Format

Send to

Choose Destination
See comment in PubMed Commons below
PLoS One. 2011;6(5):e20445. doi: 10.1371/journal.pone.0020445. Epub 2011 May 31.

Identification of antifreeze proteins and their functional residues by support vector machine and genetic algorithms based on n-peptide compositions.

Author information

1
Department of Information Engineering and Computer Science, Feng Chia University, Taichung, Taiwan. yucs@fcu.edu.tw

Abstract

For the first time, multiple sets of n-peptide compositions from antifreeze protein (AFP) sequences of various cold-adapted fish and insects were analyzed using support vector machine and genetic algorithms. The identification of AFPs is difficult because they exist as evolutionarily divergent types, and because their sequences and structures are present in limited numbers in currently available databases. Our results reveal that it is feasible to identify the shared sequential features among the various structural types of AFPs. Moreover, we were able to identify residues involved in ice binding without requiring knowledge of the three-dimensional structures of these AFPs. This approach should be useful for genomic and proteomic studies involving cold-adapted organisms.

PMID:
21655262
PMCID:
PMC3105057
DOI:
10.1371/journal.pone.0020445
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Public Library of Science Icon for PubMed Central
    Loading ...
    Support Center