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Prediction of Functional Sites Based on the Fuzzy Oil Drop Model

A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized...

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Detalles Bibliográficos
Autores principales: Bryliński, Michał, Prymula, Katarzyna, Jurkowski, Wiktor, Kochańczyk, Marek, Stawowczyk, Ewa, Konieczny, Leszek, Roterman, Irena
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1876487/
https://www.ncbi.nlm.nih.gov/pubmed/17530916
http://dx.doi.org/10.1371/journal.pcbi.0030094
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author Bryliński, Michał
Prymula, Katarzyna
Jurkowski, Wiktor
Kochańczyk, Marek
Stawowczyk, Ewa
Konieczny, Leszek
Roterman, Irena
author_facet Bryliński, Michał
Prymula, Katarzyna
Jurkowski, Wiktor
Kochańczyk, Marek
Stawowczyk, Ewa
Konieczny, Leszek
Roterman, Irena
author_sort Bryliński, Michał
collection PubMed
description A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized experimentally, await identification of their biological activity. Currently used methods do not always yield satisfactory results, and new algorithms need to be developed to recognize the localization of active sites in proteins. This paper describes a computational model that can be used to identify potential areas that are able to interact with other molecules (ligands, substrates, inhibitors, etc.). The model for active site recognition is based on the analysis of hydrophobicity distribution in protein molecules. It is shown, based on the analyses of proteins with known biological activity and of proteins of unknown function, that the region of significantly irregular hydrophobicity distribution in proteins appears to be function related.
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spelling pubmed-18764872007-05-24 Prediction of Functional Sites Based on the Fuzzy Oil Drop Model Bryliński, Michał Prymula, Katarzyna Jurkowski, Wiktor Kochańczyk, Marek Stawowczyk, Ewa Konieczny, Leszek Roterman, Irena PLoS Comput Biol Research Article A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized experimentally, await identification of their biological activity. Currently used methods do not always yield satisfactory results, and new algorithms need to be developed to recognize the localization of active sites in proteins. This paper describes a computational model that can be used to identify potential areas that are able to interact with other molecules (ligands, substrates, inhibitors, etc.). The model for active site recognition is based on the analysis of hydrophobicity distribution in protein molecules. It is shown, based on the analyses of proteins with known biological activity and of proteins of unknown function, that the region of significantly irregular hydrophobicity distribution in proteins appears to be function related. Public Library of Science 2007-05 2007-05-25 /pmc/articles/PMC1876487/ /pubmed/17530916 http://dx.doi.org/10.1371/journal.pcbi.0030094 Text en © 2007 Bryliński 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Bryliński, Michał
Prymula, Katarzyna
Jurkowski, Wiktor
Kochańczyk, Marek
Stawowczyk, Ewa
Konieczny, Leszek
Roterman, Irena
Prediction of Functional Sites Based on the Fuzzy Oil Drop Model
title Prediction of Functional Sites Based on the Fuzzy Oil Drop Model
title_full Prediction of Functional Sites Based on the Fuzzy Oil Drop Model
title_fullStr Prediction of Functional Sites Based on the Fuzzy Oil Drop Model
title_full_unstemmed Prediction of Functional Sites Based on the Fuzzy Oil Drop Model
title_short Prediction of Functional Sites Based on the Fuzzy Oil Drop Model
title_sort prediction of functional sites based on the fuzzy oil drop model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1876487/
https://www.ncbi.nlm.nih.gov/pubmed/17530916
http://dx.doi.org/10.1371/journal.pcbi.0030094
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