Literature DB >> 30994691

The role of computer-assisted structure elucidation (CASE) programs in the structure elucidation of complex natural products.

Darcy C Burns1, Eugene P Mazzola, William F Reynolds.   

Abstract

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.

Year:  2019        PMID: 30994691     DOI: 10.1039/c9np00007k

Source DB:  PubMed          Journal:  Nat Prod Rep        ISSN: 0265-0568            Impact factor:   13.423


  10 in total

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Journal:  Chem Rev       Date:  2020-11-09       Impact factor: 60.622

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  10 in total

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