Natural-like products as potential SARS-CoV-2 Mproinhibitors:in-silicodrug discovery

In December 2019, a COVID-19 epidemic was discovered in Wuhan, China, and since has disseminated around the world impacting human health for millions. Herein,in-silicodrug discovery approaches have been utilized to identify potential natural products (NPs) as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) main protease (M-pro) inhibitors. The MolPort database that contains over 100,000 NPs was screened and filtered using molecular docking techniques. Based on calculated docking scores, the top 5,000 NPs/natural-like products (NLPs) were selected and subjected to molecular dynamics (MD) simulations followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. Combined 50 ns MD simulations and MM-GBSA calculations revealed nine potent NLPs with binding affinities (Delta G(binding)) > -48.0 kcal/mol. Interestingly, among the identified NLPs, four bis([1,3]dioxolo)pyran-5-carboxamide derivatives showed Delta G(binding)> -56.0 kcal/mol, forming essential short hydrogen bonds with HIS163 and GLY143 amino acids via dioxolane oxygen atoms. Structural and energetic analyses over 50 ns MD simulation demonstrated NLP-M(pro)complex stability. Drug-likeness predictions revealed the prospects of the identified NLPs as potential drug candidates. The findings are expected to provide a novel contribution to the field of COVID-19 drug discovery. Communicated by Ramaswamy H. Sarma

Automated summary

The study utilized in-silico drug discovery approaches to identify nine potent natural-like products as potential inhibitors of SARS-CoV-2 main protease. Among these, four derivatives showed high binding affinities and stability in MD simulations, indicating their potential as drug candidates for COVID-19.