Unraveling structural requirements of amino-pyrimidine T790M/L858R double mutant EGFR inhibitors: 2D and 3D QSAR study. (4th July 2018)

• Record Type: Journal Article
• Authors: Fatima, Shehnaz; Agarwal, Subhash Mohan
• Is Part Of: Journal of receptor and signal transduction research. Volume 38:Number 4(2018)
• Page Start: 299
• Page End: 306
• Publication Date: 2018-07-04
• Subjects: EGFR -- double mutant inhibitor -- QSAR -- TMLR; Cell receptors -- Periodicals; Cellular signal transduction -- Periodicals; 571.6
• DOI: 10.1080/10799893.2018.1494740
• Languages: English
• ISSNs: 1079-9893

Abstract

Abstract: EGFR is an important drug target in cancer. However, the ineffectiveness of first generation inhibitors due to the occurrence of a secondary mutation (T790M) results in the relapse of the disease. Identification of reversible inhibitors against T790M/L858R double mutants (TMLR) thus is a foremost requirement. In this study, various 2 D and 3 D Quantitative Structure–Activity Relationship models were built for amino-pyrimidine compounds with their known biological activity against TMLR mutants. The model developed using multiple linear regression statistical method via stepwise forward-backward variable selection technique showed the best results in terms of internal and external predictivity. The 2D-QSAR model indicated that the presence of electronegative atom, H-bond donors, moderate slogp, count of number of N atoms separated from O (T_N_O_4), 4pathClusterCount and number of S atom connected with two single bonds (SssSE-index), is required for increasing the inhibitory potential of compounds. Also, the 3D-QSAR model suggested that electronegative group at certain positions along with the presence of bulky groups is beneficial for good inhibition activity of the compounds. Thus, the QSAR models developed in the present work can be used for predicting the TMLR bioactivity of a new series of amino-pyrimidine derivatives. To the best of the author's knowledge, this is the first study which deals with the development of 2 D and 3D-QSAR models for double mutant TMLR inhibitors.