Int J Mol Sci . Computational Selectivity Assessment of Protease Inhibitors against SARS-CoV-2

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Int J Mol Sci


. 2021 Feb 19;22(4):2065.
doi: 10.3390/ijms22042065.
Computational Selectivity Assessment of Protease Inhibitors against SARS-CoV-2


Andr? Fischer ¹ , Manuel Sellner ¹ , Karolina Mitusi?ska ² , Maria Bz?wka ² , Markus A Lill ¹ , Artur G?ra ² , Martin Smie?ko ¹



Affiliations

• PMID: 33669738
• DOI: 10.3390/ijms22042065

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Abstract

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious global health threat. Since no specific therapeutics are available, researchers around the world screened compounds to inhibit various molecular targets of SARS-CoV-2 including its main protease (M^pro) essential for viral replication. Due to the high urgency of these discovery efforts, off-target binding, which is one of the major reasons for drug-induced toxicity and safety-related drug attrition, was neglected. Here, we used molecular docking, toxicity profiling, and multiple molecular dynamics (MD) protocols to assess the selectivity of 33 reported non-covalent inhibitors of SARS-CoV-2 M^pro against eight proteases and 16 anti-targets. The panel of proteases included SARS-CoV M^pro, cathepsin G, caspase-3, ubiquitin carboxy-terminal hydrolase L1 (UCHL1), thrombin, factor Xa, chymase, and prostasin. Several of the assessed compounds presented considerable off-target binding towards the panel of proteases, as well as the selected anti-targets. Our results further suggest a high risk of off-target binding to chymase and cathepsin G. Thus, in future discovery projects, experimental selectivity assessment should be directed toward these proteases. A systematic selectivity assessment of SARS-CoV-2 M^pro inhibitors, as we report it, was not previously conducted.

Keywords: SARS; coronavirus; protease; selectivity; structure-based design.