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 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.
Bryliński
Michał
M
Department of Bioinformatics and Telemedicine, Jagiellonian University-Collegium Medicum, Kraków, Poland.
Prymula
Katarzyna
K
Jurkowski
Wiktor
W
Kochańczyk
Marek
M
Stawowczyk
Ewa
E
Konieczny
Leszek
L
Roterman
Irena
I
D000465:Algorithms; D000595:Amino Acid Sequence; D001665:Binding Sites; D003198:Computer Simulation; D017143:Fuzzy Logic; D057927:Hydrophobic and Hydrophilic Interactions; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009821:Oils / Q000737:chemistry; D011485:Protein Binding; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*
D009821:Oils