An approach to design antimicrobial agents by 2D QSAR studies on series of 5, 5-diphenylimidazolidine-2, 4-dione derivatives

Abstract

A series of twenty two molecules substituted 5,5-diphenylimidazolidine-2,4-dione derivatives displaying variable inhibition of microbial activity were selected to develop models for establishing 2D QSAR by multiple linear regression analysis. The compounds in the selected series were characterized by spatial, molecular and electro topological descriptors using QSAR model of molecular design suite (V-Life MDS 3.5). Correlations between inhibitory activities and calculated predictor variables were established through multiple linear regression method. The whole dataset was divided into training set (17 compounds) and test set (05 compounds). The statistically significant best 2D QSAR model having correlation coefficient r² = 0.8686 and cross validated squared correlation coefficient q² = 0.7994 with external predictive ability of pred_r² = 0.6791 coefficient of correlation of predicted data set (pred_r²se) 0.0999 was developed by stepwise MLR method with the descriptors like SSCH₃, SdSE-index, SsssN Count and Xlogp. These results should serve as a guideline in designing more potent and selective antimicrobial and antifungal molecules.