About
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.
Underlying method
PrankWeb is web interface based on P2Rank standalone method . For batch-processing, it is recommended to download standalone version of P2Rank and run experiments locally.
Training Datasets
PrankWeb classification models have been trained and validated on publicly available datasets .
Precomputed predictions
We have computed the ligand-binding sites predictions for two components of the AlphaFold DB, the “model organism proteomes” and “Swiss-Prot”, as well as PDB. For each database, AlphaFold DB and PDB, we computed the prediction with and without conservations. What is available for download is the content of the predictions directory created as described at wiki page Large scale Predictions.
- PDB with conservation (183051 predicated structures)
- PDB (183051 predicated structures)
- AlphaFold with conservation (365198 predicated structures)
- AlphaFold (365198 predicated structures)
Citing
If you use P2Rank online service, please cite:
- Lukáš Jendele and Radoslav Krivák and Petr Škoda and Marian Novotný and David Hoksza. PrankWeb: a web server for ligand binding site prediction and visualization. Nucleic Acids Research. May 2019
- Radoslav Krivák and David Hoksza. P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure. Journal of Cheminformatics. Aug 2018
Authors
David Hoksza
(contact person)
Faculty of Mathematics and Physics, Charles University
david.hoksza (at) matfyz.cuni.cz.
Lukas Jendele
Faculty of Mathematics and Physics, Charles University
Department of Computer Science, ETH Zurich
lukas.jendele (at) gmail.com
Radoslav Krivák
Faculty of Mathematics and Physics, Charles University
rkrivak (at) gmail.com
Marian Novotný
Faculty of Science, Charles University
marian.novotny (at) natur.cuni.cz
PrankWeb is a part of services provided by ELIXIR – European research infrastructure for biological information.
See services provided by ELIXIR's Czech Republic Node.
PrankWeb, Charles University 2017-