Abstract

A set of 58 compounds of pyrimidines derivatives was subjected to molecular modeling studies using two-dimensional, k-Nearest Neighbor (kNN), and pharmacophore methods. Two-dimensional-QSAR modeling using simulated annealing or stepwise coupled partial least squares (SA-PLS and SW-PLS) methods identified some important topological indices, hydrophobic thermodynamic electronic and spatial descriptors properties descriptors as important factor for cannabinoid CB1 activity. The best quantitative structure–activity relationship models were further validated by leave-one-out method of cross-validation. The best 2D-QSAR model was selected, having showed best predictability of cannabinoid CB1 receptor activity with cross-validated value (q2) = 0.7942, coefficient of determination (r2) = 0.9054, and r2_pred value of 0.8269 was developed by SA-PLS. kNN-MFA 3D QSAR was performed on the same series to correlate the effects of electrostatic, steric, and hydrophobic parameters with the cannabinoid CB1 activity using simulated annealing, stepwise forward backward regression and genetic algorithm methods. The best 3D model SA-PLS shows electrostatic descriptor present near R1 of the pyrimidine suggested that the electron-withdrawing group is required for enhancing the biological activity. The presence of steric descriptors with negative coefficients simultaneously at chloro and R2-positions of the pyrimidine ring, suggests the favorable of that less steric or less bulky substituents groups in these regions for producing potent cannabinoid CB1 receptor. Chemical feature-based pharmacophore models with lowest RMSD value (0.0681 A), consists of two AroC feature (aromatic), one HDr (hydrogen-bond donor), one HAc (hydrogen-bond acceptor), and one (aliphatic) features was developed. This work may provide a platform for generating leads for novel cannabinoid CB1 receptor inhibitors.

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