s Anti-COVID-19 Sulfonamides: A DFT, Docking and ADMET Study

Background: The development of a specific curative drug or prophylactic and vaccine is urgently required to cure COVID-19. Sulfonamide and its derivatives are famous for their multifaceted antibiotic and antiviral activities against verities of a pathogen. Objective: The objective of this study is to find new potential molecules for COVID-19 treatment. We tested some sulfonamide molecules (including antiviral compounds) as SARS CoV-2 M^pro inhibitors. Methods: In this study, the Density Functional Theory (DFT) and Docking study have been utilized for protein-small molecule affinity prediction. The SwissADME server was used for pharmacokinetics and drug-like likeness prediction, and the Pred-hERG server was employed for cardiotoxicity prediction. Results: In this study, sixteen sulfonamides have been investigated in silico, with a perspective to obtaining a potential anti-covid compound. The sulfonamides have been subjected to molecular docking with SARS CoV-2 M^pro, mainly responsible for viral infection and replication. We discover the molecular flexibility and charge distribution profoundly affecting the binding of the compounds to the protein. Moderately flexible (six rotatable bond) and less polar (sufficient hydrophobic) sulfonamide are favorable for strong binding with the enzyme. Here, the bioavailability properties like adsorption, distribution, metabolism, excretion, pharmacokinetics, and potential toxicity of these compounds have also been checked. Conclusion: Low cardio-toxicity and high bioavailability make these sulfonamides a good anti- COVID-19 drug option. The sulfonamide 16 was found to be the best.