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In silico identification of a potent arsenic based lead drug di-phenyl phenoxy roxarsone against SARS-CoV-2

Authors: Trinath Chowdhury; Joyita Dutta; Santi M. Mandal; Gourisankar Roymahapatra;

In silico identification of a potent arsenic based lead drug di-phenyl phenoxy roxarsone against SARS-CoV-2

Abstract

Central Research Facility, Indian Institute of Technology Kharagpur, Kharagpur-721 302, West Bengal, India School of Applied Science and Humanities, Haldia Institute of Technology, Haldia-721 657, West Bengal, India E-mail:grm.chem@gmail.com, gourisankar1978@gmail.com Manuscript received online 20 July 2020, accepted 30 July 2020 In this article we have tried to address the plausible identification of a novel lead drug molecule against COVID-19. Nine different arsenic (As) based molecules, roxarsone derivatives were designed and optimized for computational analysis to determine its binding affinity against SARS-CoV-2. The molecules were screened based on their chemical reactivity with respect to conceptual density functional theory (CDFT) and global reactivity descriptors. The screened molecules were docked blindly against RNA dependent RNA polymerase (RdRp) using molecular docking software iGEMDOCK v2.1. On the basis of idock score in their respective catalytic domain, di-phenyl phenoxy roxarsone identified as promising inhibitor against SARS-CoV-2 with binding free energy calculated as –86.8 kcal/mol. Site specific docking was also executed with target site, receptor binding domain (RDB) of spike glycoprotein of SARS-CoV-2 whose structure was computationally designed using Phyre2 server. The interaction study of RDB with di-phenyl phenoxy roxarsone revealed a binding energy –133.3 kcal/mol. Thus it can be concluded from the above in silico experiment that screening of potential arsenic based roxarsone derivative would help in development of new therapeutic drug for COVID-19.

Keywords

in silico experiment, Drug molecule design, COVID-19, di-phenyl phenoxy roxarsone

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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