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<p>Dengue fever, caused by the Dengue virus (DENV), is a significant global health concern that affects millions of people each year, and there is currently no specific antiviral treatment available. The RNA-dependent RNA polymerase (RdRp) is an essential viral enzyme that replicates the viral RNA genome, making it a crucial target for therapeutic intervention. Previous computational studies have primarily focused on small natural or synthetic compound libraries, often relying solely on docking or limited validation, resulting in low chemical diversity and structural novelty. In this study, we employed a computational approach to identify a novel natural product inhibitor of DENV RdRp. High-throughput virtual screening of 407,270 natural compounds from the COCONUT database was performed to identify four lead compounds: CNP0243663, CNP0306108, CNP0384605, and CNP0226892, which were selected based on favourable binding free energies ranging from −&#xa0;81.64 to −&#xa0;74.97&#xa0;kcal/mol. The selected compounds showed higher docking scores, ranging from −&#xa0;9.639 to −&#xa0;11.806&#xa0;kcal/mol, compared to the co-crystallized reference inhibitor 68&#xa0;T, which had a docking score of −&#xa0;9.368&#xa0;kcal/mol. Molecular docking and interaction analysis revealed that the selected compounds bind to key residues within the RdRp active sites, demonstrating higher binding affinities and more favourable interaction profiles than 68&#xa0;T. Additionally, these selected compounds were further optimized using Density Functional Theory (DFT) and subjected to 200&#xa0;ns Molecular Dynamics (MD) simulations, confirming their stable binding and protein–ligand interactions. Post-MD analysis, including Molecular Mechanics and Generalized Born Surface Area (MM/GBSA) rescoring and Principal Component Analysis (PCA), further validated their conformational stability and dynamic behaviour. These results provide novel computational insights into natural compounds as promising RdRp inhibitors, offering a prioritized set of lead candidates for the development of anti-dengue therapeutics and establishing a robust foundation for future experimental validation.</p> Graphical Abstract <p></p>

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Natural product inhibitors targeting dengue virus RNA dependent RNA polymerase using molecular dynamics and density functional theory

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月11日

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  • Aishwarya Khare,
  • Varsha Tripathi,
  • Vivek Dhar Dwivedi,
  • Neelam Pathak,
  • Shivi Srivastava

摘要

Dengue fever, caused by the Dengue virus (DENV), is a significant global health concern that affects millions of people each year, and there is currently no specific antiviral treatment available. The RNA-dependent RNA polymerase (RdRp) is an essential viral enzyme that replicates the viral RNA genome, making it a crucial target for therapeutic intervention. Previous computational studies have primarily focused on small natural or synthetic compound libraries, often relying solely on docking or limited validation, resulting in low chemical diversity and structural novelty. In this study, we employed a computational approach to identify a novel natural product inhibitor of DENV RdRp. High-throughput virtual screening of 407,270 natural compounds from the COCONUT database was performed to identify four lead compounds: CNP0243663, CNP0306108, CNP0384605, and CNP0226892, which were selected based on favourable binding free energies ranging from − 81.64 to − 74.97 kcal/mol. The selected compounds showed higher docking scores, ranging from − 9.639 to − 11.806 kcal/mol, compared to the co-crystallized reference inhibitor 68 T, which had a docking score of − 9.368 kcal/mol. Molecular docking and interaction analysis revealed that the selected compounds bind to key residues within the RdRp active sites, demonstrating higher binding affinities and more favourable interaction profiles than 68 T. Additionally, these selected compounds were further optimized using Density Functional Theory (DFT) and subjected to 200 ns Molecular Dynamics (MD) simulations, confirming their stable binding and protein–ligand interactions. Post-MD analysis, including Molecular Mechanics and Generalized Born Surface Area (MM/GBSA) rescoring and Principal Component Analysis (PCA), further validated their conformational stability and dynamic behaviour. These results provide novel computational insights into natural compounds as promising RdRp inhibitors, offering a prioritized set of lead candidates for the development of anti-dengue therapeutics and establishing a robust foundation for future experimental validation.

Graphical Abstract