The METLIN Metabolomics Database is a repository of metabolite information as well as tandem mass spectrometry data. The information is provided to facilitate metabolomics experiments.
METLIN is a metabolomics database and, as of 5 September 2012, contains over 64,727 structures. It serves as a data management system to assist in metabolite research and metabolite identification by providing public access to its repository of comprehensive MS/MS metabolite data. An annotated list of known metabolites and their mass, chemical formula, and structure are available on the METLIN website. Each metabolite is linked to outside resources such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) for further reference and inquiry. Available MS/MS data are expanding continuously as more metabolite information is being deposited and discovered. The METLIN database was developed and is maintained by the Siuzdak laboratory at The Scripps Research Institute.
Introduction
Since its initial implementation in 2005, the METLIN site has collected comments and suggestions from users in the biotechnology, pharmaceutical and academic communities ultimately resulting in a dynamic, intuitive, and functionally useful metabolomics tool. The improved interface allows researchers to readily search the database and characterize metabolites through features such as accurate mass, single and multiple fragment searching, neutral loss and full spectrum search capabilities. These features are designed to facilitate the value of their metabolomics MS and MS/MS data and expedite the identification process.
The METLIN metabolite database is implemented using the open-source software tool, MySQL. The predicted fragment structures have been added to METLIN database using in-silico fragmentation. In addition to enhancements to the data structure, METLIN is utilizing a new database server that provides faster results than the previous server. The METLIN database currently contains accurate masses, chemical formulas, and structures. It also has tandem MS data on more than 10,000 distinct metabolites, over 50,000 high-resolution ESI-QTOF MS/MS spectra at four collision energies, and over 160,000 in silico predicted unique fragment structures.