👤 Nazmiye Sabanci

In the present work, pharmacophore identification and biological activity prediction for 86 pyrazole pyridine carboxylic acid derivatives were made using the electron conformational genetic algorithm approach which was introduced as a 4D-QSAR analysis by us in recent years. In the light of the data obtained from quantum chemical calculations at HF/6-311 G** level, the Electron Conformational Matrices of Congruity (ECMC) were constructed by EMRE software. Comparing the matrices, electron conformational submatrix of activity (ECSA, Pha) was revealed that are common for these compounds within a minimum tolerance. A parameter pool was generated considering the obtained pharmacophore. To determine the theoretical biological activity of molecules and identify the best subset of variables affecting bioactivities, we used the nonlinear least square regression method and genetic algorithm. The results obtained in this study are in good agreement with the experimental data presented in the literature. The model for training and test sets attained by the optimum 12 parameters gave highly satisfactory results with R2 training= 0.889, q2=0.839 and SEtraining=0.066, q2 ext1 = 0.770, q2 ext2 = 0.750, q2 ext3=0.824, ccctr = 0.941, ccctest = 0.869 and cccall = 0.927. Show less

The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity. The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically. The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R2 training= 0.817, q 2=0.718 and SEtraining=0.066, q2 ext1 = 0.867, q2 ext2 = 0.849, q2 ext3 =0.895, ccctr = 0.895, ccctest = 0.930 and cccall = 0.905. Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes. Show less