QSAR study of anti-Human African Trypanosomiasis activity for 2-phenylimidazopyridines derivatives using DFT and Lipinski's descriptors.

The quantitative structure-activity relationship (QSAR) of sixty 2-phenylimidazopyridines derivatives with anti-Human African Trypanosomiasis (anti-HAT) activity has been studied by using the density functional theory (DFT) and statistical methods. Becke's three-parameter hybrid method and the Lee-Yang-Parr B3LYP functional employing 6-31G(d) basis set are used to calculate quantum chemical descriptors using Gaussian 03W software, and the five Lipinski's parameters were calculated using ChemOffice software. In order to obtain robust and reliable QSAR model, the original dataset was randomly divided into training and prediction sets comprising 48 and 12 compounds, respectively. An optimal model for the training set with significant statistical quality was established. The same model was further applied to predict pEC50 values of the 12 compounds in the test set, further showing that this QSAR model has high predictive ability. It is very interesting to find that the anti-HAT of these compounds appear to be mainly governed by four factors, i.e., the number of H-bond donors, the lowest unoccupied molecular orbital energy, the molecular weight and the octanol/water partition coefficient. Here the possible action mechanism of these compounds was analysed and discussed, in particular, important structural requirements for great anti-HAT activity will be by increasing molecular size and substitute the 2-phenylimidazopyridines derivatives with polar, ionic, stronger accepting electron ability group and heteroatoms attached to one or more hydrogen atoms. Based on this proposed QSAR model, some new compounds with higher anti-HAT activities have been theoretically designed. Such results can offer useful theoretical references for future experimental works.

QSAR Analysis for Antioxidant Activity of Dipicolinic Acid Derivatives.

AIMS AND OBJECTIVES: The aim of this study was to derive robust and reliable QSAR models for clarification and prediction of antioxidant activity of 43 heterocyclic and Schiff bases dipicolinic acid derivatives. According to the best obtained QSAR model, structures of new compounds with possible great activities should be proposed. METHODS: Molecular descriptors were calculated by DRAGON and ADMEWORKS from optimized molecular structure and two algorithms were used for creating the training and test sets in both set of descriptors. Regression analysis and validation of models were performed using QSARINS. RESULTS: The model with best internal validation result was obtained by DRAGON descriptors (MATS4m, EEig03d, BELm4, Mor10p), split by ranking method (R2 = 0.805; R2 ext = 0.833; F = 30.914). The model with best external validation result was obtained by ADMEWORKS descriptors (NDB, MATS5p, MDEN33, TPSA), split by random method (R2 = 0.692; R2 ext = 0.848; F = 16.818). CONCLUSION: Important structural requirements for great antioxidant activity are: low number of double bonds in molecules; absence of tertial nitrogen atoms; higher number of hydrogen bond donors; enhanced molecular polarity; and symmetrical moiety. Two new compounds with potentially great antioxidant activities were proposed.