An in silico study on phytochemicals from Hibiscus rosa-sinensis as potential inhibitors of SARS-CoV-2 3CLpro
Hibiscus rosa-sinensis has an infinite resource of phytochemicals and emerged as a solution for different health-related issues, such as anti-diabetic, anti-microbial, and wound healing activity, as proved in past clinical studies. COVID-19 remains an ongoing concern, and the struggle to discover effective treatment measures for SARS-CoV-2 has led to a global health catastrophe. The COVID-19 pandemic has exhibited a wave-like progression, encompassing first, second, and third waves, with potential for future resurgences. To effectively halt the transmission of SARS-CoV-2, identifying and targeting a key viral component is critical. One such promising candidate is the 3-chymotrypsin-like protease (3CLpro), also known as the main protease (Mpro). This study aims to investigate the phytochemicals identified in Hibiscus rosa-sinensis flowers for their potential anti-SARS-CoV-2 properties, targeting the 3CLpro, which regulates virus replication and associated pathogenesis. The present research protocol includes molecular docking of 34 phytochemicals identified from the Hibiscus rosa-sinensis flower and targeted against the active site of the 3CLpro. Computational analysis revealed that the top 3 ligands: cyanidin-3-sophoroside-5-glucoside (− 10.9 kcal/mol), 1,2-benzenedicarboxylic acidisodecyl octyl ester (− 10.1 kcal/mol), and rutin (− 9.3 kcal/mol) had better binding affinity to 3CLpro as compared to the control inhibitor remdesivir (− 8 kcal/mol). Further investigation of ligand–protein interaction, physiochemical, ADMET profile, and drug-likeness parameters showed that cyanidin-3-sophoroside-5-glucoside possessed promising properties, indicating its potential as a viable drug candidate against COVID-19.
Authors
- Diptikanta Acharya (ORCID: https://orcid.org/0000-0002-1011-8825)
- Sagarika Satapathy (ORCID: https://orcid.org/0000-0002-6313-9646)
- Ashutosh Kumar (ORCID: https://orcid.org/0000-0002-2623-0416)
- Pritismita Mahalik -
- Subhadeep Das (ORCID: https://orcid.org/0000-0003-2450-971X)
Institutions
- Visva-Bharati University (IN)
- GIET University (IN)
Publication Details
- Journal
- Discover Applied Sciences
- Published
- 2025-10-10
- DOI
- https://doi.org/10.1007/s42452-025-07595-w
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Indian Council of Medical Research