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

• Authors: Carlos Polanco , Thomas Buhse , Jorge Castañón-González , José Samaniego
• Languages of publication: EN

Abstracts

EN

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.

Keywords

EN

Polarity Index Method; influenza A virus subtype H1N1; drug design; QSAR method

• Publisher: Polish Biochemical Society
• Journal: Acta Biochimica Polonica
• Year: 2014
• Volume: 61
• Issue: 4
• Pages: 693-698

Dates

published

2014

received

2013-05-21

revised

2014-04-04

accepted

2014-06-12

(unknown)

2014-11-07

Contributors

author

Carlos Polanco

• Facultad de Ciencias de la Salud, Universidad Anáhuac, Col. Lomas Anáhuac, Huixquilucan Estado de México, México

author

Thomas Buhse

• Centro de Investigaciones Químicas, Universidad Autónoma del Estado de Morelos, Cuernavaca Morelos, México

author

Jorge Castañón-González

• Facultad de Ciencias de la Salud, Universidad Anáhuac, Col. Lomas Anáhuac, Huixquilucan Estado de México, México

author

José Samaniego

• Facultad de Ciencias de la Salud, Universidad Anáhuac, Col. Lomas Anáhuac, Huixquilucan Estado de México, México

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