2D-QSAR study of the anti-obesity activity for the compounds based on 2-anilino, 4-aryl pyrimidines and 2,4-diaryl 7-azaindoles using statistical methods
Halima Hajji, Ilham Aanouz, Khalil El Khatabi, Tahar Lakhlifi, Mohammed Aziz Ajana, Mohammed Bouachrıne · Journal of Analytical Science & Technology · 2020
In this study, we have developed a new effective study to find solutions for obesity disease by exploring the links between this disease and the CAMKK2 inhibitor by developing a two-dimensional model of quantitative structure-activity relationships (2D-QSAR) for a group of 32 molecules based on pyrimidine and azaindole derivatives, these molecules were subjected to quantitative structure-activity analysis (QSAR) to study, interpret and predict activities using several statistical tools, such as Multiple Linear Regression (MLR), Nonlinear Regression (MNLR) , and principal component analysis models (PCA) which are developed using 32 molecules with a pIC50 between 6.7 and 9.1. The 16 descriptors are calculated for the 32 compounds studied using ACD / ChemSketch and Marvin Sketch software. The best-generated MLR and MNLR models show conventional correlation coefficients R of 0.829 and 0.878, respectively.