Homology Modelling and Molecular Docking Studies of Spike Protein in SARS-CoV-2

ABSTRACT: The COVID-19 pandemic, caused by SARS-CoV-2, has posed substantial global health challenges, highlighting the urgent need for effective antiviral treatments. This study utilizes homology and molecular docking to identify potential natural compound inhibitors targeting the SARS-CoV-2 spike protein. The spike protein sequence was sourced from the Swiss-Prot database and modeled using MODELLER 10.3, employing templates from the Protein Data Bank (PDB). The constructed model underwent validation via Ramachandran plot analysis and MolProbity scores, confirming its reliability for subsequent analyses. Virtual screening of database was performed using AutoDock Vina. Compounds exhibiting the highest binding affinities were subjected to MD simulations to evaluate their stability. Tetrandrine (L1) and Tubocurarine (L2) emerged as the top candidates, with Tetrandrine demonstrating the lowest binding energy and the best fit. The ADMET properties of these compounds were assessed using SwissADME, affirming their drug-like potential. Molecular dynamics simulations further substantiated the stability of the Tetrandrine-spike protein complex, revealing significant interactions. This study identifies Tetrandrine as a promising inhibitor of SARS-CoV-2, warranting further exploration for antiviral drug development.