Mohebbi, A.; Askari, F.S.; Askari, P.; Kiani, S.J. Ligand-based pharmacophore modeling, virtual screening, and 2D quantitative structure-activity relationship performance on anti-Hepatitis B virus flavonols. Preprints2024, 2024031775. https://doi.org/10.20944/preprints202403.1775.v1
APA Style
Mohebbi, A., Askari, F.S., Askari, P., & Kiani, S.J. (2024). Ligand-based pharmacophore modeling, virtual screening, and 2D quantitative structure-activity relationship performance on anti-Hepatitis B virus flavonols. Preprints. https://doi.org/10.20944/preprints202403.1775.v1
Chicago/Turabian Style
Mohebbi, A., Parnia Askari and Seyed Jalal Kiani. 2024 "Ligand-based pharmacophore modeling, virtual screening, and 2D quantitative structure-activity relationship performance on anti-Hepatitis B virus flavonols" Preprints. https://doi.org/10.20944/preprints202403.1775.v1
Abstract
Background: Targeting Hepatitis B virus (HBV) infection in human is crucial due to its adverse. Herbal medicine has long been significant in this regard, with flavonoids demonstrating promising results. Hence, establishing a way of identifying flavonoids with anti-HBV activities is the aim of the present study. Methods: Flavonoid structures with anti-HBV activities were retrieved. A flavonol-based pharmacophore model was established using LigandScout v4.4. Screening was performed using the PharmIt server. A QSAR equation was developed and validated with independent sets of compounds. Applicability domain (AD) was defined using Euclidean distance calculations for model validation. Results: The best model, consisting of 57 features was generated. HTS using the flavonol-based model resulted in 509 unique hits. The model's sensitivity and specificity were 71% and 100%, respectively. The QSAR model with two predictors, x4a and qed, exhibited strong predictive performance with an adjusted-R² value of 0.85 and 0.90 of Q2. Conclusion: The QSAR model has been validated with two separate chemical sets, guaranteeing the model's reproducibility and usefulness for other flavonols by utilizing the predictive characteristics of X4A and qed. These results provide new possibilities for discovering future anti-HBV drugs by integrating modeling and experimental research.
Keywords
Hepatitis B virus; Antivirals; Flavonoid; Drug discovery; Pharmacophore; Quantitative structure-activity relationship
Subject
Biology and Life Sciences, Virology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
