4. EXPLORING NS3 PROTEASE INHIBITORS USING IN SILICO METHODS: POTENTIAL FOR ZIKA VIRUS TREATMENT
Main Article Content
Abstract
Objectives: (1) To develop a pharmacophore model to identify compounds capable of inhibiting the NS3 protease enzyme; (2) Based on the established pharmacophore model, this study performed virtual screening for potential NS3 protease inhibitors from the ZINC database using the ZINCPharmer tool.
Subjects and Methods: A pharmacophore model was constructed via the docking of a reference compound (Compound 1) into the NS3 protease enzyme (PDB ID: 5H4I). Virtual screening was performed using ZINCPharmer on the ZINC database, followed by molecular docking evaluation using AutoDock Vina.
Results: A pharmacophore model was successfully developed, characterized by three aromatic rings (Ar), one hydrophobic feature, and two hydrogen bond acceptors. Virtual screening of 21.777.093 compounds from the ZINC database resulted in the identification of 24 compounds matching the pharmacophore model. Among these, 10 compounds satisfied Lipinski’s Rule of Five. Subsequent molecular docking of these compounds revealed binding energies ranging from -7,5 to -8,1 kcal/mol. Notably, compound ZINC08961480 exhibited the lowest binding energy (-8,1 kcal/mol) and formed several key interactions with critical amino acid residues, including hydrogen bonds (Ser135 and Tyr150), π-π stacking interaction (Tyr161), π-alkyl and alkyl (Val36 and Ala132).
Conclusion: The study successfully developed a pharmacophore model to facilitate the screening of potential NS3 protease inhibitors. Virtual screening of the ZINC database identified 24 compounds fitting the model, of which 10 compounds complied with Lipinski’s criteria for drug-likeness. Among these, ZINC08961480 exhibited the highest binding affinity and demonstrated strong potential as a lead compound for the development of anti-Zika drugs through NS3 protease inhibition.
Article Details
Keywords
Pharmacophore model, molecular docking, NS3 protease, Zika virus.
References
[2] Cuong Quoc Nguyen, et al. (2021). Designs, synthesis, docking studies, and biological evaluation of novel berberine derivatives targeting zika virus. Journal of Chemistry, 2021(1).
[3] Kunal Roy, Supratik Kar, and Rudra Narayan Das (2015). Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment, 1st ed. Academic press.
[4] Yingqi Feng (2024). Recent advances in the study of zika virus structure, drug targets, and inhibitors. Frontiers in Pharmacology, 15.
[5] Yan Li, et al. (2018). Structural insights into the inhibition of Zika virus NS2B-NS3 protease by a small-molecule inhibitor. Structure, 26(4), pp. 555-564.
[6] Lucy R Bowen, et al. (2019). Identification of potential Zika virus NS2B-NS3 protease inhibitors via docking, molecular dynamics and consensus scoring-based virtual screening. Journal of Molecular Modeling, 25(7).
[7] Quang De Tran, et al. (2023). ZIKV Inhibitors Based on Pyrazolo [3, 4-d] pyridazine-7-one Core: Rational Design, In Vitro Evaluation, and Theoretical Studies. ACS omega, 8(51), pp. 48994-49008.
[8] Mohit Motiwale, et al. (2024). The utilization of descriptors in convoluted Lipinski’s rule of five. Computational Drug Delivery: Molecular Simulation for Pharmaceutical Formulation, pp. 39-70.
[9] Josè Starvaggi, et al. (2024). The inhibition of NS2B/NS3 protease: A new therapeutic opportunity to treat dengue and Zika virus infection. International Journal of Molecular Sciences, 25(8).