Quantitative Structure Activity Relationship (QSAR) Based on Electronic Descriptors and Docking Studies of Quinazoline Derivatives for Anticancer Activity

Abstract

Quantitative structure-activity relationship (QSAR) based on electronic descriptors had been conducted on 2,3-dihydro-[1,4]dioxino[2,3-f]quinazoline analogues as anticancer using DFT/B3LYP method. The best QSAR equation described as follow: Log IC50 = -11.688 + (-35.522×qC6) + (-21.055×qC10) + (-85.682×qC12) + (-32.997×qO22) + (-85.129 EHOMO) + (19.724×ELUMO). Statistical value of R2 = 0.8732, rm2 = 0.7935, r2-r02/r2 = 0.0118, PRESS = 1.5727 and Fcalc/Ftable = 2.4067 used as external validation. Atomic net charge showed as the most important descriptor to predict activity and design new molecule. Following QSAR analysis, Lipinski rules was applied to filter the design compound due to physicochemical properties and resulted that all filtered compounds did not violate the rules. Docking analysis was conducted to determine interaction between proposed compounds and EGFR protein. Critical hydrogen bond was found in Met769 residue suggesting that proposed compounds could be used to inhibit EGFR protein.

Design of New Quinazoline Derivative as EGFR (Epidermal Growth Factor Receptor) Inhibitor through Molecular Docking and Dynamics Simulation

“…The advantage of molecular docking in designing a new inhibitor does not require a large amount of data or only employ some molecules as the lead compounds. Previous research had designed quinazoline derivative compounds by using quantitative structureactivity relationship (QSAR) analysis in large data compounds [16][17][18] and studied the stability of hydrogen bond formed through compound and protein [19][20][21][22]. However, designing a new EGFR inhibitor using a molecular docking approach of the lead compounds such as erlotinib, afatinib, and WZ4002 has never been done.…”