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2009 | 56 | 1 | 167-176
Article title

Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models

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Abstracts
EN
Antibacterial peptides are researched mainly for the potential benefit they have in a variety of socially relevant diseases, used by the host to protect itself from different types of pathogenic bacteria. We used the mathematical-computational method known as Hidden Markov models (HMMs) in targeting a subset of antibacterial peptides named Selective Cationic Amphipatic Antibacterial Peptides (SCAAPs). The main difference in the implementation of HMMs was focused on the detection of SCAAP using principally five physical-chemical properties for each candidate SCAAPs, instead of using the statistical information about the amino acids which form a peptide. By this method a cluster of antibacterial peptides was detected and as a result the following were found: 9 SCAAPs, 6 synthetic antibacterial peptides that belong to a subregion of Cecropin A and Magainin 2, and 19 peptides from the Cecropin A family. A scoring function was developed using HMMs as its core, uniquely employing information accessible from the databases.
Publisher

Year
Volume
56
Issue
1
Pages
167-176
Physical description
Dates
published
2009
received
2009-01-30
revised
2009-03-03
accepted
2009-03-11
(unknown)
2009-03-18
Contributors
  • Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Circuito Exterior s/n Ciudad Universitaria Delegación Coyoacán, México City, México
  • Departamento de Matemáticas, Facultad de Ciencias, Universidad Nacional Autónoma de México, Circuito Exterior s/n Ciudad Universitaria Delegación Coyoacán, México City, México
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bwmeta1.element.bwnjournal-article-abpv56p167kz
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