Automated structure elucidation of phytochemicals

Trends in Phytochemical Research

مقاله 1، دوره 1، شماره 3، آذر 2017، صفحه 109-110   

نوع مقاله: Guest editorial

نویسندگان

Lutfun Nahar^* ؛ Satyajit D. Sarker

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

چکیده

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.

کلیدواژه‌ها

Chemical compounds؛ Chemical scaffolds؛ HMBC؛ MS؛ NMR؛ Phytochemical data

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