Discovery of Novel Natural Inhibitors of H5N1 Neuraminidase Using Integrated Molecular Modeling and ADMET Prediction
The avian influenza virus, particularly the highly pathogenic H5N1 subtype, represents a significant public health threat due to its interspecies transmission potential and growing resistance to current antiviral therapies. To address this, the identification of novel and effective neuraminidase (NA...
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2025-06-01
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| author | Afaf Zekri Mebarka Ouassaf Shafi Ullah Khan Kannan R. R. Rengasamy Bader Y. Alhatlani |
| author_facet | Afaf Zekri Mebarka Ouassaf Shafi Ullah Khan Kannan R. R. Rengasamy Bader Y. Alhatlani |
| author_sort | Afaf Zekri |
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| description | The avian influenza virus, particularly the highly pathogenic H5N1 subtype, represents a significant public health threat due to its interspecies transmission potential and growing resistance to current antiviral therapies. To address this, the identification of novel and effective neuraminidase (NA) inhibitors is critical. In this study, an integrated in silico strategy was employed, beginning with the generation of an energy-optimized pharmacophore model (e-pharmacophore, ADDN) based on the reference inhibitor Zanamivir. A virtual screening of 47,781 natural compounds from the PubChem database was performed, followed by molecular docking validated through an enrichment assay. Promising hits were further evaluated via ADMET predictions, density functional theory (DFT) calculations to assess chemical reactivity, and molecular dynamics (MD) simulations to examine the stability of the ligand–protein complexes. Three lead compounds (C1: CID 102209473, C2: CID 85692821, and C3: CID 45379525) demonstrated strong binding affinity toward NA. Their ADMET profiles predicted favorable bioavailability and low toxicity. The DFT analyses indicated suitable chemical reactivity, particularly for C2 and C3. The MD simulations confirmed the structural stability of all three ligand–NA complexes, supported by robust and complementary intermolecular interactions. In contrast, Zanamivir exhibited limited hydrophobic interactions, compromising its binding stability within the active site. These findings offer a rational foundation for further experimental validation and the development of next-generation NA inhibitors derived from natural sources. |
| format | Article |
| id | doaj-art-d8570dd2ddd947b681d322f54e0dec30 |
| institution | Kabale University |
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| language | English |
| publishDate | 2025-06-01 |
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| spelling | doaj-art-d8570dd2ddd947b681d322f54e0dec302025-08-20T03:26:25ZengMDPI AGBioengineering2306-53542025-06-0112662210.3390/bioengineering12060622Discovery of Novel Natural Inhibitors of H5N1 Neuraminidase Using Integrated Molecular Modeling and ADMET PredictionAfaf Zekri0Mebarka Ouassaf1Shafi Ullah Khan2Kannan R. R. Rengasamy3Bader Y. Alhatlani4Group of Computational and Medicinal Chemistry, LMCE Laboratory, University of Biskra, BP 145, Biskra 07000, AlgeriaGroup of Computational and Medicinal Chemistry, LMCE Laboratory, University of Biskra, BP 145, Biskra 07000, AlgeriaInserm U1086 ANTICIPE (Interdisciplinary Research Unit for Cancer Prevention and Treatment), Normandie University, Université de Caen Normandie, 14076 Caen, FranceLaboratory of Natural Products and Medicinal Chemistry (LNPMC), Saveetha Medicinal College and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai 602105, IndiaUnit of Scientific Research, Applied College, Qassim University, Buraydah 52571, Saudi ArabiaThe avian influenza virus, particularly the highly pathogenic H5N1 subtype, represents a significant public health threat due to its interspecies transmission potential and growing resistance to current antiviral therapies. To address this, the identification of novel and effective neuraminidase (NA) inhibitors is critical. In this study, an integrated in silico strategy was employed, beginning with the generation of an energy-optimized pharmacophore model (e-pharmacophore, ADDN) based on the reference inhibitor Zanamivir. A virtual screening of 47,781 natural compounds from the PubChem database was performed, followed by molecular docking validated through an enrichment assay. Promising hits were further evaluated via ADMET predictions, density functional theory (DFT) calculations to assess chemical reactivity, and molecular dynamics (MD) simulations to examine the stability of the ligand–protein complexes. Three lead compounds (C1: CID 102209473, C2: CID 85692821, and C3: CID 45379525) demonstrated strong binding affinity toward NA. Their ADMET profiles predicted favorable bioavailability and low toxicity. The DFT analyses indicated suitable chemical reactivity, particularly for C2 and C3. The MD simulations confirmed the structural stability of all three ligand–NA complexes, supported by robust and complementary intermolecular interactions. In contrast, Zanamivir exhibited limited hydrophobic interactions, compromising its binding stability within the active site. These findings offer a rational foundation for further experimental validation and the development of next-generation NA inhibitors derived from natural sources.https://www.mdpi.com/2306-5354/12/6/622ADMETmolecular dockingmolecular dynamics simulationsneuraminidase inhibitorZanamivir |
| spellingShingle | Afaf Zekri Mebarka Ouassaf Shafi Ullah Khan Kannan R. R. Rengasamy Bader Y. Alhatlani Discovery of Novel Natural Inhibitors of H5N1 Neuraminidase Using Integrated Molecular Modeling and ADMET Prediction Bioengineering ADMET molecular docking molecular dynamics simulations neuraminidase inhibitor Zanamivir |
| title | Discovery of Novel Natural Inhibitors of H5N1 Neuraminidase Using Integrated Molecular Modeling and ADMET Prediction |
| title_full | Discovery of Novel Natural Inhibitors of H5N1 Neuraminidase Using Integrated Molecular Modeling and ADMET Prediction |
| title_fullStr | Discovery of Novel Natural Inhibitors of H5N1 Neuraminidase Using Integrated Molecular Modeling and ADMET Prediction |
| title_full_unstemmed | Discovery of Novel Natural Inhibitors of H5N1 Neuraminidase Using Integrated Molecular Modeling and ADMET Prediction |
| title_short | Discovery of Novel Natural Inhibitors of H5N1 Neuraminidase Using Integrated Molecular Modeling and ADMET Prediction |
| title_sort | discovery of novel natural inhibitors of h5n1 neuraminidase using integrated molecular modeling and admet prediction |
| topic | ADMET molecular docking molecular dynamics simulations neuraminidase inhibitor Zanamivir |
| url | https://www.mdpi.com/2306-5354/12/6/622 |
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