3D-QSAR, homology modelling of influenza hemagglutinin receptor (StrainA/WS/1933), molecular dynamics, DFT, and ADMET studies for newly designed inhibitors

Abstract

Influenza pandemic cases are related to high morbidity and mortality rates due to the genetic variability of the influenza strains. This necessitated the need for the search and discovery of more potential anti-influenza agents to avert future outbreaks. The 3D-QSAR studies were built through comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The results showed CoMFA (Rtrain2 = 0.98, Q2 = 0.58) and CoMSIA (Rtrain2 0.96, Q2 = 0.54) models for reliable activity predictions. Using the worthy information obtained from the field contributors of the 3D-QSAR models and the molecular docking studies of the most active compound 4 (template 4), nine (9) compounds were designed (4a-i) with better potency as compared with a reference drug (arbidol). The dynamic stability of the bound ligand (4d) in the binding site of the modelled protein was further justified through molecular dynamics simulations for up to 100 ns. Moreover, the quantum chemical and drug-likeness parameters of the designed compounds predicted good chemical reactivity and pharmacokinetic profiles respectively. Hence, the outcome of this study recommends the development and bioassay testing of these newly designed compounds through in vitro and in-vivo analysis.