Searching possible SARS-CoV-2 main protease inhibitors in constituents from herbal medicines using in silico studies

Abstract

The largest threat to civilization since the Second World War is the spread of the new coronavirus disease (COVID-19). Therefore, there is an urgent need for innovative therapeutic medicines to treat COVID-19. Reusing bio-actives is a workable and efficient strategy in the battle against new epidemics because the process of developing new drugs is time-consuming. This research aimed to identify which herbal remedies had the highest affinity for the receptor and assess a variety of them for potential targets to suppress the SARS-CoV-2 M^pro. The use of AutoDock Vina for structure-based virtual screening was done first due to the importance of protein interactions in the development of drugs. Molecular docking was used in the comparative study to assess 89 different chemicals from medicinal herbs. To anticipate their effectiveness against the primary protease of SARS-CoV-2, more analysis was done on the ADMET profile, drug-likeness, and Lipinski’s rule of five. The next step involved three replicas of 100 ns-long molecular dynamics simulations on the potential candidates, which were preceded by calculations of the binding free energy of MM-GBSA. The outcomes showed that Achyrodimer A, Cinchonain Ib, Symphonone F, and Lupeol acetate all performed well and had the highest 6LU7 binding affinities. Using RMSD, RMSF, and protein-ligand interactions, the stability of the protein-ligand complex was assessed. The studies indicate that bioactive substances obtained from herbal medicines may function as a COVID-19 therapeutic agent, necessitating additional wet lab research to confirm their therapeutic potential, efficacy, and pharmacological capacity against the condition.

Communicated by Ramaswamy H. Sarma

KEYWORDS:

• SARS-CoV-2 m^pro
• herbal medicine
• ADMET
• molecular docking
• molecular dynamics

Acknowledgements

The authors thank the Research Directorate for their support through the DIREG project 03/2020.

Authors’ contributions

All authors have contributed equally. Conceptualization: Hezha O. Rasul, Guillermo Salgado M; Data curation: Dlzar D. Ghafour, Noel Vinay Thomas; Software: Dlzar D. Ghafour; Resources: Noel Vinay Thomas, Lorena Gerli Candia, Guillermo Salgado M; Formal Analysis: Bakhtyar K. Aziz, Lorena Gerli Candia; Methodology: L. H. Mendoza-Huizar, Dlzar D. Ghafour; Supervision: Hezha O. Rasul, L. H. Mendoza-Huizar; Validation: Bakhtyar K. Aziz, Lorena Gerli Candia, Guillermo Salgado M; Writing review & editing: Hezha O. Rasul, Noel Vinay Thomas, Bakhtyar K. Aziz

Disclosure statement

No potential conflicts of interest were declared by the authors.

Ethical approval

None of the authors of this paper conducted any studies using human subjects or animals.

Data availability statement

The supplementary information files contain all data generated during this investigation.

Additional information

Funding

This work was supported by the Universidad Católica de la Santísima Concepción.