Lucy Botros, Yang Liu, Charlotte Corbett, Dan Sørensen, Christina Szabo, Anton Bzhelyansky, Matthias Niemitz, Petrus Korhonen, Guido F Pauli, Patrick Giraudeau, G Joseph Ray
{"title":"Connecting the Practice of Modern Qualitative and Quantitative NMR Analysis with Its Theoretical Foundation.","authors":"Lucy Botros, Yang Liu, Charlotte Corbett, Dan Sørensen, Christina Szabo, Anton Bzhelyansky, Matthias Niemitz, Petrus Korhonen, Guido F Pauli, Patrick Giraudeau, G Joseph Ray","doi":"10.1021/acs.jnatprod.4c01013","DOIUrl":null,"url":null,"abstract":"<p><p>This Perspective seeks to reconnect the current practice of nuclear magnetic resonance (NMR) spectroscopy in chemical structure and quantitative (qNMR) analysis with its roots in classical physics and quantum mechanics (QM). Rationales for this approach are derived from various angles, including focused reviews of the key parameters of the nuclear resonance phenomenon, the structural information richness of NMR spectra, and significant progress in both computational and spectrometer hardware. This provides collective reasoning for the reintegration of computational quantum mechanical spectral analysis (QMSA) into the contemporary practice of NMR spectral interpretation. Retethering operator-dependent visual <i>phenotypic</i> with QM-driven computational <i>genotypic</i> analysis yields more objective and accurate information by taking advantage of QM as the foundational reference point for NMR. Powerful computational tools for compound <i>genotyping</i> are available and evolve rapidly toward automation. In addition to enhancing the rigor and reproducibility of structure elucidation of new and the dereplication of known compounds, QM anchoring enables competent resolution of peak overlap, with resulting benefits in qNMR and low-field/benchtop NMR analysis. Furthermore, examination of common definitions and documentation practices shows that an evolutionary reconciliation of NMR terminology helps resolve ambiguities: shifting from <i>phenotypic</i> peak focus to <i>genotypic</i> QM-based pattern analysis is not only the logical next step when communicating structures of natural products and other molecules reproducibly but also a timely approach, as it yields QMSA-verified data for evolving knowledge bases for molecules of biomedical relevance.</p>","PeriodicalId":47,"journal":{"name":"Journal of Natural Products ","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Natural Products ","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acs.jnatprod.4c01013","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0
Abstract
This Perspective seeks to reconnect the current practice of nuclear magnetic resonance (NMR) spectroscopy in chemical structure and quantitative (qNMR) analysis with its roots in classical physics and quantum mechanics (QM). Rationales for this approach are derived from various angles, including focused reviews of the key parameters of the nuclear resonance phenomenon, the structural information richness of NMR spectra, and significant progress in both computational and spectrometer hardware. This provides collective reasoning for the reintegration of computational quantum mechanical spectral analysis (QMSA) into the contemporary practice of NMR spectral interpretation. Retethering operator-dependent visual phenotypic with QM-driven computational genotypic analysis yields more objective and accurate information by taking advantage of QM as the foundational reference point for NMR. Powerful computational tools for compound genotyping are available and evolve rapidly toward automation. In addition to enhancing the rigor and reproducibility of structure elucidation of new and the dereplication of known compounds, QM anchoring enables competent resolution of peak overlap, with resulting benefits in qNMR and low-field/benchtop NMR analysis. Furthermore, examination of common definitions and documentation practices shows that an evolutionary reconciliation of NMR terminology helps resolve ambiguities: shifting from phenotypic peak focus to genotypic QM-based pattern analysis is not only the logical next step when communicating structures of natural products and other molecules reproducibly but also a timely approach, as it yields QMSA-verified data for evolving knowledge bases for molecules of biomedical relevance.
期刊介绍:
The Journal of Natural Products invites and publishes papers that make substantial and scholarly contributions to the area of natural products research. Contributions may relate to the chemistry and/or biochemistry of naturally occurring compounds or the biology of living systems from which they are obtained.
Specifically, there may be articles that describe secondary metabolites of microorganisms, including antibiotics and mycotoxins; physiologically active compounds from terrestrial and marine plants and animals; biochemical studies, including biosynthesis and microbiological transformations; fermentation and plant tissue culture; the isolation, structure elucidation, and chemical synthesis of novel compounds from nature; and the pharmacology of compounds of natural origin.
When new compounds are reported, manuscripts describing their biological activity are much preferred.
Specifically, there may be articles that describe secondary metabolites of microorganisms, including antibiotics and mycotoxins; physiologically active compounds from terrestrial and marine plants and animals; biochemical studies, including biosynthesis and microbiological transformations; fermentation and plant tissue culture; the isolation, structure elucidation, and chemical synthesis of novel compounds from nature; and the pharmacology of compounds of natural origin.