bioRxivBioinformaticsPreprint
Harnessing Computational Insights to Identify Potent Inhibitors for Human Metapneumovirus (HMPV): A Synergistic Approach with Natural Compounds
Amit DubeyiD, Manish KumariD, Aisha TufailiD, Vivek Dhar DwivediiD
Abstract
Human metapneumovirus (HMPV), a leading cause of acute lower respiratory tract infections, has emerged as a global health challenge due to its high prevalence, particularly among children, the elderly, and immunocompromised individuals. Despite its significant impact, no targeted antivirals or vaccines are available. This study employs a comprehensive computational pipeline to identify and evaluate potential inhibitors of the HMPV matrix protein (PDB: 5WB0). Natural compounds such as epigallocatechingallate (EGCG), rutin, and quercetin, along with control drugs, were screened for their therapeutic potential.Virtual screening identified EGCG (-9.1 kcal/mol), rutin (-9.0 kcal/mol), and quercetin (-8.8 kcal/mol) as top binders, surpassing standard drugs like ribavirin (-8.9 kcal/mol). Molecular docking revealed stable binding interactions, including hydrogen bonding with residues Arg143 and Glu186. Molecular dynamics (MD) simulations over a 1000 ns trajectory confirmed the stability of these complexes, with EGCG displaying the lowest RMSD (2.1 [A]) and consistent hydrogen bonding throughout the simulation. Density Functional Theory (DFT) calculations highlighted favorable electronic properties, with EGCG showing a low band gap (3.29 eV) and high dipole moment (3.12 D), indicative of strong reactivity and binding potential. ADMET profiling revealed excellent oral bioavailability for EGCG (84%) and quercetin (88%), with minimal toxicity risks. The Molecular Electrostatic Potential (MESP) mapping identified highly reactive regions on the molecular surface, correlating with nucleophilic and electrophilic binding capabilities. The findings position EGCG, rutin, and quercetin as promising candidates for HMPV therapy, providing a strong foundation for further experimental validation and preclinical development.
- organism: human
- assay: protein structure
- research focus: drug response / drug discovery
- approach: statistical model
- approach: simulation
- Citations
- 9
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