3D-QSAR Models to Predict the Antiviral Activities of a series of novel N-phenylbenzamideand N-phenylacetophenone compounds based on density functional theory using statistical methods
Mohamed Bourass, Hadaji El Ghalia, Ouammou, Abdelkarim, Mohammed Bouachrıne · Moroccan Journal of chemistry · 2015
This research is a fundamental study of the structure activity relationship of a series of novel N-phenylbenzamide and N-phenylacetophenone. In this study we used the quantum chemical calculation using density functional theory DFT (B3LYP/6-31G) methods to determine the quantum chemical parameters,the electronics and energy associated with molecules studied. The QSAR studies have been performed on twenty one molecules of a series of novel N-phenylbenzamide and N-phenylacetophenone analogues. The compounds are characterized by the effect for the development of anti-EV 71 drugs. A multiple linear regression (MLR) and a multiple non-linear regression procedure were been carried out to develop the relationships between descriptors and molecular properties antiviral activity. The statistical results indicate that these models are statistically significant and represent a very good stability for high values of the correlation coefficients (R(pIC50 = 0.87) and R(pTC50) = 0.95 for MLR and R=0.91 R =0.96 to the RNLM). The validation of the model RLM has been done by dividing the dataset into training and test set, the external validation of multiple correlation coefficients were(pIC50 = 0.93) and R(pTC50) = 0.95 for MLR and (pIC50 = 0.93) and R(pTC50) = 0.94 for MNLR.