Use of liquid chromatography/time-of-flight mass spectrometry and multivariate statistical analysis shows promise for the detection of drug metabolites in biological fluids (original) (raw)
Related papers
Analytical Chemistry, 2006
The aim of metabolite profiling is to monitor all metabolites within a biological sample for applications in basic biochemical research as well as pharmacokinetic studies and biomarker discovery. Here, novel data analysis software, XCMS, was used to monitor all metabolite features detected from an array of serum extraction methods, with application to metabolite profiling using electrospray liquid chromatography/mass spectrometry (ESI-LC/MS). The XCMS software enabled the comparison of methods with regard to reproducibility, the number and type of metabolite features detected, and the similarity of these features between different extraction methods. Extraction efficiency with regard to metabolite feature hydrophobicity was examined through the generation of unique feature density distribution plots, displaying feature distribution along chromatographic time. Hierarchical clustering was performed to highlight similarities in the metabolite features observed between the extraction methods. Protein extraction efficiency was determined using the Bradford assay, and the residual proteins were identified using nano-LC/MS/MS. Additionally, the identification of four of the most intensely ionized serum metabolites using FTMS and tandem mass spectrometry was reported. The extraction methods, ranging from organic solvents and acids to heat denaturation, varied widely in both protein removal efficiency and the number of mass spectral features detected. Methanol protein precipitation followed by centrifugation was found to be the most effective, straightforward, and reproducible approach, resulting in serum extracts containing over 2000 detected metabolite features and less than 2% residual protein. Interestingly, the combination of all approaches produced over 10 000 unique metabolite features, a number that is indicative of the complexity of the human metabolome and the potential of metabolomics in biomarker discovery.
UPLC–MS for metabolomics: a giant step forward in support of pharmaceutical research
Drug Discovery Today, 2016
Metabolomics is a relatively new and rapidly growing area of post-genomic biological research. As use of metabolomics technology grows throughout the spectrum of drug discovery and development, and its applications broaden, its impact is expanding dramatically. This review seeks to provide the reader with a brief history of the development of metabolomics, its significance and strategies for conducting metabolomics studies. The most widely used analytical tools for metabolomics: NMR, LC-MS and GC-MS, are discussed along with considerations for their use. Herein, we will show how metabolomics can assist in pharmaceutical research studies, such as pharmacology and toxicology, and discuss some examples of the importance of metabolomics analysis in research and development.
Journal of analytical & bioanalytical techniques, 2010
M etabolite identification is amongst the important studies during early stages of drug development because metabolic products may be pharmacologically active or toxic in nature. In the last one decade, there have been revolutionary changes in the way metabolite identification is carried out. This has mainly become possible due to the advent of sophisticated analytical modalities, particularly, hyphenated liquid chromatography-mass spectrometry (LC-MS). There are varieties of LC-MS systems available with difference in their utility in metabolite identification. Particularly, HPLC coupled with high resolution-mass spectrometry (HR-MS) and multiple-stage MS (MS n) plays a leading role in identification of metabolites (1-2). Sample preparation, mass fragmentation studies, in silico metabolite prediction and detection, chromatographic retention, UV spectra matching, determination of molecular formula, and establishment of possible site of metabolism are the important aspects in unequivocal identification of metabolites. In this same context, there have been several recent advancements in metabolite identification. These include approaches for detection of reactive metabolites, new generation LC systems and MS ion sources, isotopic pattern matching, hydrogen/deuterium exchange mass spectrometry, data dependent analyses, MS E approach, mass defect filter, 2D and 3D approaches for elucidation of molecular formula, polarity switching, background subtraction-noise reduction algorithms (BgS-NoRA), etc. The same will be discussed with case examples, as appropriate.
The emergence of metabolomics as a key discipline in the drug discovery process
Drug Discovery Today: Technologies, 2015
Metabolomics is a recent science that could be defined as the comprehensive qualitative and quantitative analysis of all small molecular weight compounds present in a cell, organ (including biofluids) or organism at a specific time point. More and more applications have been found these last years to metabolomics in the pharmaceutical field. Specifically in the drug discovery process, metabolomics open new perspectives, in new targets identification, in toxicological studies and in bioactive natural products discovery. The challenge in metabolomics is to find a technological approach allowing the reproducible identification and quantitation of as much metabolites as possible. In this context, mass spectrometry and NMR are emerging as key and complementary technologies.
Rapid identification of drug metabolites with tandem mass spectrometry
Biological Mass Spectrometry, 1988
A method which involves the use of tandem mass spectrometry (MS/MS) for the identification of drug metabolites has been demonstrated with a triple quadrupole mass spectrometer. The method is based on the fact that metabolites usually retain various substructures of the original drug molecule. MS/MS is capable of rapidly identifying molecules with characteristic substructures without prior separation. It is shown that this method makes it possible to postulate possible drug metabolite structures rapidly and systematically without the use of standards. The MS/MS method, as it was applied to the identification of the metabolites of a new antiepileptic drug, zonisamide, is discussed. In this case it was possible to identify isomeric metabolites due to their differences in vaporization times off the probe and their different daughter spectra. The complementary uses of the neutral loss and parent scans for the determination of the site of metabolism is demonstrated. A new figure of merit, the limit of identification, is introduced. The amount of the epoxide metabolite of carbamazepine necessary for its reliable identification in urine was shown to be 0.4 ng/pl. The application of various techniques to confirm preliminary findings with this MS/MS method are described.
From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics
2007
Mass spectrometry (MS) is an established technology in drug metabolite analysis and is now expanding into endogenous metabolite research. Its utility derives from its wide dynamic range, reproducible quantitative analysis, and the ability to analyze biofluids with extreme molecular complexity. The aims of developing mass spectrometry for metabolomics range from understanding basic biochemistry to biomarker discovery and the structural characterization of physiologically important metabolites. In this review, we will discuss the techniques involved in this exciting area and the current and future applications of this field. . Ultrahigh performance liquid chromatography (UPLC) utilizes columns with smaller particle size packing material (1.4-1.7 µm) than traditional columns and can enhance several aspects of chromatography in a metabolomics context. (1) Separation of metabolites is improved, decreasing ion suppression and in turn improving data interpretability (2) Signal to Noise (S/N) is improved due to narrower peak widths allowing for increased peak capacity and improved accuracy and sensitivity. (3) Sample run time is decreased dramatically allowing for faster sample throughput.
Analytical Strategies for Identifying Drug Metabolites
Mass Spectrometry …, 2007
The drug development process is scientifically complex and financially risky, hence very time consuming and expensive (Grabowski, Vernon, & DiMasi, 2002; DiMasi, Hansen, & Grabowski, 2003). It has been estimated that for every 5,000 new chemical entities ...