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Towards predictive inhibitor design for the EGFR autophosphorylation activity.

机译:趋向于针对EGFR自磷酸化活性的预测性抑制剂设计。

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Inhibition of the epidermal growth factor receptor (EGFR) tyrosine kinase is one among the pivotal targets for the treatment of cancer. The structural investigation directly halting the EGFR autophosphorylation is expected to give insights into alternatively blocking the aberrant activity of EGFR. The three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed from the systematic search conformer-based alignment method. Models derived from the training set of 95 compounds showed superior CoMFA as compared with CoMSIA (CoMFA: q(2)=0.50, r(2)=0.74, N=5, F=48.83, r(2)(pred)=0.56 while CoMSIA: q(2)=0.48, r(2)=0.62, N=2, F=72.70, r(2)(pred)=0.51). Validation of the models by test set prediction of 26 compounds was in good agreement with the experimental results. Further validation by molecular docking superimposition into the 3D-QSAR contour maps was found in agreement with each other. We identified that the structural modification of compound 19 by attachment of a bulky group on pyrrole ring along with an electronegative group on quinazoline ring and a hydrogen-bond donor on methyl formate opens a new avenue towards the optimization of novel chemical entities to develop potent inhibitors for EGFR autophosphorylation.
机译:表皮生长因子受体(EGFR)酪氨酸激酶的抑制是治疗癌症的关键目标之一。直接停止EGFR自磷酸化的结构研究有望为替代性阻断EGFR异常活性提供见识。三维定量结构-活性关系(3D-QSAR)模型是从基于系统搜索符合者的比对方法开发的。来自95种化合物的训练集的模型显示出比CoMSIA更好的CoMFA(CoMFA:q(2)= 0.50,r(2)= 0.74,N = 5,F = 48.83,r(2)(pred)= 0.56而CoMSIA:q(2)= 0.48,r(2)= 0.62,N = 2,F = 72.70,r(2)(pred)= 0.51)。通过测试集预测的26种化合物对模型的验证与实验结果非常吻合。通过彼此对接,发现通过分子对接叠加到3D-QSAR等高线图中的进一步验证。我们发现,通过吡咯环上的一个庞大基团与喹唑啉环上的一个负电基团和甲酸甲酯上的一个氢键供体的连接,对化合物19进行结构修饰,为优化新型化学实体以开发有效的抑制剂开辟了一条新途径用于EGFR自身磷酸化。

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