Literature DB >> 11560068

The automation of natural product structure elucidation.

C Steinbeck1.   

Abstract

The last two or three years have seen exciting developments in the field of computer-assisted structure elucidation (CASE) with a number of programs becoming commercially or freely available. This was the conditio sine qua non for CASE to be widely applied in the daily work of bench chemists and spectroscopists. A number of promising applications have been published in the area of structure generators, deterministic and stochastic CASE tools and property predictions, including the automatic distinction between natural products and artificial compounds, as well as the determination of 3-D structure from a connection table based on IR spectroscopy. Advancements in coupling techniques between chromatographic and spectroscopic methods demonstrate progress towards a fully automated structure elucidation or identification process starting at the earliest steps of obtaining crude extracts.

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Year:  2001        PMID: 11560068

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  2 in total

1.  Building blocks for automated elucidation of metabolites: machine learning methods for NMR prediction.

Authors:  Stefan Kuhn; Björn Egert; Steffen Neumann; Christoph Steinbeck
Journal:  BMC Bioinformatics       Date:  2008-09-25       Impact factor: 3.169

2.  Building blocks for automated elucidation of metabolites: natural product-likeness for candidate ranking.

Authors:  Kalai Vanii Jayaseelan; Christoph Steinbeck
Journal:  BMC Bioinformatics       Date:  2014-07-05       Impact factor: 3.169

  2 in total

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