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
antimicrobial agents
derivatives,
quantitative
structure
activity
relationship,
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.