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Statistical Correlations between HPLC Activity-Based Profiling Results and NMR/MS Microfraction Data to Deconvolute
Samuel Bertrand1,2, Antonio Azzollini3, Andreas Nievergelt4
1School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Quai Ernest-Ansermet 30, CH-1211 Geneva 4, Switzerland. Samuel.bertrand@univ-nantes.fr.
Molecules (Basel, Switzerland)
|March 2, 2016
Summary
Statistical correlation analysis of microfractionated natural products (NPs) aids in identifying bioactive compounds early. This method bypasses the need for complete isolation, accelerating natural product discovery.
Area of Science:
- Natural Product Chemistry
- Analytical Chemistry
- Bioactive Compound Discovery
Background:
- Modern natural product (NP) research focuses on discovering bioactive compounds at microgram levels.
- Traditional large-scale bioassay-guided fractionation is time-consuming.
- LC-MS metabolite profiling and microfractionation offer early identification of bioactive compounds.
Purpose of the Study:
- To evaluate the efficacy of statistical correlation analysis for identifying bioactive compound features in mixtures.
- To demonstrate the potential for unambiguous identification without complete compound isolation.
- To validate a proof-of-concept using microfractionation of a natural product mixture.
Main Methods:
- Microfractionation of a natural product mixture using rapid small-scale semi-preparative HPLC.
- Analysis of microfractions using UHPLC-ESI-TOFMS (Ultra-High-Performance Liquid Chromatography-Electrospray Ionization-Time-of-Flight Mass Spectrometry).
- Acquisition of micro-flow CapNMR (Capillary Nuclear Magnetic Resonance) spectra for each microfraction.
- Bioactivity profiling using a cancer chemopreventive assay on all microfractions.
- Application of statistical correlation analysis to integrated data.
Main Results:
- Statistical correlation analysis successfully identified features linked to bioactive compounds within the natural product mixture.
- The approach enabled the characterization of bioactive components without requiring their complete isolation.
- Proof-of-concept demonstrated the feasibility of combining microfractionation, multi-technique analysis, and statistical correlation.
Conclusions:
- Statistical correlation analysis is a powerful tool for accelerating the identification of bioactive natural products.
- This integrated approach significantly enhances early-stage discovery by reducing the need for extensive purification.
- The methodology holds promise for efficient screening and characterization of complex natural product mixtures.
Keywords:
biological profilingcorrelation analysismetabolomicsmicrofractionationquinone reductase inductionMore Related Videos
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