Metabolite Structural Analysis Software MetID Solution
MetID Solution compares the pre- and post-metabolized sample data, and a search is then performed for expected and unexpected metabolites. (See the Profiling SolutionMetabolomics Software AM+ for a description of the statistics-driven in-depth search function that pinpoints changes among huge amounts of data.) Peaks generated with the metabolized sample that do not occur in the pre-metabolized sample are recognized a possible metabolites, and isotopic pattern comparison in conjunction with the composition prediction tool powerfully support highly accurate metabolite identification. As for the unexpected metabolite candidates (substances not expected in the metabolic pathway), this statistical multivariate analysis is applied to the MSn spectrum in conjunction with composition prediction tool to efficiently filter the candidates and identify the metabolites. This technique can be applied not only to metabolite analysis but to detection and identification of similar compounds in contaminant identification and natural substance chemistry.
- Easy operation
- Comparison of pre- and post-metabolized sample
- Metabolite candidate detection by multivariable analysis
- Synchronization with Composition Prediction Tool
- Lhasa Meteor Support
Comparison of Pre-metabolized and Post-metabolized Samples
MetID Solution can be used to compare pre- and post-metabolized samples to check the types of metabolites that are formed. Following is an explanation of the data obtained when the compound with the composition formula C18H11N2 is metabolized through an oxidation reaction. The compound changes as shown at right due to oxidation.
A comparison of the mass spectrum at m/z 289.0739 in the pre-metabolized and post-metabolized samples reveals a peak that is only observed in the post-metabolized sample. Thus, the substance is judged to be a metabolite. By comparing the peaks, any substances with masses in the vicinity of metabolites may be detected as metabolites. However, with the high-resolution, high-accuracy Shimadzu LCMS-IT-TOF, since comparisons are made between chromatograms drawn using precise mass width (XIC: Extracted Ion Chromatogram), assessments are made with high reliability.
Metabolic pathways often follow typical patterns, such as oxidation reaction, etc., and the presence of derived metabolites can be judged using MetID Solution. However, as less typical metabolic pathways also exist, the mass chromatograms are compared over the entire measurement mass range, and the differences between their respective samples are also assessed. Since composition prediction is applied to these differences, it can be judged as to whether or not they could have metabolized from the parent compound. These results are displayed in a window like that shown below.
Metabolite Candidate Detection by Multivariate Analysis
As there is often some type of correlation between the MSn spectrum (n(2) of the parent compound and that of the metabolite, statistical analysis (PLS method: Partial Least Squares method) is used to analyze the correlation between the MSn spectrum of the parent compound and that of each precursor ion.
Basically, if the parent compound is metabolized, there is a strong possibility that part of the metabolites will maintain a structure consistent with that of the parent compound. Therefore, by utilizing the ability to find commonalities between the product ions and neutral loss in the metabolite MSn spectra with that of the parent compound, high-correlation precursor ions are automatically extracted as metabolite candidates.
The analysis results appear as shown in the following window. The correlation between each precursor ion and the parent compound ion are plotted at the upper left. High-correlation precursor ions are distributed along the X axis in the region greater than 0. In addition, these precursor ions are displayed in the list at the bottom of the window.
MetID Solution can automatically generate the method for acquiring MS/MS spectra. The retention times, mass spectra, MS spectra and MS/MS spectrum accurate mass information can be obtained by a single analysis, and in addition to identifying expected metabolites using fewer analyses than previously, it enables reliable and efficient detection and prediction of unexpected metabolites.
Composition Prediction of Metabolite Candidates
Even for unknown metabolites, metabolic clues can be obtained from the differences between the composition formula candidates and the administered drug using the Composition Prediction Tool. The precise masses are used to automatically predict the compositions of unknown metabolites. High-accuracy prediction is possible through comparison of the isotopic patterns of MS spectra.
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