Mass spectrometry-based proteomics routinely quantifies proteins through signals derived from peptides or intact molecular species, yet a protein name or total abundance value can encompass multiple proteoforms with different sequences, processing histories, post-translational modifications, conformational states, interaction partners, and cellular contexts. This critical review examines how those layers of molecular heterogeneity limit functional interpretation when proteomic measurements are collapsed to protein-level abundance. Evidence from 2017–2024 is evaluated across proteoform classification, post-translational modification analysis, bottom-up and top-down mass spectrometry, ion-mobility and orthogonal separation strategies, statistical treatment of modified peptides, and emerging state-sensitive proteomic measurements. The analysis distinguishes molecular detection from proteoform assignment, modification localization, biological-state characterization, and causal functional inference. Particular attention is given to information that may be lost during digestion, sample preparation, precursor reconstruction, database inference, or aggregation of heterogeneous molecular forms. Proteoform-resolved approaches preserve more molecular connectivity, although their interpretation remains constrained by sensitivity, fragmentation, sample preparation, computational deconvolution, and incomplete contextual validation. The central conclusion is that total protein abundance remains informative for many biological questions but cannot be assumed to represent a single molecular or functional state. Functionally informative proteomics therefore requires explicit accounting for proteoform identity, modification topology, measurement uncertainty, biological context, and orthogonal evidence whenever these dimensions materially affect the inference being made.
