Computational analysis of drug like candidates against Neuraminidase of Human Influenza A virus subtypes

Abstract

Influenza virus is an enveloped virus having segmented genome, coded by eight (negative-sense) RNA segments. The RNA segments are packed in a nucleocapsid protein. Neuraminidase (NA), an exosialidase, is the major antigen as well as vital virulence factor of the virus and is coded by the 6th segment of RNA. Eleven subtypes of NA are characterized for influenza A and the N1–N9 are divided into two phylogenic groups. NA is an active target for development of potent antivirals or Neuraminidase inhibitors (NAIs), which are reported to interact with multiple conserved residues in the active site of NA resulting in inhibition of virion release and prevention of viral spread to nearby cells. The current computational study focuses on docking of eleven different drug-like molecules including the known NAIs such as oseltamivir and zanamivir against crystal structures of NA of human Influenza A virus subtypes of both phylogenic groups. The docking results of this study indicated that zanamivir was the most active drug candidate against various NA subtypes followed by laninamivir. The study provides insights on interactions as well as cross-reactivity between lead compounds and NA proteins of various influenza subtypes. Observations on the efficacy of these NAIs assessed by the computational study have to be validated through in vitro and in vivo studies for successfully translating them as potential therapeutic agents to treat infection by various subtypes of influenza. Keywords: Influenza A virus, Computational analysis, Docking, Neuraminidase, Antivirals, Drugs