QSAR investigation on benzimidazole derivatives in Trichomonosis disease
Keywords:Benzimidazole derivatives, QSAR model, Genetic Algorithm, Artificial Neural Network.
Globally trichomoniasis affects approximately 152 million people as of 2010 (2.2% of the population). It is more common in women (2.7%) than males (1.4%). The American Social Health Association estimates trichomoniasis affects 7.4 million previously unaffected Americans each year and is the most frequently presenting new infection of the common sexually transmitted diseases. On the pattern, QSAR study has been done on benzimidazole derivatives as potent inhibitors with trichomonicidal activity. Genetic algorithm (GA), artificial neural network (ANN), stepwise multiple linear regression (stepwise-MLR) were used to create then on non-linear and linear QSAR models. Geometry optimization of compounds was carried out by B3LYP method employing 6“31G (2d) basis set. HyperChem, Gaussian 03W, and Dragon (version 5.5) software programs were used for geometry optimization of the molecules and calculation of the quantum chemical descriptors. Finally, Unscrambler program was used for the analysis of data. The root-mean square errors of the training set and the test set for GAANN model using jack-knife method, were 0.1840, 0.5051 and R2 was 0.70. Also, the R and R2 values in the gas phase were obtained 0.78, 0.61 from GA-stepwise MLR model. According to the obtained results, we find out GA-ANN model is the most favorable method toward the other statistical methods. Also, we would suggest that compounds No. 20, 33, 58, 48 and 47 as the most appropriate structure for the design of drugs to pharmacists.
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