Title:QSAR Modeling and Molecular Docking Studies of New Substituted Pyrazolyl-Pyrimidinones as Potent HIV-1 Inhibitors
Volume: 18
Issue: 3
Author(s): Badr Hamdache, Kamal Tabti, Mohammed Er-rajy, Mustapha Dib*, Khadija ElFarouki, Khadija Ouchetto, Menana Elhalaoui, Abderrafia Hafid, Mostafa Khouili and Hajiba Ouchetto
Affiliation:
- Laboratory of Applied Chemistry and Environment,
Mineral Solid Chemistry Team, Faculty of Sciences, Mohammed First University, B.P. 717, 60 000, Oujda, Morocco
Keywords:
Anti-HIV activity, bioactive molecules, pyrazolyl-pyrimidinones, 2D-QSAR, molecular docking, heterocycles compounds, quantitative structure activity relationship.
Abstract:
Background: Pyrazolyl-pyrimidinone derivatives are important heterocyclic compounds.
A novel HIV-1 (human immunodeficiency virus type 1) inhibitors based on these components were
designed as potential drug candidates for AIDS (acquired immunodeficiency syndrome) therapy.
Objective: This research aims to develop a predictive mathematical model linking the biological activity
and physicochemical properties of pyrazolyl-pyrimidinones derivatives and to identify the interactions
between the most active compound and the HIV-1 active site.
Method: A QSAR-2D study was conducted on 40 pyrazolyl-pyrimidinone derivatives, followed by
molecular docking of the most active compounds.
Results: Principal Component Analysis (PCA) was used to select the best descriptors for building
QSAR models using Multiple Linear Regression (MLR), Multiple Nonlinear Regression (MNLR),
and Artificial Neural Networks (ANN). The MLR model achieved R² = 0.70, Q²Cv = 0.54, and successful
Y-randomization (R = 0.83). The MNLR model had an R² of 0.81 and low mean square error
RMSE = 0.17, while the ANN model showed ρ = 1.5 and RMSE = 0.15. Docking studies confirmed
key interactions between compounds 1 and 11 with the HIV-1 active site. The results of molecular
packaging Substances 11 and 1 have the lowest energy levels of -13.26 kcal/mol and -12.5
kcal/mol, respectively, and have more than one hydrogen bond. The molecular docking validation
finds RMSD = 0.821.
Conclusion: This study allowed the establishment of robust QSAR models with a good predictive
capacity, confirmed by several statistical indicators, with the aim of inhibiting HIV-1. The models
showed satisfactory reliability and docking studies identified key interactions between the compounds
and the active sites of HIV-1, thus reinforcing their profile as promising candidates for the
development of new antiviral treatments.
