Virtual screening of bioactive anti-SARS-CoV natural products and identification of 3β,12-diacetoxyabieta-6,8,11,13-tetraene as a potential inhibitor of SARS-CoV-2 virus and its infection related pathways by MD simulation and network pharmacology

Abstract

Since the first prevalence of COVID-19 in 2019, it still remains the most devastating pandemic throughout the world. The current research aimed to find potential natural products to inhibit the novel coronavirus and associated infection by MD simulation and network pharmacology approach. Molecular docking was performed for 39 natural products having potent anti-SARS-CoV activity. Five natural products showed high binding interaction with the viral main protease for the SARS-CoV-2 virus, where 3β,12-diacetoxyabieta-6,8,11,13 tetraene showed stable binding in MD simulation until 100 ns. Both 3β,12-diacetoxyabieta-6,8,11,13 tetraene and tomentin A targeted 11 common genes that are related to COVID-19 and interact with each other. Gene ontology development analysis further showed that all these 11 genes are attached to various biological processes. The KEGG pathway analysis also showed that the proteins that are targeted by 3β,12-diacetoxyabieta-6,8,11,13 tetraene and tomentin A are associated with multiple pathways related to COVID-19 infection. Furthermore, the ADMET and MDS studies reveals 3β,12-diacetoxyabieta-6,8,11,13 as the best-suited compound for oral drug delivery.

Communicated by Ramaswamy H. Sarma

Keywords:

• COVID-19
• docking
• ADMET
• natural products
• MD simulation
• network pharmacology

Acknowledgments

The authors would like to express their appreciation to Universiti Kebangsaan Malaysia (UKM) for giving the Discovery Studio 3.1 software.

Authors’ contributions

AKMMH conceived the idea, outlined the research strategy, partially performed the Drug-likeness test, drafted the manuscript, MR & MFFMA performed the docking and ADMET study and drafted the manuscript, SUK, TTH and SI resourcing and performed molecular dynamic simulation and thermodynamic studies, MNU performed the Network Pharmacology study. AAB and MAB critically reviewed and edited the manuscript. SNT acquired fund, supervised the work and finalized the manuscript. ZAZ proofread and edited the manuscript. The final manuscript was reviewed and approved by all authors.

Data availability statement

The compound-gene interaction generated during the current study is available in the SwissTargetPrediction tool (http://www.swisstargetprediction.ch/). In addition, we retrieved COVID-19 and SARS-CoV-2 associated genes from the NCBI-Gene database for humans (https://www.ncbi.nlm.nih.gov/). Moreover, we used the search tool for the retrieval of interacting genes (STRING) database (https://string-db.org/cgi/input.pl; STRING-DB v11.0) for identifying the PPI.

Disclosure statement

The authors have no conflict of interest.

This work was supported by the Lembaga Koko Malaysia (Malaysian Cocoa Board) (Grant Number: RDU 210710) and the Fundamental Research Grant Scheme (Reference Number:FRGS/1/2021/STG01/UPM/02/3) awarded by the Ministry of Higher Education, Malaysia.