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Prediction of functional sites based on the fuzzy oil drop model
Brylinski, Michal; Prymula, Katarzyna; Jurkowski, Wiktor et al.
2007In PLoS Computational Biology, 3 (5), p. 1-2
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Abstract :
[en] 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.
Disciplines :
Biochemistry, biophysics & molecular biology
Identifiers :
UNILU:UL-ARTICLE-2012-584
Author, co-author :
Brylinski, Michal
Prymula, Katarzyna
Jurkowski, Wiktor ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Kochanczyk, Marek
Stawowczyk, Ewa
Konieczny, Leszek
Roterman, Irena
External co-authors :
yes
Language :
English
Title :
Prediction of functional sites based on the fuzzy oil drop model
Publication date :
2007
Journal title :
PLoS Computational Biology
ISSN :
1553-7358
Publisher :
Public Library of Science, San Francisco, United States - California
Volume :
3
Issue :
5
Pages :
1-2
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBilu :
since 08 April 2016

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