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Updated: May 24, 2026
Facile Preparation of 4-Substituted Quinazoline Derivatives
Published on: February 15, 2016
2D and 3D-QSAR study on 4-anilinoquinozaline derivatives as potent apoptosis inducer and efficacious anticancer agent
Vivek Kumar Vyas1, Manjunath Ghate, Hitesh Katariya
1Department of Pharmaceutical Chemistry, Institute of Pharmacy, Nirma University, S,G, Highway, Chharodi, Ahmedabad 382 481, Gujarat, India. vicky_1744@yahoo.com.
Background:
Apoptosis is known as programmed cell death that plays an important role in tumor biology.
Methods:
In this study, apoptosis-inducing activity is predicted by using a QSAR modeling approach for a series of 4-anilinoquinozaline derivatives. 2D-QSAR model for the prediction of apoptosis-inducing activity was obtained by applying multiple linear regression giving r2 = 0.8225 and q2 = 0.7626, principal component regression giving r2 = 0.7539 and q2 = 0.6669 and partial least squares giving r2 = 0.8237 and q2 = 0.6224.
Results:
QSAR study revealed that alignment-independent descriptors and distance-based topology index are the most important descriptors in predicting apoptosis-inducing activity. 3D-QSAR study was performed using k-nearest neighbor molecular field analysis (kNN-MFA) approach for both electrostatic and steric fields. Three different kNN-MFA 3D-QSAR methods (SW-FB, SA, and GA) were used for the development of models and tested successfully for internal (q2 > 0.62) and external (predictive r2 > 0.52) validation criteria. Thus, 3D-QSAR models showed that electrostatic effects dominantly determine the binding affinities.
Conclusions:
The QSAR models developed in this study would be useful for the development of new apoptosis inducer as anticancer agents.
