Unlocking antiviral potentials of traditional plants: A multi-method computational study against human metapneumovirus (HMPV)

Amit Dubey; Manish Kumar; Aisha Tufail; Vivek Dhar Dwivedi; Andrea Ragusa

doi:10.1016/j.jiph.2025.102885

Unlocking antiviral potentials of traditional plants: A multi-method computational study against human metapneumovirus (HMPV)

J Infect Public Health. 2025 Jun 27;18(10):102885. doi: 10.1016/j.jiph.2025.102885. Online ahead of print.

Authors

Amit Dubey¹, Manish Kumar², Aisha Tufail³, Vivek Dhar Dwivedi⁴, Andrea Ragusa⁵

Affiliations

¹ Center for Global Health Research, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India. Electronic address: amitdubey@saveetha.com.
² Department of Biochemistry, Iswar Saran Degree College, University of Allahabad (A Constituent PG College of University of Allahabad), Prayagraj, India.
³ Computational Chemistry and Drug Discovery Division, Quanta Calculus, Greater Noida, Uttar Pradesh 201310, India.
⁴ Bioinformatics Research Division, Quanta Calculus, Greater Noida 201310, India.
⁵ CNR-Nanotec, Institute of Nanotechnology, Via Monteroni, Lecce 73100, Italy; Department of Life Sciences, Health and Health Professions, Link Campus University, Via del Casale Di San Pio V 44, Rome 00165, Italy.

PMID: 40616912
DOI: 10.1016/j.jiph.2025.102885

Abstract

Background: Human metapneumovirus (HMPV) is a major cause of respiratory infections, especially in vulnerable populations. The absence of targeted antiviral therapies necessitates the exploration of novel drug candidates. Traditional medicinal plants offer a reservoir of bioactive compounds with potential antiviral properties. This study employs a multi-method computational approach to assess the antiviral potential of phytochemicals against HMPV.

Methods: A comprehensive in silico framework was employed, including virtual screening, molecular docking, molecular dynamics (MD) simulations, density functional theory (DFT) calculations, pharmacophore modeling, and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiling. Key bioactive compounds were evaluated for their binding affinity, stability, and pharmacokinetic properties.

Results: Among the analyzed phytochemicals, Glycyrrhizin exhibited the highest binding affinity (-65.4 kcal/mol) with strong hydrogen bonding and remarkable dynamic stability (RMSD 1.3 Å). Withaferin A (-63.7 kcal/mol) also demonstrated high pharmacokinetic potential. DFT analyses confirmed their favorable electronic properties, and ADMET profiling validated their drug-like characteristics. These findings highlight the promise of natural compounds as potential HMPV inhibitors.

Conclusions: This study underscores the potential of traditional phytochemicals in antiviral drug discovery. The integration of computational techniques accelerates lead identification and optimization. Further in vitro and in vivo validations are essential to confirm these findings and facilitate clinical translation.

Keywords: Antiviral Therapeutics; Computational Drug Discovery; Human Metapneumovirus (HMPV); Molecular Docking; Molecular Dynamics Simulations.