Department of Chemistry, University of Toronto, Toronto, Ontario, Canada.
Nat Prod Rep. 2019 Jun 19;36(6):919-933. doi: 10.1039/c9np00007k.
Covering: up to the end of December, 2018 There are still a disturbing number of incorrect natural product structure elucidations reported in the literature. The use of Computer-Assisted Structure Elucidation (CASE) programs can minimize this risk by generating all structures that are consistent with the input data and by ranking these structures in order of probability. They can successfully determine structures for complex natural products, with the possible exception of compounds with very few protons. Current CASE programs utilize mainly 2D COSY and HMBC correlation data for structure generation with a starting assumption that all observed peaks are due to pairs of atoms no more than 3 bonds apart. We discuss these assumptions and the problems that occur when they are violated. We also discuss the advantages and disadvantages of other types of 2D data that could be included at the structure generation stage. Four different CASE programs are described with particular emphasis on how they deal with the presence of longer range correlation peaks. These programs provide only planar skeletal structures. However, a new program that relies on different types of stereospecific NMR data to determine 3D structures is also described. Other types of computer assistance for structure elucidation are discussed, including the increasing use of theoretical DFT calculations to determine 3D structures and to predict chemical shifts. Finally, we suggest possible improvements in these programs and suggest that a challenge match between the developers of current CASE programs would be useful.
截至 2018 年 12 月底,文献中仍有大量不正确的天然产物结构解析报道。使用计算机辅助结构解析(CASE)程序可以通过生成与输入数据一致的所有结构并按概率对这些结构进行排序,从而最大程度地降低这种风险。它们可以成功确定复杂天然产物的结构,但可能除外的是质子非常少的化合物。当前的 CASE 程序主要利用 2D COSY 和 HMBC 相关数据进行结构生成,其起始假设是所有观察到的峰都归因于不超过 3 个键的原子对。我们讨论了这些假设以及违反这些假设时出现的问题。我们还讨论了在结构生成阶段可以包含的其他类型的二维数据的优缺点。描述了四种不同的 CASE 程序,特别强调了它们如何处理长程相关峰的存在。这些程序仅提供平面骨架结构。然而,还描述了一个依赖于不同类型立体特异性 NMR 数据来确定 3D 结构的新程序。还讨论了其他类型的计算机辅助结构解析,包括越来越多地使用理论 DFT 计算来确定 3D 结构和预测化学位移。最后,我们对这些程序提出了可能的改进建议,并建议当前 CASE 程序的开发人员之间进行挑战比赛将是有用的。