Software predicts mass spectral fragmentation patterns, which accelerates the identification of unknown molecular structures in mass spectral data sets
Advanced Chemistry Development announces the release of ACD/MS Fragmenter.
This software application predicts mass spectral fragmentation patterns, which accelerates the identification of unknown molecular structures in mass spectral data sets.
ACD/Labs has automated the rule-based task of determining possible fragmentation for organic molecules in an easy-to-use interface. MS Fragmenter's prediction capability complements the powerful verification capabilities of autoassignment in MS Manager enabling scientists to reduce the time consuming, expert knowledge-based task of identifying unknown compounds.
Fully integrated with ChemSketch, this sophisticated tool is able to predict the likely mass spectral fragmentation for any organic chemically drawn or imported structure.
"MS Fragmenter is designed for visualisation of predicted structure fragments in mass spectrometry built on the proven and widely used fragmentation engine that is integrated into our MS Manager product line," said Mark Bayliss, mass spectrometry product manager at ACD.
"Early discussions with a number of mass spectrometrists indicate that MS Fragmenter will have wide applicability for anyone interested in structural elucidation studies and the fragmentation routes of the individual fragments within a spectrum." Advanced features enable scientists to select fragmentation-rule parameters to mimic different ionisation techniques that range from classical electron ionisation to low energy protonation techniques such as electrospray (ESI) and atmospheric pressure ionisation (APCI). Fragmentation is presented in an organised fashion through a genealogical tree that establishes the parent child relationship of fragment ions in a natural manner.
MS Fragmenter allows easy navigation along the fragmentation scheme with a smart graph tree structure.
As a result, the normally tedious, manual, expert-requiring task of fragment prediction is reduced from countless hours to mere seconds.
