Software Automates Deep Characterization of Biotherapeutic Proteins
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As protein-based drugs become more important in treating major diseases, producers face the critical challenge of deeply characterizing these highly complex molecules for efficacy and safety, as well as to meet quality requirements.
PepFinder software is designed to streamline relative and absolute quantitation, and identification of proteins from biological samples using liquid chromatography-mass spectrometry (LC-MS). The new software is making its debut at the 62nd ASMS Conference on Mass Spectrometry and Allied Topics at the Holiday suite in the Hilton Baltimore Hotel.
Therapeutic proteins such as monoclonal antibodies, interferons and insulin must be produced in biologically active forms that have proper folding and specific post-translational modifications (PTM). Traditional analysis of these complex biological molecules is highly complex and time-consuming. PepFinder software uses multidimensional dynamic search capabilities to automatically integrate complex data into concise reports.
“This is a new paradigm for peptide mapping data analysis,” said Ken Miller, vice president marketing, life sciences mass spectrometry, Thermo Fisher Scientific. “Customers can expect to reduce analysis time from weeks to hours in some cases, while generating high-confidence, comprehensive characterization reports, including known and unknown modifications.”
“Using PepFinder, a complex protein was analyzed with great details (including PTMs), and with great ease and speed,” said Shiaw-Lin (Billy) Wu, head of analytical sciences, BioAnalytix and research associate professor at Northeastern University.
PepFinder software, based on Mass Analyzer software licensed from Amgen, is compatible with Thermo Scientific LC-MS instruments, including the industry-leading high resolution, accurate-mass Orbitrap-based systems. This software is designed for fast, high-quality PTM profiles and peptide identifications based on a novel prediction algorithm. The software displays sequence coverage maps, automates relative changes in site specific PTMs for rapid monitoring of modifications in a single sample or across sample comparison. The software is written to provide an automated workflow for glycopeptides ID, disulfide bond mapping and other common PTM’s, including oxidation, deamidation and phosphorylation. This can eliminate time consuming and error-prone manual PTM mapping.
