Bioinformatics Prediction of Potential Inhibitors For the SARS-CoV-2 NTPase/Helicase Using Molecular Docking and Dynamics Simulation From Organic Phenolic Compounds

Background: Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a disorder with human-to-human rapid transmission. With several vaccines introduced, we need to find out the effectiveness of such medications in a short-period therapeutic procedure. The NTPase/helicase plays a key role in the replication of the viral RNA.Materials and Methods: We estimated the binding affinity of several natural polyphenolics, commonly found in fruits and vegetables, with the catalytic site of SARS-CoV-2 helicase by molecular docking analysis using the AutoDock tool. The stability of connections between top-ranked components inside the catalytic site of the helicase was evaluated by molecular dynamics (MD) simulations. The most active residues within the catalytic site of the helicase were ranked based on their degree in a phenolic-residue interaction (PRI) network.Results: Amentoflavone, theaflavin 3'-gallate, and procyanidin were estimated to be the most potential effective SARS-CoV-2 helicase inhibitors with the salient inhibition constant value (Ki) at the picomolar scale. The docked pose of these compounds was also found to be stable after MD simulations. The binding energy of these compounds with the helicase catalytic site was estimated between −13.90 and −12.77 kcal/mol. Asp534 and Leu412 demonstrated more degrees in the PRI network compared to the other residues.Conclusion: The present study predicts that amentoflavone, theaflavin 3'-gallate, and procyanidin might be helpful for the treatment of COVID-19.

Bioinformatics Prediction of Potential Inhibitors For the SARS-CoV-2 NTPase/Helicase Using Molecular Docking and Dynamics Simulation From Organic Phenolic Compounds Keywords:

COVID-19 , Helicase , Inhibitor , Molecular docking , SARS-CoV-2