PrankWeb 4: a modular web server for protein–ligand binding site prediction and downstream analysis
Knowledge of protein-ligand binding sites (LBSs) is crucial for advancing our understanding of biology and developing practical applications in fields such as medicine or biotechnology. PrankWeb is a web server that allows users to predict LBSs from a given three-dimensional structure. It provides access to P2Rank, a state-of-the-art machine learning tool for binding site prediction. Here, we present a new version of PrankWeb enabling the development of both client- and server-side modules acting as postprocessing tasks on the predicted pockets. Furthermore, each module can be associated with a visualization module that acts on the results provided by both client- and server-side modules. This newly developed system was utilized to implement the ability to dock user-provided molecules into the predicted pockets using AutoDock Vina (server-side module) and to interactively visualize the predicted poses (visualization module). In addition to introducing a modular architecture, we revamped PrankWeb's interface to better support the modules and enhance user interaction between the 1D and 3D viewers. We introduced a new, faster P2Rank backend or user-friendly exports, including ChimeraX visualization.
Authors
- Kamila Riedlová (ORCID: https://orcid.org/0000-0002-9134-2297)
- L. Polák (ORCID: https://orcid.org/0000-0002-1190-8124)
- David Hoksza (ORCID: https://orcid.org/0000-0003-4679-0557)
- Petr Škoda (ORCID: https://orcid.org/0000-0002-2732-9370)
- Marián Novotný (ORCID: https://orcid.org/0000-0001-8788-3202)
- Radoslav Krivák (ORCID: https://orcid.org/0000-0001-7521-0844)
Institutions
- Czech Academy of Sciences (CZ)
- Charles University (CZ)
- Czech Academy of Sciences, Institute of Organic Chemistry and Biochemistry (CZ)
- Software (Spain) (ES)
Publication Details
- Journal
- Nucleic Acids Research
- Published
- 2025-05-19
- DOI
- https://doi.org/10.1093/nar/gkaf421
- Citations
- 26
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 39.11
Funders
- Ministry of Higher Education and Scientific Research
- Grantová Agentura České Republiky