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首页> 外文期刊>Tetrahedron letters: The International Journal for the Rapid Publication of Preliminary Communications in Organic Chemistry >Structure-based predictions of ~1H NMR chemical shifts of sesquiterpene lactones using neural networks
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Structure-based predictions of ~1H NMR chemical shifts of sesquiterpene lactones using neural networks

机译:基于神经网络的倍半萜内酯〜1H NMR化学位移的基于结构的预测

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摘要

In this work the prediction of 'H NMR chemical shifts of CH_n protons of sesquiterpene lactones by means of neural networks is described.This method is based on the incorporation of experimental chemical shifts of protons of sesquiterpene lactones as additional memory of an associative neural network system previously trained with chemical shifts of other organic compounds.One advantage of this method is its ability to distinguish between CH_2 diastereotopic protons belonging to rigid substructures since stereochemistry is considered.This is achieved via the automatic conversion of the 2D structure diagram into a 3D molecular structure.The predicted ~1H NMR chemical shifts of the sesquiterpene lactones showed a high level of accuracy.This is the first report on a fully automatic proton assignment of structures of sesquiterpene lactones of an accuracy that allows its use in structure elucidation.
机译:在这项工作中,描述了通过神经网络预测倍半萜烯内酯CH_n质子的1 H NMR化学位移。该方法基于结合倍半萜烯内酯的质子实验化学位移作为联想神经网络系统的附加记忆这种方法的一个优点是,由于考虑了立体化学,因此能够区分属于刚性亚结构的CH_2非对映质子,这是通过将2D结构图自动转换为3D分子结构来实现的。倍半萜内酯的〜1H NMR化学位移预测具有很高的准确性,这是关于倍半萜内酯结构的全自动质子分配的首次报道,该准确度可使其用于结构阐明。

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