Tags

Type your tag names separated by a space and hit enter

Multi-component metabolic classification of commercial feverfew preparations via high-field 1H-NMR spectroscopy and chemometrics.
Planta Med. 2002 Aug; 68(8):734-8.PM

Abstract

There is increasing interest in evaluating the clinical efficacy of herbal medicines. However, there are significant analytical problems associated with quality control and the measurement of the overall composition of such complex, multi-component mixtures as normally required in the pharmaceutical industry. Here we describe a novel NMR spectroscopic and pattern recognition analytical approach to investigate composition and variability of a commonly used herbal medicine. 600 MHz (1)H-NMR spectroscopy and principal components analysis (PCA) was used to discriminate between batches of 14 commercially available feverfew samples based on multi-component metabolite profiles. Two of the batches were significantly different from the other twelve. The twelve remaining classes could be classified into discrete groups by PCA on the basis of minor differences in overall chemical composition. NMR based pattern recognition (PR) analysis of extracts proved to be superior to PR analysis of HPLC traces of the same mixtures. This work indicates the potential value of NMR combined with PCA for the characterisation of complex natural product mixtures, and the discrimination of samples containing allegedly identical ingredients.

Authors+Show Affiliations

Biological Chemistry, Biomedical Sciences Division, Imperial College of Science, Technology and Medicine, University of London, South Kensington, London, United Kingdom. nigel.bailey@ic.ac.ukNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

12221598

Citation

Bailey, Nigel J C., et al. "Multi-component Metabolic Classification of Commercial Feverfew Preparations Via High-field 1H-NMR Spectroscopy and Chemometrics." Planta Medica, vol. 68, no. 8, 2002, pp. 734-8.
Bailey NJ, Sampson J, Hylands PJ, et al. Multi-component metabolic classification of commercial feverfew preparations via high-field 1H-NMR spectroscopy and chemometrics. Planta Med. 2002;68(8):734-8.
Bailey, N. J., Sampson, J., Hylands, P. J., Nicholson, J. K., & Holmes, E. (2002). Multi-component metabolic classification of commercial feverfew preparations via high-field 1H-NMR spectroscopy and chemometrics. Planta Medica, 68(8), 734-8.
Bailey NJ, et al. Multi-component Metabolic Classification of Commercial Feverfew Preparations Via High-field 1H-NMR Spectroscopy and Chemometrics. Planta Med. 2002;68(8):734-8. PubMed PMID: 12221598.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Multi-component metabolic classification of commercial feverfew preparations via high-field 1H-NMR spectroscopy and chemometrics. AU - Bailey,Nigel J C, AU - Sampson,Julia, AU - Hylands,Peter J, AU - Nicholson,Jeremy K, AU - Holmes,Elaine, PY - 2002/9/11/pubmed PY - 2002/11/26/medline PY - 2002/9/11/entrez SP - 734 EP - 8 JF - Planta medica JO - Planta Med VL - 68 IS - 8 N2 - There is increasing interest in evaluating the clinical efficacy of herbal medicines. However, there are significant analytical problems associated with quality control and the measurement of the overall composition of such complex, multi-component mixtures as normally required in the pharmaceutical industry. Here we describe a novel NMR spectroscopic and pattern recognition analytical approach to investigate composition and variability of a commonly used herbal medicine. 600 MHz (1)H-NMR spectroscopy and principal components analysis (PCA) was used to discriminate between batches of 14 commercially available feverfew samples based on multi-component metabolite profiles. Two of the batches were significantly different from the other twelve. The twelve remaining classes could be classified into discrete groups by PCA on the basis of minor differences in overall chemical composition. NMR based pattern recognition (PR) analysis of extracts proved to be superior to PR analysis of HPLC traces of the same mixtures. This work indicates the potential value of NMR combined with PCA for the characterisation of complex natural product mixtures, and the discrimination of samples containing allegedly identical ingredients. SN - 0032-0943 UR - https://www.unboundmedicine.com/medline/citation/12221598/Multi_component_metabolic_classification_of_commercial_feverfew_preparations_via_high_field_1H_NMR_spectroscopy_and_chemometrics_ L2 - http://www.thieme-connect.com/DOI/DOI?10.1055/s-2002-33793 DB - PRIME DP - Unbound Medicine ER -