MixONat

MixONat performs dereplication of complex natural product mixtures using 13C nuclear magnetic resonance (NMR) spectroscopy by matching {1H}-13C and DEPT spectral data to predicted or experimental 13C chemical shifts (δc) to identify and classify compounds.

Key Features:

• 13C NMR spectroscopy: Uses 13C NMR spectral patterns to examine a wide array of organic compounds, including the ability to differentiate stereoisomers.
• {1H}-13C spectral processing: Processes {1H}-13C NMR spectra to extract carbon chemical shift information for matching.
• DEPT integration: Incorporates Distortionless Enhancement by Polarization Transfer (DEPT) data, specifically DEPT-135 and DEPT-90, to distinguish carbon types (CH3, CH2, CH, and C).
• Mass weight filtering: Applies mass weight filtering to refine candidate matches by molecular weight constraints.
• Database matching: Matches observed chemical shifts against databases containing predicted or experimental 13C chemical shifts (δc).
• Structural class orientation: Implements an algorithm to orient spectral results toward structural classes of secondary metabolites.

Scientific Applications:

• Pharmacology (poppy alkaloids): Dereplicates and identifies alkaloid constituents in pharmaceutical-relevant mixtures such as poppy alkaloids.
• Nutrition (rosemary extracts): Identifies known components within nutritional plant extracts, exemplified by rosemary.
• Cosmetics (mangosteen peel extract): Detects and dereplicates bioactive compounds in cosmetic ingredient mixtures such as mangosteen peel extract.
• Stereoisomer discrimination: Distinguishes structurally similar natural products, including stereoisomers, using 13C chemical shifts and DEPT data.

Methodology:

Implemented in Python 3.5; processes {1H}-13C NMR spectra with DEPT-135 and DEPT-90 data, matches observed 13C chemical shifts (δc) against databases of predicted or experimental shifts, applies mass weight filtering, and uses an algorithm to assign carbon types and orient results toward structural classes of secondary metabolites.