2D QSAR Studies on a Series of Quinazoline Derivatives as Tyrosine Kinase (EGFR) Inhibitor: An Approach to Design Anticancer Agents

摘要

Abstract: Epidermal growth factor receptor (EGFR) protein tyrosine kinases (PTKs) are known for its role in cancer. nQSAR studies were performed on a set of 137 analogs of quinazoline using MDS vlife science QSAR plus module by us-ning Multiple Linear Regression (MLR), Principal Component Regression (PCR) and Partial Least Squares (PLS) Regres-nsion methods. Among these, MLR method has shown a very promising result as compared to other two methods and a nQSAR model was generated by a training set of 100 molecules with correlation coefficient (rn2n) of 0.884, significant cross nvalidated correlation coefficient (q2n) of 0.800, F test of 39.5149, rn2n for external test set (pred_rn2n) 0.5902, coefficient of cor-nrelation of predicted data set (pred_rn2nse) 0.7438 and degree of freedom 83. In the selected descriptors, alignment inde-npendent descriptors T_2_C_5 (11.74%) and T_2_O_7 (-11.27%) are the most important descriptors in predicting EGFR ninhibitory activity. Electron withdrawing group at anilino quinazolines enhances the activity as evident by positive value nof T_F_Cl_4 (2.07%). In addition, for quinazoline substituents, estate contribution descriptors, SaaCHE –index and Ssss nNE-index have a large deactivating effect.