Possible computational filter to detect proteins associated to influenza A subtype H1N1.

Carlos Polanco; Thomas Buhse; Jorge Alberto Castañón-González; José Lino Samaniego

doi:10.18388/abp.2014_1832

Possible computational filter to detect proteins associated to influenza A subtype H1N1.

Carlos Polanco Facultad de Ciencias de la Salud, Universidad Anáhuac, Col. Lomas Anáhuac, Huixquilucan Estado de México, México.;
Thomas Buhse Centro de Investigaciones Químicas, Universidad Autónoma del Estado de Morelos, Cuernavaca Morelos, México.;
Jorge Alberto Castañón-González Facultad de Ciencias de la Salud, Universidad Anáhuac, Col. Lomas Anáhuac, Huixquilucan Estado de México, México.;
José Lino Samaniego Facultad de Ciencias de la Salud, Universidad Anáhuac, Col. Lomas Anáhuac, Huixquilucan Estado de México, México.;

DOI: https://doi.org/10.18388/abp.2014_1832

Abstract

The design of drugs with bioinformatics methods to identify proteins and peptides with a specific toxic action is increasingly recurrent. Here, we identify toxic proteins towards the influenza A virus subtype H1N1 located at the UniProt database. Our quantitative structure-activity relationship (QSAR) approach is based on the analysis of the linear peptide sequence with the so-called Polarity Index Method that shows an efficiency of 90% for proteins from the Uniprot Database. This method was exhaustively verified with the APD2, CPPsite, Uniprot, and AmyPDB databases as well as with the set of antibacterial peptides studied by del Rio et al. and Oldfield et al.

Published

2014-11-07

Issue

Vol. 61 No. 4 (2014)

Section

Articles

Acta Biochimica Polonica is an OpenAccess quarterly and publishes four issues a year. All contents are distributed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY 4.0) license. Everybody may use the content following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.