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Identification of potential inhibitors of dengue virus ns5 methyltransferase and polymerase domains through virtual screening and molecular dynamics studies

  • Nabeel Haider
  • , Abolfazl Zare
  • , Yi Zhou
  • , Faez Iqbal Khan*
  • *Corresponding author for this work
  • Yangzhou University
  • Yazd University
  • Xi'an Jiaotong-Liverpool University

Research output: Contribution to journalArticlepeer-review

Abstract

Context: The dengue virus continues to pose a serious global health challenge due to the absence of effective antiviral therapies. Non-structural protein 5 (NS5), a multifunctional non-structural protein containing methyltransferase and RNA-dependent RNA polymerase domains, is essential for viral replication and represents a high-priority therapeutic target. In this study, potential inhibitors targeting two functional sites of Dengue virus serotype 3 (DENV-3) NS5 were identified through structure-based virtual screening and structural dynamics analysis. Docking results identified PubChem compound 135,625,223 as the strongest binder at the RNA-binding site with a binding affinity of − 11.8 kcal/mol, forming a hydrogen bond with Arg481 and a hydrophobic interaction with Phe485. Molecular dynamics simulations showed that the S-adenosylmethionine (SAM)-binding site ligand formed a more stable complex with lower root-mean-square deviation (RMSD) (0.26 nm) and reduced flexibility, indicating a promising lead candidate for further optimization and experimental validation against dengue virus NS5. Methods: The full-length NS5 structure was constructed using homology modeling with MODELLER, ab initio modeling, and AlphaFold, and the best model was selected based on low RMSD and stereochemical quality. A library of 587 antiviral compounds retrieved from PubChem was docked against the SAM-binding site of the methyltransferase domain and the RNA-binding site of the polymerase domain using AutoDock Vina. The top-ranked ligands were further evaluated through Insilico screening and 300-ns molecular dynamics simulations using GROMACS.

Original languageEnglish
Article number263
JournalJournal of Molecular Modeling
Volume32
Issue number8
DOIs
Publication statusPublished - 8 Jul 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Dengue virus NS5
  • Dual-site inhibitors
  • Molecular dynamics
  • Structure-based drug discovery
  • Virtual screening

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