Answering researchers' need for improved accuracy and speed in identification of unknown components, Shimadzu has developed a new system featuring its award-winning LCMS-IT-Tof mass spectrometer
Using information-rich MSn data, the Formula Predictor software takes advantage of multiple levels of fragmentation, isotope pattern verification, and unique fragment-ion filtering techniques to accurately determine the correct formula for unknown components.
Traditional approaches for deducing empirical formulae from mass spec data often depend on very high mass accuracy, which carries a correspondingly high cost, and considerable time input from the user to eliminate low-probability structures.
Shimadzu's new system reduces or eliminates this need for tedious, manual processing of target candidates.
In many cases, the software can reduce the collection of target compounds from a high number of possible candidates to predicting the most likely empirical formula with just a simple mouse click.
The first LCMS system to fully utilize the information-rich content of MSn data in formulae prediction, Shimadzu's LCMS-IT-TOF addresses the needs of biomarker discovery, trace amount impurity identification, and natural products research.
Kozo Shimazu, corporate officer and deputy general manager analytical and measuring instruments division for mass spectrometry and life sciences at Shimadzu, stated: "Our formula prediction software has been developed to help researchers working in compound verification to identify unknown compounds correctly with higher confidence.
"We believe that this software further strengthens the unique technology of the LCMS-IT-Tof in delivering an integrated solution to identify or verify empirical formulae."
