Computational analysis in Influenza virus

Abstract

Influenza viruses are major human pathogens accountable for respiratory diseases affecting millions of people worldwide and characterized by high morbidity and significant mortality. Influenza infections can be controlled by vaccination and antiviral drugs. However, vaccines need yearly updating and give limited protection. In addition, the currently available drugs suffer from the rapid and extensive emergence of drug resistance. All this highlights the urgent need for developing new antiviral strategies with novel mechanisms of action and with reduced drug resistance potential. Recent advances in the understanding of Influenza virus replication have discovered a number of cellular drug targets that counteract viral drug resistance. With expanded bioinformatics' knowledge on computational modeling and molecular dynamic stimulations, novel small molecule inhibitors of herbal/ayurvedic origin are being explored due to their non-toxicity and affordability. Using in-silico techniques the structural details and information of influenza protein have been studied to identify the potential drugs for inhibition. Further, we have discussed the various computational studies carried out on major protein/targets of Influenza which could provide new clues for a newer class of antiviral (ayurvedic) drugs. In the years to come ahead, the influenza treatment will go through major changes, with advancing our knowledge of pathogenesis as new methods becoming clinically validated.