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Natural products dereplication by diffusion ordered NMR spectroscopy (DOSY).

Guy Kleks1,2, Darren C Holland1,2, Joshua Porter1,2

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Summary

Diffusion-ordered NMR spectroscopy (DOSY) now predicts molecular weight (MW) for natural products (NP) using diffusion coefficients (D). This method accounts for factors like hydrogen bonding and shape, enabling accurate MW prediction and compound identification without mass spectrometry.

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Area of Science:

  • Analytical Chemistry
  • Organic Chemistry
  • Biochemistry

Background:

  • Diffusion-ordered NMR spectroscopy (DOSY) is a powerful technique for analyzing compound mixtures by differentiating resonances based on diffusion coefficients (D).
  • Historically, DOSY applications have focused on organometallic and polymer analysis, with limited exploration in diverse organic compounds like natural products (NP).

Purpose of the Study:

  • To extend the application of DOSY for analyzing structurally diverse organic compounds, specifically natural products (NP).
  • To establish predictive models for molecular weight (MW) based on experimental diffusion coefficients (D) and other physicochemical properties.
  • To develop a robust method for dereplicating known compounds and identifying novel compounds in mixtures using DOSY NMR data.

Main Methods:

  • Experimental diffusion coefficients (D) were measured for 55 diverse natural products (NPs).
  • Power law and multiple linear regression analyses were employed to correlate D with molecular weight (MW) and other physicochemical properties (hydrogen bonding, molar density, molecular shape).
  • A polynomial equation incorporating eight calculated physicochemical properties was generated to predict D, which was then applied to a database of 217,043 compounds (DEREP-NP).

Main Results:

  • A power law relationship was established between experimental D and MW for 55 NPs, enabling MW prediction.
  • New models incorporating factors like hydrogen bonding, molar density, and molecular shape improved MW prediction accuracy.
  • A polynomial equation based on multiple linear regression of eight physicochemical properties accurately correlated predicted D with experimental D for known organic compounds.
  • The developed methodology successfully dereplicated known compounds and identified new compounds from natural sources, validated by analyzing sesquiterpenes and bryozoan alkaloids.

Conclusions:

  • DOSY NMR can be effectively applied to predict molecular weight (MW) of natural products (NP) without mass spectrometry (MS).
  • Incorporating physicochemical properties into predictive models enhances the accuracy of MW determination and compound characterization.
  • This approach facilitates the dereplication of known compounds and the identification of new compounds directly from NMR data, significantly advancing natural product research.