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Research Articles

Virtual repurposing of ursodeoxycholate and chenodeoxycholate as lead candidates against SARS-Cov2-Envelope protein: A molecular dynamics investigation

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Pages 5147-5158 | Received 18 Aug 2020, Accepted 18 Dec 2020, Published online: 31 Dec 2020
 

Abstract

Drug repurposing is an apt choice to combat the currently prevailing global threat of COVID-19, caused by SARS-Cov2in absence of any specific medication/vaccine. The present work employs state of art computational methods like homology modelling, molecular docking and molecular dynamics simulations to evaluate the potential of two widely used surfactant drugs namely chenodeoxycholate(CDC) and ursodeoxycholate (UDC), to bind to the envelope protein of SARS-Cov2(SARS-Cov2-E).The monomeric unit of SARS-Cov2-E was modelled from a close homologue (>90% sequence identity) and a pentameric assembly was modelled using symmetric docking, followed by energy minimization in a DPPC membrane environment. The minimized structure was used to generate best scoring SARS-Cov2-E–CDC/UDC complexes through blind docking. These complexes were subjected to 230 ns molecular dynamics simulations in triplicates in a DPPC membrane environment. Comparative analyses of structural properties and molecular interaction profiles from the MD trajectories revealed that, both CDC and UDC could stably bind to SARS-Cov2-E through H-bonds, water-bridges and hydrophobic contacts with the transmembrane-channelresidues.T30 was observed to be a key residue for CDC/UDC binding. CDC/UDC binding affected the H-bonding pattern between adjacent monomeric chains, slackening the compact transmembrane region of SARS-Cov2-E. Additionally, the polar functional groups of CDC/UDC facilitated entry of a large number of water molecules into the channel. These observations suggest CDC/UDC as potential candidates to hinder the survival of SARS-Cov2 by disrupting the structure of SARS-Cov2-E and facilitating the entry of solvents/polar inhibitors inside the viral cell.

Communicated by Ramaswamy H. Sarma

Graphical abstract

Acknowledgements

CC thanks the Department of Science and Technology for financial assistance in the form of DST-INSPIRE Faculty award (IFA16-LSBM-170) and Schrodinger for providing short term licenses for some of the modules. RY acknowledges the Council of Scientific and Industrial Research, India for providing financial support in the form of Junior Research Fellowship.

Disclosure statement

The authors declare that there is no conflict of interest

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