Identification is by far the most challenging step in metabolomics research. After statistical analysis, interesting features are identified in order to understand their biological significance.
The level of confidence in compound identification is dependent upon the workflow and the analytical technique used to acquire the data. The most common approach is metabolite-specific database matching using accurate mass information. This approach provides compound candidates, yet lacks specificity for identity confirmation. The addition of isotope pattern matching will confirm the empirical formula. If retention time information is also included, confident compound identification can be achieved. Alternatively, MS/MS library or EI library searching can produce similar identification results. Combining retention time information with MS/MS library or EI library searching gives the highest level of confidence.
Agilent provides databases and libraries for compound identification using either GC/MS or LC/MS.
If the compound is not identified using any of the above databases or libraries, it is often possible to interpret the compound fragmentation spectra and propose a rational structure. However, this requires a high level of mass spectrometry expertise and is time consuming. There are two common approaches to spectral interpretation:
- De novo interpretation – reconstructing a chemical structure based on fragmentation data without using prior knowledge. There are software packages available to support this method, such as Structure Elucidator from ACD Labs.
- Structural correlation - correlating MS/MS spectra to a list of proposed chemical structures which is obtained from a database search using the calculated molecular formula. Agilent offers Molecular Structure Correlator to rapidly and easily search databases and arrive at a list of likely compounds.