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基于ISIDA局部描述符的单个氢键强度定量构效关系建模:迈向多功能分子的一步。

Individual Hydrogen-Bond Strength QSPR Modelling with ISIDA Local Descriptors: a Step Towards Polyfunctional Molecules.

作者信息

Ruggiu Fiorella, Solov'ev Vitaly, Marcou Gilles, Horvath Dragos, Graton Jérôme, Le Questel Jean-Yves, Varnek Alexandre

机构信息

Laboratoire de Chémoinformatique, UMR 7140 CNRS, Université de Strasbourg, 1, rue Blaise Pascal, 67000 Strasbourg, France phone:+33368851560.

Institute of Physical Chemistry and Electrochemistry, Russian Academy of Sciences, Leninskiy prospect, 31a, 119991, Moscow, Russian Federation.

出版信息

Mol Inform. 2014 Jun;33(6-7):477-87. doi: 10.1002/minf.201400032. Epub 2014 Jun 17.

Abstract

Here, we introduce new ISIDA fragment descriptors able to describe "local" properties related to selected atoms or molecular fragments. These descriptors have been applied for QSPR modelling of the H-bond basicity scale pKBHX , measured by the 1 : 1 complexation constant of a series of organic acceptors (H-bond bases) with 4-fluorophenol as the reference H-bond donor in CCl4 at 298 K. Unlike previous QSPR studies of H-bond complexation, the models based on these new descriptors are able to predict the H-bond basicity of different acceptor centres on the same polyfunctional molecule. QSPR models were obtained using support vector machine and ensemble multiple linear regression methods on a set of 537 organic compounds including 5 bifunctional molecules. They were validated with cross-validation procedures and with two external test sets. The best model displays good predictive performance on a large test set of 451 mono- and bifunctional molecules: a root-mean squared error RMSE=0.26 and a determination coefficient R(2) =0.91. It is implemented on our website (http://infochim.u-strasbg.fr/webserv/VSEngine.html) together with the estimation of its applicability domain and an automatic detection of potential H-bond acceptors.

摘要

在此,我们引入了新的ISIDA片段描述符,其能够描述与选定原子或分子片段相关的“局部”性质。这些描述符已应用于氢键碱度标度pKBHX的定量构效关系(QSPR)建模,该标度通过一系列有机受体(氢键碱)与4-氟苯酚在298 K的四氯化碳中作为参考氢键供体的1 : 1络合常数来测量。与先前关于氢键络合的QSPR研究不同,基于这些新描述符的模型能够预测同一多功能分子上不同受体中心的氢键碱度。使用支持向量机和集成多元线性回归方法,对包括5个双功能分子在内的537种有机化合物进行建模,得到了QSPR模型。通过交叉验证程序和两个外部测试集对模型进行了验证。最佳模型在由451个单功能和双功能分子组成的大型测试集上显示出良好的预测性能:均方根误差RMSE = 0.26,决定系数R(2) = 0.91。该模型连同其适用域的估计以及潜在氢键受体的自动检测功能一起在我们的网站(http://infochim.u-strasbg.fr/webserv/VSEngine.html)上实现。

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