We describe a method that integrates data derived from different mass spectrometry (MS)-based techniques with a modeling strategy for structural characterization of protein assemblies. We encoded structural data derived from native MS, bottom-up proteomics, ion mobility–MS and chemical cross-linking MS into modeling restraints to compute the most likely structure of a protein assembly. We used the method to generate near-native models for three known structures and characterized an assembly intermediate of the proteasomal base.