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Detection of potential TNA and RNA nucleoside precursors in a prebiotic mixture by pure shift diffusion-ordered NMR spectroscopy.

ABSTRACT: In the context of prebiotic chemistry, one of the characteristics of mixed nitrogenous-oxygenous chemistry is its propensity to give rise to highly complex reaction mixtures. There is therefore an urgent need to develop improved spectroscopic techniques if onerous chromatographic separations are to be avoided. One potential avenue is the combination of pure shift methodology, in which NMR spectra are measured with greatly improved resolution by suppressing multiplet structure, with diffusion-ordered spectroscopy, in which NMR signals from different species are distinguished through their different rates of diffusion. Such a combination has the added advantage of working with intact mixtures, allowing analyses to be carried out without perturbing mixtures in which chemical entities are part of a network of reactions in equilibrium. As part of a systems chemistry approach towards investigating the self-assembly of potentially prebiotic small molecules, we have analysed the complex mixture arising from mixing glycolaldehyde and cyanamide, in a first application of pure shift DOSY NMR to the characterisation of a partially unknown reaction composition. The work presented illustrates the potential of pure shift DOSY to be applied to chemistries that give rise to mixtures of compounds in which the NMR signal resolution is poor. The direct formation of potential RNA and TNA nucleoside precursors, amongst other adducts, was observed. These preliminary observations may have implications for the potentially prebiotic assembly chemistry of pyrimidine threonucleotides, and therefore of TNA, by using recently reported chemistries that yield the activated pyridimidine ribonucleotides.

SUBMITTER: Islam S

PROVIDER: S-EPMC3814424 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Project description:Diffusion-ordered NMR spectroscopy (DOSY) can be used to analyze mixtures of compounds since resonances deriving from different compounds are distinguished by their diffusion coefficients (D). Previously, DOSY has mostly been used for organometallic and polymer analysis, we have now applied DOSY to investigate diffusion coefficients of structurally diverse organic compounds such as natural products (NP). The experimental Ds derived from 55 diverse NPs has allowed us to establish a power law relationship between D and molecular weight (MW) and therefore predict MW from experimental D. We have shown that D is also affected by factors such as hydrogen bonding, molar density and molecular shape of the compound and we have generated new models that incorporate experimentally derived variables for these factors so that more accurate predictions of MW can be calculated from experimental D. The recognition that multiple physicochemical properties affect D has allowed us to generate a polynomial equation based on multiple linear regression analysis of eight calculated physicochemical properties from 63 compounds to accurately correlate predicted D with experimental D for any known organic compound. This equation has been used to calculate predicted D for 217 043 compounds present in a publicly available natural product database (DEREP-NP) and to dereplicate known NPs in a mixture based on matching of experimental D and structural features derived from NMR analysis with predicted D and calculated structural features in the database. These models have been validated by the dereplication of a mixture of two known sesquiterpenes obtained from Tasmannia xerophila and the identification of new alkaloids from the bryozoan Amathia lamourouxi. These new methodologies allow the MW of compounds in mixtures to be predicted without the need for MS analysis, the dereplication of known compounds and identification of new compounds based solely on parameters derived by DOSY NMR.

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Detection of potential TNA and RNA nucleoside precursors in a prebiotic mixture by pure shift diffusion-ordered NMR spectroscopy.

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