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Normal Modes Expose Active Sites in Enzymes

Accurate prediction of active sites is an important tool in bioinformatics. Here we present an improved structure based technique to expose active sites that is based on large changes of solvent accessibility accompanying normal mode dynamics. The technique which detects EXPOsure of active SITes thr...

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Autores principales: Glantz-Gashai, Yitav, Meirson, Tomer, Samson, Abraham O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5225006/
https://www.ncbi.nlm.nih.gov/pubmed/28002427
http://dx.doi.org/10.1371/journal.pcbi.1005293
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author Glantz-Gashai, Yitav
Meirson, Tomer
Samson, Abraham O.
author_facet Glantz-Gashai, Yitav
Meirson, Tomer
Samson, Abraham O.
author_sort Glantz-Gashai, Yitav
collection PubMed
description Accurate prediction of active sites is an important tool in bioinformatics. Here we present an improved structure based technique to expose active sites that is based on large changes of solvent accessibility accompanying normal mode dynamics. The technique which detects EXPOsure of active SITes through normal modEs is named EXPOSITE. The technique is trained using a small 133 enzyme dataset and tested using a large 845 enzyme dataset, both with known active site residues. EXPOSITE is also tested in a benchmark protein ligand dataset (PLD) comprising 48 proteins with and without bound ligands. EXPOSITE is shown to successfully locate the active site in most instances, and is found to be more accurate than other structure-based techniques. Interestingly, in several instances, the active site does not correspond to the largest pocket. EXPOSITE is advantageous due to its high precision and paves the way for structure based prediction of active site in enzymes.
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spelling pubmed-52250062017-01-25 Normal Modes Expose Active Sites in Enzymes Glantz-Gashai, Yitav Meirson, Tomer Samson, Abraham O. PLoS Comput Biol Research Article Accurate prediction of active sites is an important tool in bioinformatics. Here we present an improved structure based technique to expose active sites that is based on large changes of solvent accessibility accompanying normal mode dynamics. The technique which detects EXPOsure of active SITes through normal modEs is named EXPOSITE. The technique is trained using a small 133 enzyme dataset and tested using a large 845 enzyme dataset, both with known active site residues. EXPOSITE is also tested in a benchmark protein ligand dataset (PLD) comprising 48 proteins with and without bound ligands. EXPOSITE is shown to successfully locate the active site in most instances, and is found to be more accurate than other structure-based techniques. Interestingly, in several instances, the active site does not correspond to the largest pocket. EXPOSITE is advantageous due to its high precision and paves the way for structure based prediction of active site in enzymes. Public Library of Science 2016-12-21 /pmc/articles/PMC5225006/ /pubmed/28002427 http://dx.doi.org/10.1371/journal.pcbi.1005293 Text en © 2016 Glantz-Gashai et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Glantz-Gashai, Yitav
Meirson, Tomer
Samson, Abraham O.
Normal Modes Expose Active Sites in Enzymes
title Normal Modes Expose Active Sites in Enzymes
title_full Normal Modes Expose Active Sites in Enzymes
title_fullStr Normal Modes Expose Active Sites in Enzymes
title_full_unstemmed Normal Modes Expose Active Sites in Enzymes
title_short Normal Modes Expose Active Sites in Enzymes
title_sort normal modes expose active sites in enzymes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5225006/
https://www.ncbi.nlm.nih.gov/pubmed/28002427
http://dx.doi.org/10.1371/journal.pcbi.1005293
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