Computational Design and In Silico Evaluation of Resveratrol Analogues as Potential Hemagglutinin Fusion Inhibitors of Influenza A (H1N1)

Influenza A hemagglutinin (HA) is a target of interest for viral entry inhibitors. The group 1 HA stem harbours a druggable pocket, occupied by the fusion inhibitor F0045(S), which blocks the low-pH conformational change required for membrane fusion and is mechanistically independent of the neuraminidase inhibitors in clinical use. This study computationally evaluated eight resveratrol derivatives using molecular docking against H1/PR8 HA (PDB ID 6WCR), density functional theory calculations, predicted ADMET properties, and internal-coordinate normal mode analysis with iMODS. L4 and L2 yielded the most favourable docking scores among the derivatives, at −8.8 and −8.6 kcal/mol respectively, against −5.2 kcal/mol for the co-crystallised ligand TU7 under the same protocol, which was validated by redocking TU7 to 0.99 Å RMSD. Normalised for molecular size, however, all eight derivatives exceeded both comparators in ligand efficiency while L2 and L4 ranked lowest within the series, indicating that their raw-score advantage derives substantially from added heavy-atom count rather than from superior complementarity. These scores support experimental prioritisation but do not establish binding affinity or antiviral efficacy. Electronic-structure calculations characterised frontier orbital properties, while normal mode analysis explored collective structural flexibility. ADMET predictions identified both favourable features and liabilities, notably poor predicted intestinal absorption for the glucuronide L2 (28.5%) and a borderline immunotoxicity alert (p = 0.52) that is too close to the decision boundary to be relied upon. No experimental validation was performed. L2 and L4 are therefore proposed as candidates for HA-binding, fusion-inhibition, antiviral, and cytotoxicity testing rather than as validated antiviral leads.

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Journal
Chemistry
Published
2026-11-10
DOI
https://doi.org/10.3390/chemistry8110159
Primary Topic
Computational Drug Discovery Methods
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article
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article

Computational Design and In Silico Evaluation of Resveratrol Analogues as Potential Hemagglutinin Fusion Inhibitors of Influenza A (H1N1)

Mohmmad Younus Wani, Faisal Mohammed Aqlan, Irfan Ahmed Rather, Abdullah S. Al‐Bogami et al.
Chemistry
Computational Drug Discovery Methods
article

Computational Design and In Silico Evaluation of Resveratrol Analogues as Potential Hemagglutinin Fusion Inhibitors of Influenza A (H1N1)

Mohmmad Younus Wani, Faisal Mohammed Aqlan, Irfan Ahmed Rather, Abdullah S. Al‐Bogami, Norah F. Alqahtani, Ammar M. AL-Farga, Aijaz Ahmed
article en

Abstract

Influenza A hemagglutinin (HA) is a target of interest for viral entry inhibitors. The group 1 HA stem harbours a druggable pocket, occupied by the fusion inhibitor F0045(S), which blocks the low-pH conformational change required for membrane fusion and is mechanistically independent of the neuraminidase inhibitors in clinical use. This study computationally evaluated eight resveratrol derivatives using molecular docking against H1/PR8 HA (PDB ID 6WCR), density functional theory calculations, predicted ADMET properties, and internal-coordinate normal mode analysis with iMODS. L4 and L2 yielded the most favourable docking scores among the derivatives, at −8.8 and −8.6 kcal/mol respectively, against −5.2 kcal/mol for the co-crystallised ligand TU7 under the same protocol, which was validated by redocking TU7 to 0.99 Å RMSD. Normalised for molecular size, however, all eight derivatives exceeded both comparators in ligand efficiency while L2 and L4 ranked lowest within the series, indicating that their raw-score advantage derives substantially from added heavy-atom count rather than from superior complementarity. These scores support experimental prioritisation but do not establish binding affinity or antiviral efficacy. Electronic-structure calculations characterised frontier orbital properties, while normal mode analysis explored collective structural flexibility. ADMET predictions identified both favourable features and liabilities, notably poor predicted intestinal absorption for the glucuronide L2 (28.5%) and a borderline immunotoxicity alert (p = 0.52) that is too close to the decision boundary to be relied upon. No experimental validation was performed. L2 and L4 are therefore proposed as candidates for HA-binding, fusion-inhibition, antiviral, and cytotoxicity testing rather than as validated antiviral leads.

ChemistryVol. 8(11)
King Abdulaziz University (SA), University of the Witwatersrand (ZA), University of Jeddah (SA), University of Pittsburgh Medical Center (US)
Computational Drug Discovery Methods
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