Developing a robust self-optimizing MS/MS QTOF workflow for de novo verification of synthetic peptides in biopharmaceutical applications

摘要

An optimized workflow allowing facile information rich MS/MS data utilizing an improved DDA based method is presented. An example study to elucidate primary and background peptides to automatically identify sequence scrambling, low abundance impurities shows a discovery adapted technique with self-optimizing DDA MS/MS provides the ability to perform comprehensive sampling data with improved data quality for automated de novo sequencing.