波谱学杂志 ›› 2019, Vol. 36 ›› Issue (3): 359-376.doi: 10.11938/cjmr20182682

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量子化学计算核磁共振参数在天然产物结构鉴定中的应用

胡坤, 孙汉董, 普诺·白玛丹增   

  1. 植物化学与西部植物资源持续利用国家重点实验室(中国科学院 昆明植物研究所), 云南 昆明 650201
  • 收稿日期:2018-09-10 发布日期:2018-10-30
  • 通讯作者: 普诺·白玛丹增 E-mail:punopematenzin@mail.kib.ac.cn
  • 基金资助:
    国家自然科学基金资助项目(81874298,81673329).

Application of Quantum Chemical Calculation of Nuclear Magnetic Resonance Parameters in the Structure Elucidation of Natural Products

HU Kun, SUN Han-dong, PUNO Pema-tenzin   

  1. State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
  • Received:2018-09-10 Published:2018-10-30

摘要: 在过去的十多年中,伴随着量子化学理论与计算机硬件、软件的不断发展,量子化学计算核磁共振参数(quantum chemical calculation of nuclear magnetic resonance parameters,qcc-NMR)的方法也日趋成熟,这些方法往往在较小的计算成本下就可以获得比较理想的计算精度,且对于NMR参数计算结果的分析也从最初的简单统计学方法逐渐发展为基于更为复杂的统计学原理或人工神经网络的方法,这些进展都促使qcc-NMR这一工具在天然产物研究中得到了越来越广泛的应用,从而对传统的NMR技术、质谱,以及各种光谱技术做出了重要补充.本文对qcc-NMR在天然产物结构鉴定中的应用进行了综述,并对近年来的一些应用实例进行了较为详细的分析.

关键词: 量子化学计算, 核磁共振(NMR)参数, 天然产物, 结构鉴定, DP4可能性分析

Abstract: With the continuous development of quantum chemical theories and advances in computer hardware and software, the methods for quantum chemical calculation of nuclear magnetic resonance parameters (qcc-NMR) are improved significantly in the past decade. With these methods, accurate calculated results can often be obtained at a relatively low cost. Furthermore, the methods for result analysis have been advanced from simple statistical parameters to more sophisticated procedures based on more complicated statistical methods or artificial neuron networks, etc. These advances make qcc-NMR a significant complement to traditional spectrometric methods, and more and more useful in natural product research. In this paper, the application of qcc-NMR in natural product research is reviewed. Representative researches featuring the use of qcc-NMR are highlighted.

Key words: quantum chemical calculation, nuclear magnetic resonance (NMR) parameters, natural product, structure elucidation, DP4 probability analysis

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