QSAR for Antimycobacterial Activity of β-Thia Adduct of Chalcone and Diazachalcone Derivatives

Quantitative structure-activity antimycobacterial relationships have been studied for a series of β-thia adduct of chalcone and diazachalcone derivatives by means of multiple linear regression (MLR) and artificial neural networks (ANN). The antimycobacterial activity against M. tuberculosis H37Rv of the compounds studied was well correlated with descriptors encoding the chemical structure. Using the pertinent descriptors revealed by a stepwise procedure in the multiple linear regression technique, a correlation coefficient of 0.9798 (s=0.0869) for the training set was obtained for the ANN model in a [3-3-1] configuration. The results show that the antimycobacterial activity of these compounds is strongly dependent on hydrogen-bonding donors, molecular refraction and also molecular connectivity indices for 2nd order.