...
首页> 外文期刊>Molecular informatics >Predictive Models for Halogen-bond Basicity of Binding Sites of Polyfunctional Molecules
【24h】

Predictive Models for Halogen-bond Basicity of Binding Sites of Polyfunctional Molecules

机译:多功能分子结合位点的卤素键碱性预测模型

获取原文
获取原文并翻译 | 示例
           

摘要

Halogen bonding (XB) strength assesses the ability of an electron-enriched group to be involved in complexes with polarizable electrophilic halogenated or diatomic halogen molecules. Here, we report QSPR models of XB of particular relevance for an efficient screening of large sets of compounds. The basicity is described by pK(BI2), the decimal logarithm of the experimental 1:1 (B:I-2) complexation constant K of organic compounds (B) with diiodine (I-2) as a reference halogen-bond donor in alkanes at 298K. Modeling involved ISIDA fragment descriptors, using SVM and MLR methods on a set of 598 organic compounds. Developed models were then challenged to make predictions for an external test set of 11 polyfunctional compounds for which unambiguous assignment of the measured effective complexation constant to specific groups out of the putative acceptor sites is not granted. At this stage, developed models were used to predict pK(BI2) of all putative acceptor sites, followed by an estimation of the predicted effective complexation constant using the ChemEqui program. The best consensus models perform well both in cross-validation (root mean squared error RMSE=0.39-0.47logK(BI2) units) and external predictions (RMSE=0.49). The SVM models are implemented on our website (http://infochim.u-strasbg.fr/webserv/VSEngine.html) together with the estimation of their applicability domain and an automatic detection of potential halogen-bond acceptor atoms.
机译:卤素键(XB)强度评估富电子基团与可极化的亲电子卤代或双原子卤素分子形成复合物的能力。在这里,我们报告了XB的QSPR模型,该模型对于有效筛查大量化合物具有特殊的意义。碱性由pK(BI2)来描述,pK(BI2)是有机化合物(B)与二碘(I-2)作为参考卤素键供体的实验1:1(B:I-2)络合常数K的十进制对数。 298K的烷烃。使用SVM和MLR方法对一组598种有机化合物进行建模,涉及ISIDA片段描述符。然后挑战已开发的模型以预测11种多官能化合物的外部测试集,对于这些测试,不允许将测得的有效络合常数明确分配给假定受体部位以外的特定基团。在这一阶段,已开发的模型用于预测所有推定受体位点的pK(BI2),然后使用ChemEqui程序估算预测的有效络合常数。最佳共识模型在交叉验证(均方根误差RMSE = 0.39-0.47logK(BI2)单位)和外部预测(RMSE = 0.49)方面均表现良好。 SVM模型可在我们的网站(http://infochim.u-strasbg.fr/webserv/VSEngine.html)上实现,并估算其适用范围并自动检测潜在的卤素键受体原子。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号