Metabolite Identification
Automatic chemical structure annotation of an LC-MS(n) based metabolic profile from green tea
1 H-NMR fingerprinting of vaccinium vitis-idaea flavonol glycosides
INTRODUCTION:
MetIDB: a publicly accessible database of predicted and experimental 1H NMR spectra of flavonoids
Systematic metabolite annotation and identification in complex biological extracts
Detailed knowledge of the chemical content of organisms, organs, tissues, and cells is needed to fully characterize complex biological systems. The high chemical variety of compounds present in biological systems is illustrated by the presence of a large variety of compounds, ranging from apolar lipids, semi-polar phenolic conjugates, toward polar sugars. A molecules’ chemical structure forms the basis to understand its biological function. The chemical identification process of small molecules (i.e., metabolites) is still one of the major focus points in metabolomics research.
Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives.
How do metabolites differ from their parent molecules and how are they excreted?
Understanding which physicochemical properties, or property distributions, are favorable for successful design and development of drugs, nutritional supplements, cosmetics, and agrochemicals is of great importance. In this study we have analyzed molecules from three distinct chemical spaces (i) approved drugs, (ii) human metabolites, and (iii) traditional Chinese medicine (TCM) to investigate four aspects determining the disposition of small organic molecules.
Structural elucidation of low abundant metabolites in complex sample matrices
Identification of metabolites is a major challenge in biological studies and relies in principle on mass spectrometry (MS) and nuclear magnetic resonance (NMR) methods.
Substructure-based annotation of high-resolution multistage MS(n) spectral trees
High-resolution multistage MS(n) data contains detailed information that can be used for structural elucidation of compounds observed in metabolomics studies. However, full exploitation of this complex data requires significant analysis efforts by human experts. In silico methods currently used to support data annotation by assigning substructures of candidate molecules are limited to a single level of MS fragmentation.