Quantitative Structure Activity Relationship Studies of Some New 4-Thiazolidinone Derivatives as Antimicrobial Agents

Abstract

In the present study, quantitative structure activity relationship (QSAR) studies have been performed on series of 24 compounds of 4-thiazolidinone derivatives with antimicrobial activity using Chemoffice version 8.0 software. The QSAR models have been developed by using multiple linear regressions in order to identify descriptors, which are actually focusing towards the biological activity. Leave one out (LOO) method was employed in cross validation analysis to validate the developed model. The best predictive QSAR model derived, had r²cv of 0.76, non-cross validated r² of 0.9, and predictive r² for test set 0.87. The model reveals that some multidimensional steric factors and electronic factors like HF (heat of formation), PMI-Y (principle moment of inertia-Y axis), D2 (Dipole energy) and electronic energy show strong correlation with biological activity. These models are expected to be useful as antimicrobial agents. Training set was formed by selecting 19 compounds from original series. Test set compounds were selected randomly. The validation techniques utilized in this work illustrate the accuracy and robustness of the constructed model by calculating its fitness on training and test set.

Keywords: 4-thiazolidinone derivatives, quantitative structure activity relationship, antimicrobial agents

Cite this Article

Blessy Jacob, Bisht Lata K, Vineeth Chandy. Quantitative Structure Activity Relationship Studies of Some New 4-Thiazolidinone Derivatives as Antimicrobial Agents. Research and Reviews: A Journal of Pharmaceutical Science. 2017; 8(2): 1–3p.