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首页> 外文期刊>Journal of receptor and signal transduction research >Unraveling structural requirements of amino-pyrimidine T790M/L858R double mutant EGFR inhibitors: 2D and 3D QSAR study
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Unraveling structural requirements of amino-pyrimidine T790M/L858R double mutant EGFR inhibitors: 2D and 3D QSAR study

机译:解开氨基 - 嘧啶T790M / L858R双突变体EGFR抑制剂的结构要求:2D和3D QSAR研究

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摘要

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.
机译:EGFR是癌症中的重要药物靶标。然而,由于发生二级突变(T790M)的发生导致第一代抑制剂的无效导致疾病的复发。因此,鉴定可逆抑制剂对T790M / L858R双突变体(TMLR)是最重要的要求。在该研究中,为氨基 - 嘧啶化合物具有针对TMLR突变体的已知生物活性的各种2d和3d定量结构 - 活性模型。通过逐步前后反向变量选择技术使用多元线性回归统计方法开发的模型显示了内部和外部预测性方面的最佳结果。 2D-QSAR模型表明,存在电致原子,H键供体,中等斜面,与与两个单个键连接的O(T_N_O_4),4PATHCLUSTCOUNT和S原子数分开的N原子数的数量(SSSSE索引) ,增加化合物的抑制潜力所必需的。此外,3D-QSAR模型表明某些位置的电负剂群随着庞大基团的存在而有利于化合物的良好抑制活性。因此,本作中开发的QSAR模型可用于预测新系列氨基 - 嘧啶衍生物的TMLR生物活性。据笔者所知的最佳知识,这是第一项研究,该研究涉及2D和3D-QSAR模型的开发,用于双突变体TMLR抑制剂。

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