Automating Mass Spectrometry Data Analysis for Antibody Subunit Characterization

Workflows and software tools for peptide mapping have been extensively optimized over the past several decades. However, top- and middle-down workflows to characterize proteoforms remain more demanding in terms of user expertise as well as instrument setup, data analysis, and result validation. To support routine intact protein characterization workflows, a new informatics platform named Proteoform Studio is introduced here, featuring an integrated pipeline encompassing rapid deconvolution to define intact mass features and improved targeted proteoform analysis via automated aggregation of results from multiple files and different fragmentation modes. Here, >80% sequence coverage of Lc and Fd antibody subunits was achieved following the aggregation of multiple fragmentation methods in middle-down experiments. Proteoform Studio was also used to define mass targets for subunits generated from above-hinge digestion and disulfide bond reduction of the NIST monoclonal antibody standard. Fragmentation analysis settings for signal to noise and isotope fit score were adjusted to achieve consistency with manually validated results. Analysis in Proteoform Studio facilitated data-guided adjustments of targeted method settings, resulting in higher sequence coverage for NIST subunits spiked into a simple antibody mixture. Software and fragmentation settings from these initial analyses informed definition of a targeted workflow to analyze NIST subunits spiked into a more complex plasma immunoglobulin G background. Introducing automation to eliminate informatics bottlenecks in antibody subunit characterization will drive adoption of the workflow to multiple biopharmaceutical assays (e.g., pharmacokinetic studies), leading to more precise knowledge of the biotherapeutic proteoforms present in samples.