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首页> 外文期刊>Medicinal chemistry research: an international journal for rapid communications on design and mechanisms of action of biologically active agents >Design of novel anaplastic lymphoma kinase (ALK) inhibitors based on predictive 3D QSAR models using different alignment strategies
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Design of novel anaplastic lymphoma kinase (ALK) inhibitors based on predictive 3D QSAR models using different alignment strategies

机译:基于预测的3D QSAR模型,使用不同的对位策略设计新型间变性淋巴瘤激酶(ALK)抑制剂

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摘要

Anaplastic lymphoma kinase (ALK) is involved in many signaling mechanisms that lead to cell-cycle progression; overexpression of ALK has been found in many types of cancers. ALK is a recognized target for the development of small-molecule inhibitors for the treatment of cancer. In this study, a diverse set of 71 ALK inhibitors were aligned by three different methods (pharmacophore, docking-based, and rigid body (Distill) alignment) for the development of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. The best 3D QSAR models were obtained, which used rigid body (Distill) alignment of test and training set molecules. CoMFA and CoMSIA models were found statistically significant with leave-one-out correlation coefficients (q~2) of 0.816 and 0.838, respectively; cross-validated coefficients (r_(cv)~2) of 0.812 and 0.837, respectively; and conventional coefficients (r2) of 0.969 and 0.966, respectively. QSAR models were validated by a test set of 14 compounds giving satisfactory prediction of correlation coefficients (r_(pred)~2) of 0.910 and 0.904 for CoMFA and CoMSIA models, respectively. Based on the generated contour maps, we have designed 10 novel ALK inhibitors and predicted their activities. Finally, molecular docking study was performed for designed molecules. The designed compounds showed good potential to be used as ALK inhibitors.
机译:间变性淋巴瘤激酶(ALK)参与导致细胞周期进程的许多信号传导机制。在许多类型的癌症中都发现了ALK的过度表达。 ALK是开发用于治疗癌症的小分子抑制剂的公认目标。在这项研究中,通过三种不同的方法(药效团,基于对接和刚体(蒸馏)比对)对71种不同的ALK抑制剂进行了比对,以开发比较分子场分析(CoMFA)和比较分子相似性指数分析( CoMSIA)模型。获得了最佳的3D QSAR模型,该模型使用测试和训练集分子的刚体(蒸馏)比对。发现CoMFA和CoMSIA模型具有统计学意义,留一法相关系数(q〜2)分别为0.816和0.838。交叉验证系数(r_(cv)〜2)分别为0.812和0.837;传统系数(r2)分别为0.969和0.966。 QSAR模型通过14种化合物的测试集进行了验证,分别对CoMFA和CoMSIA模型给出了令人满意的0.910和0.904的相关系数(r_(pred)〜2)预测。基于生成的轮廓图,我们设计了10种新型ALK抑制剂并预测了它们的活性。最后,对设计的分子进行了分子对接研究。设计的化合物显示出良好的潜力,可用作ALK抑制剂。

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