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Letters in Drug Design & Discovery

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ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

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Research Article

Sequence Analysis, Structure Prediction of Receptor Proteins and In Silico Study of Potential Inhibitors for Management of Life Threatening COVID-19

Author(s): Hriday Kumar Basak, Soumen Saha, Joydeep Ghosh, Uttam Paswan, Sujoy Karmakar, Ayon Pal and Abhik Chatterjee*

Volume 19, Issue 2, 2022

Published on: 04 August, 2021

Page: [108 - 122] Pages: 15

DOI: 10.2174/1570180818666210804141613

Price: $65

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Abstract

Background: Treatment of the Covid-19 pandemic caused by the highly contagious and pathogenic SARS-CoV-2 is a global menace. Day by day, this pandemic is getting worse. Doctors, scientists and researchers across the world are urgently scrambling for a cure for novel corona virus and continuously working at break neck speed to develop vaccines or drugs. But to date, there are no specific drugs or vaccines available in the market to cope up with the virus.

Objective: The present study helps us to elucidate 3D structures of SARS-CoV-2 proteins and also to identify natural compounds as potential inhibitors against COVID-19.

Methods: The 3D structures of the proteins were constructed using Modeller 9.16 modeling tool. Modelled proteins were validated with PROCHECK by Ramachandran plot analysis. In this study, a small library of natural compounds (fifty compounds) was docked to the hACE2 binding site of the modelled surface glycoprotein of SARS-CoV-2 using AutoDock Vina to repurpose these inhibitors against SARS-CoV-2. Conceptual density functional theory calculations of the best eight compounds had been performed by Gaussian-09. Geometry optimizations for these molecules were done at M06-2X/ def2-TZVP level of theory. ADME parameters, pharmacokinetic properties and drug likeness of the compounds were analyzed using swissADME website.

Results: In this study, we analysed the sequences of surface glycoprotein, nucleocapsid phosphoprotein and envelope protein obtained from different parts of the globe. We modelled all the different sequences of surface glycoprotein and envelop protein in order to derive 3D structure of a molecular target, which is essential for the development of therapeutics. Different electronic properties of the inhibitors have been calculated using DFT through M06-2X functional with def2-TZVP basis set. Docking result at the hACE2 binding site of all modelled surface glycoproteins of SARSCoV- 2 showed that all the eight inhibitors (actinomycin D, avellanin C, ichangin, kanglemycin A, obacunone, ursolic acid, ansamiotocin P-3 and isomitomycin A) studied here were many folds better compared to hydroxychloroquine which has been found to be effective to treat patients suffering from COVID-19. All the inhibitors meet most of the criteria of drug likeness assessment.

Conclusion: We expect that eight compounds (actinomycin D, avellanin C, ichangin, kanglemycin A, obacunone, ursolic acid, ansamiotocin P-3 and isomitomycin A) can be used as potential inhibitors against SARS-CoV-2.

Keywords: COVID-19, SARS-CoV-2, hACE2, density functional theory, docking, potential inhibitors.

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