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基于分类算法的预测模型,用于预测可能作为线粒体ATP敏感性钾通道开放剂具有活性的化合物。

Predictive models, based on classification algorithms, for compounds potentially active as mitochondrial ATP-sensitive potassium channel openers.

作者信息

Coi Alessio, Bianucci Anna Maria, Calderone Vincenzo, Testai Lara, Digiacomo Maria, Rapposelli Simona, Balsamo Aldo

机构信息

Dipartimento di Scienze Farmaceutiche, Università di Pisa, Via Bonanno 6, 56126 Pisa, Italy.

出版信息

Bioorg Med Chem. 2009 Aug 1;17(15):5565-71. doi: 10.1016/j.bmc.2009.06.028. Epub 2009 Jun 21.

DOI:10.1016/j.bmc.2009.06.028
PMID:19595602
Abstract

Heart mitochondrial ATP-sensitive potassium channel (mito-K(ATP) channels) are deeply implicated in the self-defense mechanism of ischemic preconditioning. Therefore, exogenous molecules activating these channels are considered as a promising pharmacological tool to reduce the myocardial injury deriving from ischemia/reperfusion events. In our laboratory, a series of 4-spiro-substituted benzopyran derivatives were earlier synthesized and some of them exhibited anti-ischemic properties. In this study, the above compounds are exploited in order to develop QSAR models, based on classification approaches, capable of discriminating between the ones acting as cardioprotective agents and those that are unable to elicit such a property. Molecules belonging to the whole dataset were subjected to CODESSA and E-Dragon calculations in order to compute a large number of molecular descriptors enabling the construction of classification models. Based on the two program packages used, two different experiments were carried out, with the aim of identify batteries of models to be exploited for designing new cardioprotective agents from libraries of new chemical entities. Both model batteries satisfy the rigorous criteria adopted for the validation, either when tested on the training and test set, according to the most straightforward protocol, and when tested on an additional prediction set. They were proven to ensure successful applications in the field of cardioprotective agent design.

摘要

心脏线粒体ATP敏感性钾通道(线粒体KATP通道)与缺血预处理的自我防御机制密切相关。因此,激活这些通道的外源性分子被认为是一种有前景的药理学工具,可减少缺血/再灌注事件引起的心肌损伤。在我们实验室,早期合成了一系列4-螺取代苯并吡喃衍生物,其中一些具有抗缺血特性。在本研究中,利用上述化合物开发基于分类方法的QSAR模型,该模型能够区分具有心脏保护作用的化合物和不具有该特性的化合物。对整个数据集中的分子进行CODESSA和E-Dragon计算,以计算大量分子描述符,从而构建分类模型。基于所使用的两个程序包,进行了两个不同的实验,目的是确定用于从新化学实体库中设计新型心脏保护剂的模型组。当按照最直接的方案在训练集和测试集上进行测试时,以及在额外的预测集上进行测试时,这两组模型均满足验证所采用的严格标准。事实证明,它们可确保在心脏保护剂设计领域的成功应用。

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