EGFR

Epidermal Growth Factor Receptor (EGFR) is known to play vital role in many cellular signalling pathways and hence is considered as a potent target for cancer. Inhibition of this enzyme has been reported to be beneficial by various workers. QSAR study of Quinazolines as EGFR was performed using accelrys discovery studio client (DSV-Version 3.0) as the modelling tool. A total of 67 selected molecules were considered for the development of QSAR model. Partial least square model of the data generated exhibited a very good linear relation between the training set of compounds with that of the reported activity as well as the test set of compounds with the predicted activity. The 4 statistical analysis performed revealed following observations; Training data set r2= 0.701, q2 (Cross validated r2) = 0.616 validated by internal validation with correlation of coefficient (r2) of 0.848 and cross validated r2 (q2) of 0.573 and external set of compounds with a predictive correlation of coefficient of 0.900.  A total of 9 descripters pruned on the study explained the structural correlation of quinazolines with EGFR. The model developed can be used to predict bioefficacy of unknown molecules 4-[1,3-benzothiazol-2-yl]-N-[(1E)-(4-nitrophenyl)methylene]aniline as EGFR inhibitors. Further a hypothetical model to describe the interaction between the predicted molecules with EGFR is proposed and this hypothetical model explains the possibility of Met769 and Gln767 as the possible binding sites. The activity is observed in the preliminary cytotoxic activity (MTT assay). The study calls for the development of the molecules predicted as bio efficacious in this model and a quantitative inhibitory analysis of EGFR. Key word: EGFR, QSAR, r2, q2