Dataset Information

Hydrocarbon Macrocycle Conformer Ensembles and ¹³ C-NMR Spectra.

ABSTRACT: NMR as a routine analytical method provides important three-dimensional structure information of compounds in solution. Here we apply the recently released CRENSO computational workflow for the automated generation of conformer ensembles to the quantum mechanical calculation of ¹³ C-NMR spectra of a series of flexible cycloalkanes up to C₂₀ H₄₀ . We evaluate the computed chemical shifts in comparison with corresponding experimental data in chloroform. It is shown that accurate and properly averaged theoretical NMR data can be obtained in about a day of computation time on a standard workstation computer. The excellent agreement between theory and experiment enables one to deduce preferred conformations of large, non-rigid macrocycles under ambient conditions from our automated procedure.

SUBMITTER: Bohle F

PROVIDER: S-EPMC9303527 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Publications

Hydrocarbon Macrocycle Conformer Ensembles and 13 C-NMR Spectra.

Bohle Fabian F Grimme Stefan S

Angewandte Chemie (International ed. in English) 20220215 14

NMR as a routine analytical method provides important three-dimensional structure information of compounds in solution. Here we apply the recently released CRENSO computational workflow for the automated generation of conformer ensembles to the quantum mechanical calculation of 13 C-NMR spectra of a series of flexible cycloalkanes up to C20 H40 . We evaluate the computed chemical shifts in comparison with corresponding experimental data in chloroform. It is shown ...[more]

PMID: 35099097

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Project description:Background: Metabolism is essential for cell survival and proliferation. A deep understanding of the metabolic network and its regulatory processes is often vital to understand and overcome disease. Stable isotope tracing of metabolism using nuclear magnetic resonance (NMR) and mass spectrometry (MS) is a powerful tool to derive mechanistic information of metabolic network activity. However, to retrieve meaningful information, automated tools are urgently needed to analyse these complex spectra and eliminate the bias introduced by manual analysis. Here, we present a data-driven algorithm to automatically annotate and analyse NMR signal multiplets in 2D- 1H, 13C-HSQC NMR spectra arising from 13C - 13C scalar couplings. The algorithm minimises the need for user input to guide the analysis of 2D- 1H, 13C-HSQC NMR spectra by performing automated peak picking and multiplet analysis. This enables non-NMR specialists to use this technology. The algorithm has been integrated into the existing MetaboLab software package. Methods: To evaluate the algorithm performance two criteria are tested: is the peak correctly annotated and secondly how confident is the algorithm with its analysis. For the latter a coefficient of determination is introduced. Three datasets were used for testing. The first was to test reproducibility with three biological replicates, the second tested the robustness of the algorithm for different amounts of scaling of the apparent J-coupling constants and the third focused on different sampling amounts. Results: The algorithm annotated overall >90% of NMR signals correctly with average coefficient of determination ρ of 94.06 ± 5.08%, 95.47 ± 7.20% and 80.47 ± 20.98% respectively. Conclusions: Our results indicate that the proposed algorithm accurately identifies and analyses NMR signal multiplets in ultra-high resolution 2D- 1H, 13C-HSQC NMR spectra. It is robust to signal splitting enhancement and up to 25% of non-uniform sampling.

Dataset Information

Hydrocarbon Macrocycle Conformer Ensembles and ¹³ C-NMR Spectra.

Publications

Hydrocarbon Macrocycle Conformer Ensembles and <sup>13</sup> C-NMR Spectra.

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