Harnessing Computational Insights to Identify Potent Inhibitors for Human Metapneumovirus (HMPV): A Synergistic Approach with Natural Compounds
Dubey, A.; Kumar, M.; Tufail, A.; Dwivedi, V. D.
Show 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.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Pharmacophore modeling, 2D-QSAR, Molecular Docking and ADME studies for the discovery of inhibitors of PBP2a in MRSA 97%
- De novo drug designing coupled with brute force screening and structure guided lead optimization gives highly specific inhibitor of METTL3: a potential cure for Acute Myeloid Leukaemia 97%
- An in-silico approach to identify bioactive phytochemicals from Houttuynia cordata Thunb. As potential inhibitors of Human Glutathione Reductase 97%
Similar papers in this journal
- Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of Rheumatoid Arthritis: Virtual screening to comprehensive in silico investigation 99%
- Identification of Natural Antiviral Drug Candidates Against Tilapia Lake Virus: Computational Drug Design Approaches 98%
- Molecular docking, simulation and binding free energy analysis of small molecules as PfHT1 inhibitors 97%
Similar papers in this journal
- Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-based Classifiers 97%
- Molecular Glue-Design-Evaluator (MOLDE): An Advanced Method for In-Silico Molecular Glue Design 96%
- Chalcogen derivatives for the treatment of African trypanosomiasis: biological evaluation of thio and seleno- semicarbazones and their azole derivatives 96%
Similar papers in this journal
- Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 protease 94%
- Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening 94%
- Structural characterization of LsrK to target quorum sensing and comparison between X-ray and homology model 94%
Similar papers in this journal
- Mechanistic insights into the Japanese Encephalitis Virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica 98%
- Discovery of Z1362873773: A Novel Fascin Inhibitor from a Large Chemical Library for Colorectal Cancer 96%
- PeruNPDB: The Peruvian Natural Products Database for in silico drug screening 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.