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Short Communication

InSilico Discovery of Non-Psychoactive Scaffolds in Cannabis Halting SARS-CoV-2 Host Entry and Replication Machinery

ORCID Icon & ORCID Icon
Pages 367-386 | Received 25 Oct 2021, Accepted 17 Mar 2022, Published online: 04 Apr 2022
 

Abstract

Aim: Coronavirus disease still poses a global health threat which advocates continuous research efforts to develop effective therapeutics. Materials & methods: We screened out an array of 29 Cannabis phytoligands for their viral spike-ACE2 complex and main protease (Mpro) inhibitory actions by in silico modeling to explore their possible dual viral entry and replication machinery inhibition. Physicochemical and pharmacokinetic parameters (ADMET) formulating drug-likeness were computed. Results: Among the studied phytoligands, cannabigerolic acid (2), cannabigerol (8), and its acid methyl ether (3) possessed the highest binding affinities to SARS-CoV-hACE2 complex essential for viral entry. Canniprene (24), cannabigerolic methyl ether (3) and cannabichromene (9) were the most promising Mpro inhibitors. Conclusion: These non-psychoactive cannabinoids could represent plausible therapeutics with added-prophylactic value as they halt both viral entry and replication machinery.

Graphical abstract

Author contributions

A Khattab: conceptualization, methodology, writing – original draft preparation; M Teleb: methodology, software, formal analysis, data curation. All authors read and approved the final manuscript.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

Availability of data & material

Data sharing is not applicable to this article because no datasets were generated or analyzed in this study.

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