Automated structure elucidation of phytochemicals

Document Type: Guest editorial

Authors

Medicinal Chemistry and Natural Products Research Group, School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool L3 3AF, UK

Abstract

Plants produce a variety of chemical compounds, and plants have been the main source of new chemical entities and novel chemical scaffolds or templates, unfolding new challenges for organic synthetic chemists to explore appropriate synthetic routes for their total synthesis. Because of the unique chemical diversity offered by plants, it is often a tedious and complicated process when it comes to structure elucidation of phytochemicals. Recent advances in spectroscopic techniques, particularly in NMR and MS methodologies, have provided various tools that assist phytochemists with the structure elucidation of known or new phytochemicals. However, spectroscopic data interpretation manually requires significant experience and expertise, knowledge, intellectual ability and patience; often the manual process can be quite time consuming and even be frustrating. Over the last several decades, especially with the phenomenal progress in computation and applications of artificial intelligence and various mathematical modelling, several automated spectral data interpretation and structure elucidation software have become available to the phytochemists. These automated tools, not necessarily have replaced human intelligence or efforts, but certainly have facilitated the process, and improved the accuracy of structure elucidation of phytochemicals.

Keywords

References

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Trends in Phytochemical Research

Volume 1, Issue 3
Summer 2017
Pages 109-110

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History

  • Receive Date: 27 August 2017
  • Accept Date: 27 August 2017

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