Proteins are fundamental building blocks of all living organisms. They perform their function by binding to other molecules. This project deals with interactions between proteins and small molecules (so called ligands) because most of the currently used drugs are small molecules. While there are several tools that can predict these interactions, they are almost none for their visualization. Thus, we built a new visualization website by combining several protein visualizers together. Since evolutionary homology correlates with binding sites, our web interface also displays homology for comparison. We developed several ways how to calculate homology, and used it to improve detection of protein-ligand binding sites. Here we present PrankWeb, a modern web application for structure and sequence visualization of a protein and its protein-ligand binding sites as well as evolutionary homology. We hope that it will provide a quick and convenient way for scientists to analyze proteins.

P2rank is a member of the PDBe-KB consortium, providing predictions of ligand binding sites to the knowledgebase.


If you use P2Rank online service, please cite:


We would be happy to hear about your use cases, experiences and ideas/feature requests. Please feel free to raise an issue on a P2Rank GitHub issue tracker (predictions and p2rank related) or P2RankWeb GitHub issue tracker (webservice and websites related).


Lukas Jendele

Faculty of Mathematics and Physics, Charles University

Department of Computer Science, ETH Zurich

lukas.jendele (at) gmail.com

David Hoksza

Faculty of Mathematics and Physics, Charles University

Luxembourg Centre for Systems Biomedicine, University of Luxembourg

david.hoksza (at) mff.cuni.cz

Radoslav Krivák

Faculty of Mathematics and Physics, Charles University

rkrivak (at) gmail.com

Petr Škoda

Faculty of Mathematics and Physics, Charles University

skodapetr (at) gmail.com

Marian Novotný

Faculty of Science, Charles University

marian.novotny (at) natur.cuni.cz

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