Pregled bibliografske jedinice broj: 1111183
A structure and evolution-guided Monte Carlo sequence selection strategy for multiple alignment-based analysis of proteins
A structure and evolution-guided Monte Carlo sequence selection strategy for multiple alignment-based analysis of proteins // Bioinformatics, 22 (2006), 2; 149-156 doi:10.1093/bioinformatics/bti791 (međunarodna recenzija, članak, znanstveni)
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Naslov
A structure and evolution-guided Monte Carlo
sequence selection strategy for multiple
alignment-based analysis of proteins
Autori
Mihalek, I. ; Reš, I. ; Lichtarge, O.
Izvornik
Bioinformatics (1367-4803) 22
(2006), 2;
149-156
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
protein ; functional surface ; evolution
Sažetak
Motivation: Various multiple sequence alignment- based methods have been proposed to detect functional surfaces in proteins, such as active sites or protein interfaces. The effect that the choice of sequences has on the conclusions of such analysis has seldom been discussed. In particular, no method has been discussed in terms of its ability to optimize the sequence selection for the reliable detection of functional surfaces. Results: Here we propose, for the case of proteins with known structure, a heuristic Metropolis Monte Carlo strategy to select sequences from a large set of homologues, in order to improve detection of functional surfaces. The quantity guiding the optimization is the clustering of residues which are under increased evolutionary pressure, according to the sample of sequences under consideration. We show that we can either improve the overlap of our prediction with known functional surfaces in comparison with the sequence similarity criteria of selection or match the quality of prediction obtained through more elaborate non-structure based-methods of sequence selection. For the purpose of demonstration we use a set of 50 homodimerizing enzymes which were co-crystallized with their substrates and cofactors.
Izvorni jezik
Engleski
Znanstvena područja
Biologija, Računarstvo, Interdisciplinarne biotehničke znanosti, Biotehnologija u biomedicini (prirodno područje, biomedicina i zdravstvo, biotehničko područje)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE