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Enhancing Efficiency of Natural Product Structure Revision: Leveraging CASE and DFT over Total Synthesis.
Elyashberg, Mikhail; Tyagarajan, Sriram; Mandal, Mihir; Buevich, Alexei V.
Afiliação
  • Elyashberg M; Advanced Chemistry Development Inc. (ACD/Labs), Toronto, ON M5C 1B5, Canada.
  • Tyagarajan S; Medicinal Chemistry, Merck & Co., Inc., Kenilworth, NJ 07033, USA.
  • Mandal M; Medicinal Chemistry, Merck & Co., Inc., Kenilworth, NJ 07033, USA.
  • Buevich AV; Analytical Research and Development, Merck & Co., Inc., Kenilworth, NJ 07033, USA.
Molecules ; 28(9)2023 Apr 28.
Article em En | MEDLINE | ID: mdl-37175206
Natural products remain one of the major sources of coveted, biologically active compounds. Each isolated compound undergoes biological testing, and its structure is usually established using a set of spectroscopic techniques (NMR, MS, UV-IR, ECD, VCD, etc.). However, the number of erroneously determined structures remains noticeable. Structure revisions are very costly, as they usually require extensive use of spectroscopic data, computational chemistry, and total synthesis. The cost is particularly high when a biologically active compound is resynthesized and the product is inactive because its structure is wrong and remains unknown. In this paper, we propose using Computer-Assisted Structure Elucidation (CASE) and Density Functional Theory (DFT) methods as tools for preventive verification of the originally proposed structure, and elucidation of the correct structure if the original structure is deemed to be incorrect. We examined twelve real cases in which structure revisions of natural products were performed using total synthesis, and we showed that in each of these cases, time-consuming total synthesis could have been avoided if CASE and DFT had been applied. In all described cases, the correct structures were established within minutes of using the originally published NMR and MS data, which were sometimes incomplete or had typos.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article