Cell Biochemistry and Biophysics

, Volume 70, Issue 2, pp 1469–1477 | Cite as

Polar Profile of Antiviral Peptides from AVPpred Database

  • Carlos Polanco
  • José Lino Samaniego
  • Jorge Alberto Castañón-González
  • Thomas Buhse
Original Paper

Abstract

Diseases of viral origin in humans are among the most serious threats to health and the global economy. As recent history has shown the virus has a high pandemic potential, among other reasons, due to its ability to spread by air, hence the identification, investigation, containment, and treatment of viral diseases should be considered of paramount importance. In this sense, the bioinformatics research has focused on finding fast and efficient algorithms that can identify highly toxic antiviral peptides and to serve as a first filter, so that trials in the laboratory are substantially reduced. The work presented here contributes to this effort through the use of an algorithm already published by this team, called polarity index method, which identifies with high efficiency antiviral peptides from the exhaustive analysis of the polar profile, using the linear sequence of the peptide. The test carried out included all peptides in APD2 Database and 60 antiviral peptides identified by Kumar and co-workers (Nucleic Acids Res 40:W199–204, 2012), to build its AVPpred algorithm. The validity of the method was focused on its discriminating capacity so we included the 15 sub-classifications of both Databases.

Keywords

Polarity index method Antiviral peptides AVPpred algorithm 

Abbreviations

SCAAP

Selective cationic amphipathic antibacterial peptides

APD2

Antimicrobial peptide database http://aps.unmc.edu/AP/ [1] accessed December 19, 2012. AVPpred, http://crdd.osdd.net/servers/avppred [2] accessed March 10, 2013

QSAR

Quantitative structure activity relationships

SVM

Support vector machine

SARS

Severe acute respiratory syndrome

HIV

Human immunodeficiency virus

AAindex

Amino acid indices, substitution matrices and pair-wise contact potentials database http://www.genome.jp/aaindex/ [3] accessed March 10, 2013

Supplementary material

12013_2014_84_MOESM1_ESM.gz (3.6 mb)
Supplementary material 1 (GZ 3700 kb)
12013_2014_84_MOESM2_ESM.gz (3.6 mb)
Supplementary material 2 (GZ 3700 kb)

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Carlos Polanco
    • 1
    • 2
  • José Lino Samaniego
    • 1
    • 2
  • Jorge Alberto Castañón-González
    • 1
  • Thomas Buhse
    • 3
  1. 1.Facultad de Ciencias de la SaludUniversidad AnáhuacHuixquilucanMexico
  2. 2.Departamento de Matemáticas, Facultad de CienciasUniversidad Nacional Autónoma de MéxicoMexicoMexico
  3. 3.Centro de Investigaciones QuímicasUniversidad Autónoma del Estado de MorelosCuernavacaMexico

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