Exploring traditional Chinese medicine for antiviral drug discovery: A computational approach to combat human metapneumovirus (HMPV)

Human metapneumovirus (HMPV) remains a major respiratory pathogen without approved antivirals, highlighting the urgent need for novel therapeutics. This study implemented an integrative computational pipeline combining virtual screening, molecular docking, 2 μs molecular dynamics (MD) simulations, density functional theory (DFT), pharmacophore modeling, and ADMET profiling to identify potent HMPV inhibitors from Traditional Chinese Medicine. Among 180 screened phytoconstituents, glycyrrhizin (–9.3 kcal mol⁻¹), hesperidin (–9.1 kcal mol⁻¹), and saikosaponins (–9.0 kcal mol⁻¹) exhibited strong binding affinities toward the HMPV matrix protein (PDB ID: 5WB0). Extended MD simulations confirmed complex stability with RMSD 0.17–0.22 nm, average of 3–5 persistent H-bonds, and DCCM correlation coefficient = 0.86 for glycyrrhizin. MM-PBSA binding free energies (ΔG_bind) of –46.2 ± 2.5, –44.7 ± 2.8, and –43.9 ± 2.2 kJ mol⁻¹ for glycyrrhizin, hesperidin, and oseltamivir respectively, validated strong and stable interactions. DFT results indicated favorable electronic reactivity (HOMO–LUMO gap = 3.86 eV; electrophilicity = 2.74 eV), enhancing ligand-target complementarity. ADMET analysis predicted low systemic toxicity (LD₅₀ = 380–530 mg kg⁻¹) but revealed moderate CYP3A4/CYP2C9 inhibition, suggesting the need for metabolic stability evaluation. Compared with reported fusion inhibitors such as EGCG and rutin, this matrix-targeted strategy introduces a distinct therapeutic mechanism. Overall, these findings establish a robust computational foundation for developing and experimentally validating potent natural inhibitors against HMPV.