While mass spectrometry has made a far-reaching impact towards understanding cellular signaling, there is still a huge limitation in analyzing phosphosites occurring in close proximity. Indeed, accumulating phosphoproteomic data shows that phosphorylation sites cluster together in multi-phosphorylated proteins, where over half of sites are within four amino acids of each other. These neighboring sites result in phosphopeptide positional isomers that can sometimes be chromatographically resolved, but because they have the same precursor mass, dynamic exclusion settings often cause these peptides to be overlooked in data-dependent acquisition (DDA) experiments. This, coupled with the stochastic nature of DDA, often results in replicate quantitative experiments that exhibit very poor overlap. Here we propose Thesaurus, a new search engine that detects clusters of phosphopeptide positional isomers from Parallel Reaction Monitoring (PRM) and Data-Independent Acquisition (DIA) experiments. Using the insulin signaling pathway as a model, we demonstrate we can computationally extract distinct quantitative signaling effects of different positional isomers, even if those isomers do not separate chromatographically.