ProteoMeter: a pipeline for integrating multi-PTM and limited proteolysis data to reveal modification-structure coupling at the residue level.

Systemic perturbations trigger extensive changes across the proteome-altering protein abundance, post-translational modifications (PTMs), conformational states, and complex assembly. Interpreting these effects demands computational pipelines capable of integrating diverse proteomics modalities, such as multi-PTM profiling, limited proteolysis mass spectrometry (LiP-MS), and cross-linking mass spectrometry (XL-MS), within a unified and interoperable framework. Because instrument data are quantified at the peptide level, mapping these measurements to individual residues or modification sites is essential for biologically meaningful interpretation. We introduce ProteoMeter, an open-source Python library designed to integrate multi-modal proteomics datasets and map them to single-residue resolution using a standardized coordinate framework. We showcase its capabilities in a combined multi-PTM and LiP-MS analysis profiling the proteomic response to human coronavirus 229e (HCoV-229E) infection. ProteoMeter is actively maintained and is freely available-including all source code and figure-generation scripts-at the following repository: https://github.com/PNNL-Predictive-Phenomics/ProteoMeter.