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Activity landscape sweeping: insights into the mechanism of inhibition and optimization of DNMT1 inhibitors

机译:活动概况:DNMT1抑制剂抑制和优化机制的见解

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摘要

The interest in developing inhibitors of DNA methyltransferases (IDNMT) as modifiers of epigenetic features for the treatment of several chronic diseases is rapidly increasing. Herein, we present insights of a chemoinformatic characterization of IDNMT focused on the analysis of the chemical space and structure-activity relationships (SAR) using activity landscape modeling (ALM). Analysis of the chemical space revealed two main groups of compounds whose chemical structures are associated with either cofactor analogs or non-nucleoside compounds. The ALM showed that non-nucleoside compounds have a continuous SAR while cofactor analogs have a rough SAR with several deep activity cliffs. Molecular modeling helped to explain the structural basis of the activity cliffs. The significance of the results is threefold: (1) the combined analysis of chemical space with activity landscape gave rise to a novel 'activity landscape sweeping' strategy that enabled a better structure-based interpretation of the SAR; (2) it is feasible - and advisable - to develop predictive models for non-nucleoside IDNMT studied in this work, and (3) structure-based interpretation of the SAR gave clear insights into the molecular mechanism of inhibition of novel IDNMT suggesting specific strategies to optimize the activity of leads compounds.
机译:对开发作为表观遗传学特征修饰剂的DNA甲基转移酶抑制剂(IDNMT)的兴趣正在迅速增加。在这里,我们介绍IDNMT的化学信息学表征的见解,重点在于使用活动景观模型(ALM)分析化学空间和结构-活性关系(SAR)。化学空间的分析揭示了两类主要化合物,它们的化学结构与辅因子类似物或非核苷化合物有关。 ALM表明,非核苷化合物具有连续的SAR,而辅因子类似物具有粗糙的SAR,且具有多个深部活性悬崖。分子建模有助于解释活动悬崖的结构基础。结果的意义有三点:(1)将化学空间与活动态结合起来,产生了一种新颖的“活动态扫掠”策略,从而可以更好地基于结构对SAR进行解释。 (2)为这项研究中研究的非核苷IDNMT建立预测模型是可行且可取的,(3)SAR的基于结构的解释为抑制新型IDNMT的分子机制提供了清晰的见解,并提出了具体策略优化铅化合物的活性。

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