4D-QSAR study of HEPT derivatives by electron conformational–genetic algorithm method

Abstract

In this work, the EC-GA method, a hybrid 4D-QSAR approach that combines the electron conformational (EC) and genetic algorithm optimization (GA) methods, was applied in order to explain pharmacophore (Pha) and predict anti-HIV-1 activity by studying 115 compounds in the class of 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio) thymine (HEPT) derivatives as non-nucleoside reverse transcriptase inhibitors (NNRTIs). The series of NNRTIs were partitioned into four training and test sets from which corresponding quantitative structure-activity relationship (QSAR) models were constructed. Analysis of the four QSAR models suggests that the three models generated from the training and test sets used in previous works yielded comparable results with those of previous studies. Model 4, the data set of which was partitioned randomly into two training and test sets with 11 descriptors, including electronical and geometrical parameters, showed good statistics both in the regression (r2(training) )= 0.867, r2test = 0.923) and cross-validation (q (2) = 0.811, q2(ext1) = 0.909, q2(ext2) = 0.909) for the training set of 80 compounds and the test set of 27 compounds. The prediction of the anti-HIV-1 activity of HEPT compounds by means of the EC-GA method allowed for a quantitatively consistent QSAR model. In addition, eight novel compounds never tested experimentally have been designed theoretically using model 4.

Two Decades of 4D-QSAR: A Dying Art or Staging a Comeback?

“…The basic operational steps of the combined EC-GA approach are presented in Figure 8 . The ligand 3D structures are constructed and optimized using the semi-empirical (PM3) or quantum chemical calculations (HF/6-311 G ** level in the aqueous medium) [ 82 , 83 , 84 ]. In order to generate the conformational ensemble profile for the investigated series Monte Carlo (MC) randomized search simulations are conducted.…”

The study of dual COX-2/5-LOX inhibitors by using electronic-topological approach based on data on the ligand–receptor interactions

“…Earlier, when forming ETMCs for flexible molecules, it was necessary to carry out complicated calculations. A new approach based on the Genetic Algorithms [36,37] has been applied for the pharmacophoric groups' identification. When ETM and docking are used together, 3D coordinates of a molecule correspond to the most effective position of the molecule within receptor.…”