whether the docked poses are physically valid.
@article{buttenschoen2024posebusters,
title = {PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences},
author = {Buttenschoen, Martin and Morris, Garrett M and Deane, Charlotte M},
journal = {Chemical Science},
volume = {15},
number = {9},
pages = {3130--3139},
year = {2024},
doi = {10.1039/D3SC04185A}
}
RDKit and Open Babel¶
RDKit builds the 3D ligands from SMILES and writes the poses as SDF. Open Babel converts the ligands for the engine.
@misc{rdkit,
title = {RDKit: Open-source cheminformatics},
howpublished = {\url{https://www.rdkit.org}},
doi = {10.5281/zenodo.591637}
}
@article{oboyle2011openbabel,
title = {Open Babel: An open chemical toolbox},
author = {O'Boyle, Noel M and Banck, Michael and James, Craig A and Morley, Chris and Vandermeersch, Tim and Hutchison, Geoffrey R},
journal = {Journal of Cheminformatics},
volume = {3},
pages = {33},
year = {2011},
doi = {10.1186/1758-2946-3-33}
}
Licences¶
PocketVina is released under the MIT licence. The
docking engine is based on AutoDock Vina and QuickVina2-GPU-2.1 and keeps their Apache License 2.0. The notices are
in the source files. The bundled Mol* viewer is MIT licensed, with its licence files in
pocketvina/viewer/molstar-pv-5.13.1/.
Acknowledgements¶
We thank these projects for making their code open source:
Mol* and MolViewSpec
RDKit and Open Babel
About these pages¶
These pages are written in Markdown and built with Sphinx, MyST-Parser, the Furo theme and sphinx-click. They are published with GitHub Pages at https://bioinformatics.mdc-berlin.de/PocketVina/.