AVPpred: collection and prediction of highly effective antiviral peptides

In the battle against viruses, antiviral peptides (AVPs) had demonstrated the immense potential. Presently, more than 15 peptide-based drugs are in various stages of clinical trials. Emerging and re-emerging viruses further emphasize the efforts to accelerate antiviral drug discovery efforts. Despite, huge importance of the field, no dedicated AVP resource is available. In the present study, we have collected 1245 peptides which were experimentally checked for antiviral activity targeting important human viruses like influenza, HIV, HCV and SARS, etc. After removing redundant peptides, 1056 peptides were divided into 951 training and 105 validation data sets. We have exploited various peptides sequence features, i.e. motifs and alignment followed by amino acid composition and physicochemical properties during 5-fold cross validation using Support Vector Machine. Physiochemical properties-based model achieved maximum 85% accuracy and 0.70 Matthew’s Correlation Coefficient (MCC). Performance of this model on the experimental validation data set showed 86% accuracy and 0.71 MCC which is far better than the general antimicrobial peptides prediction methods. Therefore, AVPpred—the first web server for predicting the highly effective AVPs would certainly be helpful to researchers working on peptide-based antiviral development. The web server is freely available at http://crdd.osdd.net/servers/avppred.

[1]  Suzana Popovic,et al.  Peptides with antimicrobial and anti-inflammatory activities that have therapeutic potential for treatment of acne vulgaris , 2012, Peptides.

[2]  Charles Elkan,et al.  Fitting a Mixture Model By Expectation Maximization To Discover Motifs In Biopolymer , 1994, ISMB.

[3]  Guillaume Castel,et al.  Phage Display of Combinatorial Peptide Libraries: Application to Antiviral Research , 2011, Molecules.

[4]  G. Schneider,et al.  Designing antimicrobial peptides: form follows function , 2011, Nature Reviews Drug Discovery.

[5]  K. Chou,et al.  Prediction of Antimicrobial Peptides Based on Sequence Alignment and Feature Selection Methods , 2011, PloS one.

[6]  Karl Frank,et al.  High-performance signal peptide prediction based on sequence alignment techniques , 2008, Bioinform..

[7]  Hiroyuki Ogata,et al.  AAindex: Amino Acid Index Database , 1999, Nucleic Acids Res..

[8]  Shijian Zhang,et al.  Inhibition of Influenza Virus Replication by Constrained Peptides Targeting Nucleoprotein , 2011, Antiviral chemistry & chemotherapy.

[9]  B. Brandsdal,et al.  Altered activity and physicochemical properties of short cationic antimicrobial peptides by incorporation of arginine analogues. , 2009, Molecular pharmaceutics.

[10]  Mikael Bodén,et al.  MEME Suite: tools for motif discovery and searching , 2009, Nucleic Acids Res..

[11]  Manoj Kumar,et al.  VIRsiRNAdb: a curated database of experimentally validated viral siRNA/shRNA , 2011, Nucleic Acids Res..

[12]  J. Drummond,et al.  Design and optimization of a multiplex anti-influenza peptide immunoassay. , 2008, Journal of immunological methods.

[13]  K. Brogden Antimicrobial peptides: pore formers or metabolic inhibitors in bacteria? , 2005, Nature Reviews Microbiology.

[14]  Ashish,et al.  Antiviral Peptides Targeting the West Nile Virus Envelope Protein , 2006, Journal of Virology.

[15]  Saheli Sadanand Vaccination: The Present and the Future , 2011, The Yale journal of biology and medicine.

[16]  Xia Li,et al.  APD2: the updated antimicrobial peptide database and its application in peptide design , 2008, Nucleic Acids Res..

[17]  D. Lambert,et al.  Peptides from conserved regions of paramyxovirus fusion (F) proteins are potent inhibitors of viral fusion. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[18]  FrankKarl,et al.  High-performance signal peptide prediction based on sequence alignment techniques , 2008 .

[19]  Gajendra P. S. Raghava,et al.  AntiBP2: improved version of antibacterial peptide prediction , 2010, BMC Bioinformatics.

[20]  K. Kavanagh,et al.  Histatins: antimicrobial peptides with therapeutic potential , 2004, The Journal of pharmacy and pharmacology.

[21]  T. Narumi,et al.  Conjugation of cell-penetrating peptides leads to identification of anti-HIV peptides from matrix proteins. , 2012, Bioorganic & medicinal chemistry.

[22]  P. Legrain,et al.  Antiviral Drug Discovery Strategy Using Combinatorial Libraries of Structurally Constrained Peptides , 2004, Journal of Virology.

[23]  Gajendra P. S. Raghava,et al.  AlgPred: prediction of allergenic proteins and mapping of IgE epitopes , 2006, Nucleic Acids Res..

[24]  Shreyas Karnik,et al.  CAMP: a useful resource for research on antimicrobial peptides , 2009, Nucleic Acids Res..

[25]  R. Frank,et al.  Identification of High-Affinity PB1-Derived Peptides with Enhanced Affinity to the PA Protein of Influenza A Virus Polymerase , 2010, Antimicrobial Agents and Chemotherapy.

[26]  C. Brandt,et al.  Multiple Peptides Homologous to Herpes Simplex Virus Type 1 Glycoprotein B Inhibit Viral Infection , 2008, Antimicrobial Agents and Chemotherapy.

[27]  Mark E. Shirtliff,et al.  Antimicrobial Peptides: Primeval Molecules or Future Drugs? , 2010, PLoS pathogens.

[28]  Jeremy C. Jones,et al.  Identification of the Minimal Active Sequence of an Anti-Influenza Virus Peptide , 2011, Antimicrobial Agents and Chemotherapy.

[29]  Marc Torrent,et al.  Connecting Peptide Physicochemical and Antimicrobial Properties by a Rational Prediction Model , 2011, PloS one.

[30]  R. Hancock,et al.  Peptide Antimicrobial Agents , 2006, Clinical Microbiology Reviews.

[31]  T. Matthews,et al.  Design of helical, oligomeric HIV-1 fusion inhibitor peptides with potent activity against enfuvirtide-resistant virus , 2007, Proceedings of the National Academy of Sciences.

[32]  Mamoon Rashid,et al.  Support Vector Machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary information and motifs , 2007, BMC Bioinformatics.

[33]  M. García-Delgado,et al.  Peptide Inhibitors of Hepatitis C Virus NS3 Protease , 2003, Antiviral chemistry & chemotherapy.