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Express Communication

Dual inhibitors of SARS-CoV-2 proteases: pharmacophore and molecular dynamics based drug repositioning and phytochemical leads

ORCID Icon, ORCID Icon, , , ORCID Icon & ORCID Icon
Pages 6324-6337 | Received 10 Jun 2020, Accepted 01 Jul 2020, Published online: 22 Jul 2020
 

Abstract

SARS-related coronaviruses poses continual threat to humanity by rapidly mutating and emerging as severe pandemic outbreaks, including the current nCoV-19 pandemic. Hence a rapid drug repositioning and lead identification strategy are required to mitigate these outbreaks. We report a pharmacophore and molecular dynamics-based approach for drug repositioning and lead identification against dual targets (3CLp and PLp) of SARS-CoV-2. The pharmacophore model of 3CLp inhibitors was apolar with two aromatic and two H-bond acceptors, whereas that of PLp was relatively polar, bearing one aromatic and three H-bond acceptors. Pharmacophore-based virtual screening yielded six existing FDA-approved drugs and twelve natural products with both the pharmacophoric features. Among them are nelfinavir, tipranavir and licochalcone-D, which has shown better binding characteristics with both the proteases compared to lopinavir. The molecular dynamics revealed that the connecting loop (residues 176–199) of 3CLp is highly flexible, and hence, inhibitors should avoid high-affinity interactions with it. Lopinavir, due to its high affinity with the loop region, exhibited unstable binding. Further, the van der Waals size of the 3CLp inhibitors positively correlated with their binding affinity with 3CLp. However, the van der Waals size of a ligand should not cross a threshold of 572Å3, beyond which the ligands are likely to make high-affinity interaction with the loop and suffer unstable binding as observed in the case of lopinavir. Similarly, the total polar surface area of the ligands were found to be negatively correlated with their binding affinity with PLp.

Communicated by Ramaswamy H. Sarma

Graphical Abstract

Acknowledgements

The authors thank the computational facility at the COSMOS lab of CRIF, Sri Sathya Sai Institute of Higher Learning, for providing computational facilities to carry out the work.

Disclosure statement

None to declare.

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