3D-QSAR and Docking Studies of 4-morpholinopyrrolopyrimidine Derivatives as Potent mTOR Inhibitors

Shao-Teng      Wang; Yong      Ai; Chu      Tang; Fa-Jun      Song; Ping-Hua      Sun

Abstract

The mammalian target of rapamycin (mTOR) has become an attractive target for the treatment of cancer. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies was performed on a series of 4- morpholinopyrrolopyrimidine derivatives and used to identify the most important features impacting their activity and their potential for predictability. The CoMFA and CoMSIA models using 31 molecules in the training set, gave r2 cv values of 0.832 and 0.815, r2 values of 0.969 and 0.951, respectively. Furthermore, the external validation was applied and indicated that our CoMFA and CoMSIA models were robust enough to predict the activities of test compounds with rpred 2 values of 0.975 and 0.968, r02 values of 0.971 and 0.972, rm2 values of 0.926 and 0.813, respectively. The contour maps produced by the CoMFA and CoMSIA models were employed to rationalize the key structural requirements responsible for the activity. Molecular docking was used to investigate the binding mode between these compounds and the receptor and furthermore, verify the reliability of the 3D-QSAR models. The information obtained from molecular modeling studies helped in understanding the structure-activity relationship of these compounds and served as a useful guide for the design of 4-morpholinopyrrolopyrimidine derivatives with desired activity. Thus a set of new analogues were designed by utilizing the results revealed in the present study, and were predicted with significantly improved potencies in the developed models.

Keywords: 4-morpholinopyrrolopyrimidine, 3D-QSAR, CoMFA, CoMSIA, Docking, mTOR, Serine/Threonine Kinase, Phosphoinositide 3-kinase, Cytoskeleton Organization, Protein Synthesis, Ribosomal Biogenesis, Docking approaches, Hydrogen Bonding Intercations, Molecular Modeling