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PrankWeb: a web server for ligand binding site prediction and visualization
PrankWeb is an online resource providing an interface to P2Rank, a state-of-the-art method for ligand binding site prediction. P2Rank is a template-free machine learning method based on the prediction of local chemical neighborhood ligandability centered on points placed on a solvent-accessible prot...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602436/ https://www.ncbi.nlm.nih.gov/pubmed/31114880 http://dx.doi.org/10.1093/nar/gkz424 |
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author | Jendele, Lukas Krivak, Radoslav Skoda, Petr Novotny, Marian Hoksza, David |
author_facet | Jendele, Lukas Krivak, Radoslav Skoda, Petr Novotny, Marian Hoksza, David |
author_sort | Jendele, Lukas |
collection | PubMed |
description | PrankWeb is an online resource providing an interface to P2Rank, a state-of-the-art method for ligand binding site prediction. P2Rank is a template-free machine learning method based on the prediction of local chemical neighborhood ligandability centered on points placed on a solvent-accessible protein surface. Points with a high ligandability score are then clustered to form the resulting ligand binding sites. In addition, PrankWeb provides a web interface enabling users to easily carry out the prediction and visually inspect the predicted binding sites via an integrated sequence-structure view. Moreover, PrankWeb can determine sequence conservation for the input molecule and use this in both the prediction and result visualization steps. Alongside its online visualization options, PrankWeb also offers the possibility of exporting the results as a PyMOL script for offline visualization. The web frontend communicates with the server side via a REST API. In high-throughput scenarios, therefore, users can utilize the server API directly, bypassing the need for a web-based frontend or installation of the P2Rank application. PrankWeb is available at http://prankweb.cz/, while the web application source code and the P2Rank method can be accessed at https://github.com/jendelel/PrankWebApp and https://github.com/rdk/p2rank, respectively. |
format | Online Article Text |
id | pubmed-6602436 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-66024362019-07-05 PrankWeb: a web server for ligand binding site prediction and visualization Jendele, Lukas Krivak, Radoslav Skoda, Petr Novotny, Marian Hoksza, David Nucleic Acids Res Web Server Issue PrankWeb is an online resource providing an interface to P2Rank, a state-of-the-art method for ligand binding site prediction. P2Rank is a template-free machine learning method based on the prediction of local chemical neighborhood ligandability centered on points placed on a solvent-accessible protein surface. Points with a high ligandability score are then clustered to form the resulting ligand binding sites. In addition, PrankWeb provides a web interface enabling users to easily carry out the prediction and visually inspect the predicted binding sites via an integrated sequence-structure view. Moreover, PrankWeb can determine sequence conservation for the input molecule and use this in both the prediction and result visualization steps. Alongside its online visualization options, PrankWeb also offers the possibility of exporting the results as a PyMOL script for offline visualization. The web frontend communicates with the server side via a REST API. In high-throughput scenarios, therefore, users can utilize the server API directly, bypassing the need for a web-based frontend or installation of the P2Rank application. PrankWeb is available at http://prankweb.cz/, while the web application source code and the P2Rank method can be accessed at https://github.com/jendelel/PrankWebApp and https://github.com/rdk/p2rank, respectively. Oxford University Press 2019-07-02 2019-05-22 /pmc/articles/PMC6602436/ /pubmed/31114880 http://dx.doi.org/10.1093/nar/gkz424 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Jendele, Lukas Krivak, Radoslav Skoda, Petr Novotny, Marian Hoksza, David PrankWeb: a web server for ligand binding site prediction and visualization |
title | PrankWeb: a web server for ligand binding site prediction and visualization |
title_full | PrankWeb: a web server for ligand binding site prediction and visualization |
title_fullStr | PrankWeb: a web server for ligand binding site prediction and visualization |
title_full_unstemmed | PrankWeb: a web server for ligand binding site prediction and visualization |
title_short | PrankWeb: a web server for ligand binding site prediction and visualization |
title_sort | prankweb: a web server for ligand binding site prediction and visualization |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602436/ https://www.ncbi.nlm.nih.gov/pubmed/31114880 http://dx.doi.org/10.1093/nar/gkz424 |
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