Abstract

CONVENTIONAL QSAR STUDIES OF THIAZOLIDINONE DERIVATIVES AS POTENTIAL EPIDERMAL GROWTH FACTOR RECEPTOR INHIBITORS

Sanmati Kumar Jain*, Ravi Tripathi and Piyush Ghode

ABSTRACT

Conventional quantitative structure activity relationship (QSAR) analysis was performed on thiazolidinone analogues for their Epidermal Growth Factor inhibitory activity (EGFR inhibitors) using Molecular Design Suite (VLife MDS) software. Partial least squares regression (PLSR) analysis coupled with stepwise variable selection (forward-backward) method was applied to derive QSAR models and validated for statistical significance by internal and external validation. Statistically significant QSAR models were generated. Among them most significant model was found to have squared correlation coefficient (r2), cross validated correlation coefficient (q2) and predictive correlation coefficient (pred_r2) 0.8758, 0.8002 and 0.9141 respectively. The QSAR model indicates that the descriptors T_N_O_4 and RadiusOfGyration contribute (positively) 43.43% and 34.11% respectively to biological activity. Descriptor T_T_C_4 contributes (inversely) 22.46% to the biological activity.The QSAR study of these derivatives provides guidance for further lead optimization and designing of potent anticancer agents.

Keywords: Thiazolidinone, EGFR, QSAR, anticancer.