Computational drug re-purposing targeting the spike glycoprotein of SARS-CoV-2 as an effective strategy to neutralize COVID-19.

COVID-19 has intensified into a global pandemic with over a million deaths worldwide. Experimental research analyses have been implemented and executed with the sole rationale to counteract SARS-CoV-2, which has initiated potent therapeutic strategy development in coherence with computational biology validation focusing on the characterized viral drug targets signified by proteomic and genomic data. Spike glycoprotein is one of such potential drug target that promotes viral attachment to the host cellular membrane by binding to its receptor ACE-2 via its Receptor-Binding Domain (RBD). Multiple Sequence alignment and relative phylogenetic analysis revealed significant sequential disparities of SARS-CoV-2 as compared to previously encountered SARS-CoV and MERS-CoV strains. We implemented a drug re-purposing approach wherein the inhibitory efficacy of a cluster of thirty known drug candidates comprising of antivirals, antibiotics and phytochemicals (selection contingent on their present developmental status in underway clinical trials) was elucidated by subjecting them to molecular docking analyses against the spike protein RBD model (developed using homology modelling and validated using SAVES server 5.0) and the composite trimeric structures of spike glycoprotein of SARS-CoV-2. Our results indicated that Camostat, Favipiravir, Tenofovir, Raltegravir and Stavudine showed significant interactions with spike RBD of SARS-CoV-2. Proficient bioavailability coupled with no predicted in silico toxicity rendered them as prospective alternatives for designing and development of novel combinatorial therapy formulations for improving existing treatment regimes to combat COVID-19.