Reassignment of Improbable Natural Products Identified through Chemical Principle Screening

Abstract

Natural products continue to be reported at an astonishing rate from a wide range of multidisciplinary research activities in the pursuit of understanding the chemistry of biodiversity. However, the elucidation of chemical structure in the modern era is heavily reliant on the analysis and interpretation of multiple spectroscopic outputs, and in most cases this activity is by no means trivial. Structural errors continue to be described given the inherent complexity of natural products. Computer‐Assisted Structure Elucidation (CASE) continues to provide improved resolving power in this regard, but for enhanced accuracy quantum chemical spectrum prediction methodology is paramount. Reported herein are a range of counterfactual natural products, identified through chemical principal screening, which have been reassigned using a combination of chemical intuition, chemical synthesis, CASE and DU8+ spectrum prediction.

Rapid screening of unprecedented sesquiterpenes with distinctive ring skeletons from Daphne aurantiaca employing an integrated strategy

“…To accurately verify the above conclusion, Computer-Assisted Structure Elucidation (CASE) systems were applied to generate a set of possible structures based on empirical NMR chemical shift predictions, which were ranked by 13 C average deviations [d A ( 13 C), d N ( 13 C), and d N ( 13 C + 1 H)]. [30][31][32][33][34][35][36][37] Notably, the top hit structure (ID = 1) with the lowest standard deviation values among all the candidates was predicted as the most reasonable structure, which is consistent with the structure elucidation (Fig. 5b and c).…”

Machine learning-assisted structure annotation of natural products based on MS and NMR data

“…This strategy has been adopted to achieve efficient structural analysis of various types of NPs such as polyphenols, terpenoids and alkaloids, etc. 110–112…”

“…This strategy has been adopted to achieve efficient structural analysis of various types of NPs such as polyphenols, terpenoids and alkaloids, etc. [110][111][112] While this section primarily focuses on ML predictions of liquid NMR chemical shis, it is worth noting that ML has also made notable advancements in predicting solid NMR. 113 In 2018, Paruzzo proposed an ML method based on the local environment to accurately predict the chemical shis of molecular solids and their polymorphs within the accuracy of DFT.…”

Structural Investigation of Aaptourinamine by a Novel Module-Assembly-Based Calculation

“…As an important irreplaceable and potential tool, computer-assisted structural elucidation (CASE) has been providing reliable and advanced solutions to elucidate complex and various structures of natural products [ 13 , 14 , 15 , 16 ]. CASE programs imitated the way spectrum experts think about structure analysis through NMR data.…”