Unraveling structural requirements of amino-pyrimidine T790M/L858R double mutant EGFR inhibitors: 2D and 3D QSAR study

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.

表皮生长因子受体（EGFR）是癌症领域重要的药物作用靶点。然而，由于继发性突变（T790M）的出现，第一代抑制剂会失效，进而导致疾病复发。因此，研发针对T790M/L858R双突变体（TMLR）的可逆抑制剂，成为当前最为迫切的需求。本研究针对已知对TMLR突变体具有生物活性的氨基嘧啶类化合物，构建了多种二维（2D）及三维（3D）定量构效关系模型。通过逐步前后向变量选择法结合多元线性回归统计方法构建的模型，在内部及外部预测能力方面表现最优。2D-QSAR模型结果显示，若要提升化合物的抑制活性，分子需具备电负性原子、氢键供体、适度的slogp值、与氧原子相隔的氮原子计数（T_N_O_4）、4pathClusterCount，以及与两个单键相连的硫原子数量（SssSE-index）。此外，3D-QSAR模型表明，在特定位置引入电负性基团并搭配大体积基团，有助于提升化合物的抑制活性。因此，本研究构建的QSAR模型可用于预测一系列新型氨基嘧啶类衍生物对TMLR的生物活性。据作者所知，本研究是首个针对TMLR双突变体抑制剂构建2D及3D-QSAR模型的相关研究。