MOLECULAR MODELLING AND LEAD DESIGN OF SUBSTITUTED ZANAMIVIR DERIVATIVES AS POTENT ANTI-INFLUENZA DRUGS

Abstract

Influenza virus spreads infection via two main surface glycoproteins namely Hemagglutinin (HA) and Neuraminidase (NA). NA cleaves the sialic acid receptors eventually releasing newly formed virus particles. These released viral particles then invades new cells. Inhibition of NA could limit the infection to one round of replication of virus which is not enough to cause the disease. In this study, novel series of acylguanidine zanamivir derivatives were used to develop a Group-based QSAR (GQSAR) model targeting NA in different strains of influenza virus viz.H1N1 and H3N2. Unlike other traditional QSAR approaches, GQSAR gives the flexibility to study fragments within a molecule and its contribution in the inhibitory effect of the compound. A correlation analysis was carried out comparing the statistics of the measured IC50 values with the predicted ones. The descriptors were interpreted graphically. A combinatorial library was developed, activities of the compound were predicted using these GQSAR models and docking study was performed on the top scoring compounds. Docking study revealed the binding orientation of these inhibitors at the active site of NA (150-loop). The top compound (AMA) was selected for carrying out molecular dynamics simulations for 15ns which provided insights into the time dependent dynamics of the designed leads. AMA possessed a docking score of -8.26 Kcal/mol with H1N1 strain and -7.00 Kcal/mol with H3N2 strain. Ligandbound complexes of both H1N1 and H3N2 were observed to be stable for 11 ns and 7 ns respectively. In addition, absorption, distribution, metabolism and excretion (ADME) descriptors were also determined to evaluate their pharmacokinetic properties. These studies provide valuable insight for designing more potent and selective inhibitors for the treatment of Influenza.