Data Processing and Analysis in Positional Proteomics

Proteolytic cleavage is an irreversible post-translational modification (PTM), and dysregulation of protease activity is often a hallmark in disease. Aberrant proteolysis can alter protein abundance or function, disturbing cellular state and resulting in disease-specific biomarkers or therapeutic targets. Positional proteomics facilitates global identification and precise quantification of position-specific peptides, such as those located N- or C-terminal in the protein sequence. These techniques enable the study of both natural and neo-protein termini, as well as associated PTMs. Despite its importance, proteolysis remains understudied due to experimental challenges and complex data processing. In this review, we outline key strategies for data analysis and processing in positional proteomics, emphasizing how identification, quantification, and interpretation of proteolytic cleavage sites differ from standard proteomics data analysis pipelines. We discuss differences in common approaches for terminomics-focused workflows, comparing N- versus C-terminomics, as well as different labeling strategies and acquisition methods. Additionally, we highlight considerations for proper normalization approaches, specifically the need to normalize cleavage abundances relative to protein and protease abundance. We explain the importance of integrating structural data, solvent accessibility, and tissue expression profiles during data analysis to better evaluate the biological significance of experimental results.