The enhancements made to its ProteinLynx Global SERVER (PLGS 2.2.5) software are especially important for drug researchers performing time-scale studies during which changes in the protein profile are carefully monitored at intervals, e.g. drug time course studies.
PLGS 2.2.5 extends this technology with improved algorithms for improved protein quantification and identification across large patient/sample sets or time-course studies.
Waters has included a new module in PLGS allows quantitative data to be generated at the protein or peptide level using any of the commercially available or user-defined labelling technologies such as SILAC, AQUATM, ICAT, iTRAQ, etc.
The ability to perform both 'label free' and 'isotopic labelling' approaches now means that PLGS provides flexibility to analyse proteomics samples of varying type and complexity.
PLGS 2.2.5 provides a 'step change' in the ability to identify proteins efficiently in complex samples by incorporating a new algorithm, which enables identification of proteins from MSE data (E - elevated collision energy) acquired from a Q-Tof type mass spectrometer.
In an LC/MS experiment a proprietary and patented* 'parallel' peptide fragmentation protocol is employed to provide a 100 per cent duty cycle on all detectable peptides in a protein digest.
This new approach results in significantly higher sequence coverage and confidence in protein identification than traditional 'Data Dependent Acquisition' (DDA) MS/MS methods.
For researchers publishing their scientific findings in peer-reviewed scientific journals, PLGS 2.2.5 will have access to a number of formats including peaklist, eXtensible Markup Language (XML), and the mzData Format as required by the Human Protein Organisation (HUPO) Proteomics Standards Initiative for Mass Spectrometry.