MassMetaSite is an established approach for the automatic identification of metabolites for small molecule and peptides using Liquid Chromatography – Mass Spectrometry, UV, fluorescence and radio-chromatogram data, reducing manual analysis from several hours to only a few minutes per compound. The program is able to assign chemical structures to each automatically detected chromatographic peak based on the MS and MS/MS fragmentation pattern of the substrates and metabolites. It can process from multiple vendors: Agilent, Bruker, Sciex, Thermo and Waters, and it is also able to analyze data from different acquisition modes: DDA, DDA, MSE, HDMSE, AIF, AF, Broad band, SWATH, Sonar, etc.
In the cases where the data cannot be used to propose a single structure for the chromatographic peaks found, the system also introduces the Site of Metabolism (SoM) prediction from MetaSite computation (the leader in the metabolism prediction market), that ranks the multiple structural options. Moreover, the user has access to the visual analysis of the enzyme-metabolite interaction CYPs, FMO and AOX proteins, and it can even propose structural modification to overcome the metabolic liability.
The auto-process and the batch processor enable the use of the software for automatic process in ADME workflows like GSH, Met ID, Soft Spot and much more.
Lead Molecular Design is activelly contributing to the development of the MassMetaSite program since the first commercial version in 2009 until today.
To request a copy of MassMetasite, visit Molecular Discovery site.
Reading of the most common file formats:
 Enhanced metabolite identification with MS(E) and a semi-automated software for structural elucidation Bonn B, Leandersson C, Fontaine F, Zamora I. Rapid Commun Mass Spectrom. 2010 Nov 15;24(21):3127-38.
 High-throughput, fully automated, specific MetID. A revolution for Drug Discovery. Zamora I, Fontaine F, Serra B, Plasencia G, Drug Discovery Today: Technologies 2012, in press.
 Metabolism of JWH-015, JWH-098, JWH-251, and JWH-307 in silico and in vitro: a pilot study for the detection of unknown synthetic cannabinoids metabolites.Strano-Rossi S1, Anzillotti L, Dragoni S, Pellegrino RM, Goracci L, Pascali VL, Cruciani G. Analytical and Bioanalytical Chemistry.June 2014;406(15):3621-3636.
 High-throughput, computer assisted, specific MetID. A revolution for drug discovery./Ismael Zamora, Fabien Fontaine, Blanca Serra, Guillem Plasencia. Drug Discovery Today: Technologies, 2013 Spring Issue;10(1):e199–e205.
 Software automation tools for increased throughput metabolic soft-spot identification in early drug discovery. Veronica Zelesky, Richard Schneider1, John Janiszewski1, Ismael Zamora, James Ferguson & Matthew Troutman. Bioanalysis, 5(10):1165-1179.
 Update on hydrocodone metabolites in rats and dogs aided with a semi-automatic software for metabolite identification Mass-MetaSite. Austin C. Li, James P. Chovan, Erya Yu, and Ismael Zamora. Xenobiotica, April 2013;43(4):390-398
 Enhanced metabolite identification with MSE and a semi-automated software for structural elucidation. Britta Bonn1, Carina Leandersson, Fabien Fontaine, Ismael Zamora. Rapid Communications in Mass Spectrometry , 15 November 2010;24(21):3127–3138.
 Post-acquisition analysis of untargeted accurate mass quadrupole time-of-flight MS(E) data for multiple collision-induced neutral losses and fragment ions of glutathione conjugates. Brink A, Fontaine F, Marschmann M, Steinhuber B, Cece EN, Zamora I, Pähler A. Rapid Commun Mass Spectrom. 2014 Dec 30;28(24):2695-703