In silico epitope structure prediction for matrix protein of H1N1

By AnupTripathi, Deepesh Kumar, Sachidanand Singh, Atul Kumar, Manitha T. P., Babu Ram, K. Panneerselvam and J. Jannet Vennila

Abstract

H1N1is a current endemic in both human and pig populations and is the cause of Swine flu in humans. Bioinformatics tools enable us to move rapidly from protein sequence to vaccine design. ProPred-I, Rankpep and PeptGen are servers used for identification of epitope with the help of artificial neural network approach. For H1N1 we identified 10 matrix proteins (M1) which are mainly responsible for propagation of H1N1. From ProPred-I,Rankpep and PeptGen conserved 40 epitopes were identified by their selective algorithms and scoring matrices. A virtual library was designed for the 40 epitopes and further it was used for epitope conservancy analysis tool (IEDB) to narrow down the list of putative epitopes to 20 only. A structural library of all conserved putative epitopes was then minimized with Prime Schrodinger module and then ten putative epitopes were designedwith the motto of identifying best virtual vaccine. The pace of vaccine design will accelerate when these in silico results combined with in vitro methods for screening and confirming epitope.

 

Key Words : Capsid Protein, peptide, epitope, matrix protein, H1N1.

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