Computational analysis and modeling the effectiveness of ‘Zanamivir’ targeting neuraminidase protein in pandemic H1N1 strains

Abstract

Antigenic drift causes number of mutations in neuraminidase protein of H1N1 swine influenza virus. We analyzed neuraminidase mutations in H1N1 strains distributed over six continents, at both the sequence and structural level. Mutations in the nearby residues of the drug binding site play crucial role in the binding affinity of the drug with the protein. For this purpose, mutant models were generated for the neuraminidase protein from 34 pandemic H1N1 isolates and docking were performed with zanamivir drug. Multiple sequence alignment (MSA) and variations in docking score suggest that there are considerable changes in the binding affinity of neuraminidase with zanamivir, which leads to probable ineffectiveness of zanamivir in the isolated samples of pandemic H1N1 collected from quite a few countries. To further evaluate the effectiveness of the antiviral drugs, we derived, calibrated and analyzed an ordinary differential equations based mathematical model for H1N1 infection dynamics and drug mediated virus deactivation.