Kyasanur Forest Disease Virus (KFDV) poses a significant public health threat due to the limited efficacy of existing vaccines, necessitating the development of effective antiviral therapeutics. The nonstructural protein 5 (NS5), essential for viral RNA synthesis and methylation, serves as a promising drug target. This study employs computational approaches to identify and evaluate potential NS5 inhibitors that may contribute to the development of antiviral compounds against KFDV. The 3D structure of NS5 was predicted using Robetta, SwissModel, and I-TASSER, with the Robetta model (ERRAT score: 96.40) selected for energy minimization. The globally minimized structure, obtained at 49.58 ns, had a potential energy of -416966.82 kcal/mol and was used for further studies. Active site residues were identified using template-based and structure-based methods (COACH-D, CASTp, PrankWeb) and were located within polymerase motif (A-G) of NS5 protein (residues 273-903 aa), which are essential for polymerase function, RNA synthesis, and viral replication. A total of 1523 compounds were identified using de novo, template-based design, pharmacophore modeling, and ligand screening. Virtual screening with PyRx 0.8 yielded 34 promising compounds, of which 11 were selected based on molecular docking (AutoDock 4.0) with binding energies of -8.86 kcal/mol (FDA-approved dasabuvir -L1), -8.28 kcal/mol (CNPO331352.1-L2), -7.94 kcal/mol (ZINC00103114410- L3), and -7.61 kcal/mol (CNPO202263.1-L4). MD simulations in triplicates under physiological conditions confirmed stability. with MM-GBSA binding free energy values of -52.28â±â2.91 kcal/mol (NS5-Dasabuvur L1complex), -46.82â±â4.31 kcal/mol (NS5-L2 complex), -50.72â±â6.36 kcal/mol (NS5-L3 complex), and -57.03â±â4.31 kcal/mol (NS5-L4 complex). The computational analysis suggests that compounds L2 and L4 have strong binding affinities comparable to dasabuvir (L1), indicating their potential as inhibitors of the KFDV NS5 protein. Further validation through in vitro assays would complement these in silico findings. These results provide a foundation for future drug development against KFDV, emphasizing the need for continued exploration of antiviral therapeutics.
Exploration of effective pharmacological inhibitors for NS5 protein through computational approach: A strategy to combat the neglected Kyasanur forest disease virus.
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作者:Achappa Sharanappa, Aldabaan Nayef Abdulaziz, Alasmary Mohammed, Shaikh Ibrahim Ahmed, Mahnashi Mater H, Desai Shivalingsarj V, Muddapur Uday M, Khan Aejaz Abdullatif, Mannasaheb Basheerahmed Abdulaziz
| 期刊: | PLoS One | 影响因子: | 2.600 |
| 时间: | 2025 | 起止号: | 2025 Jul 10; 20(7):e0325613 |
| doi: | 10.1371/journal.pone.0325613 | ||
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