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Amyloid fibrils are pathological hallmarks of neurodegenerative diseases and central contributors to their progression, representing promising targets for disease-modifying interventions. However, limited access to patient-derived fibrils and the inability to reproduce pathological foldsin vitrohinder the development of fibril-specific ligands. Here, we present FibrilSite, a computational pipeline that identifies geometric and physicochemical similarities across fibril surfaces and demonstrate its utility to identify structural features that distinguish different fibril polymorphs. Our analysis uncovered conserved and polymorph-specific features within alpha-synuclein fibrils. Notably, one site was conserved betweenex vivomultiple system atrophy andin vitroH50Q mutant fibrils, suggesting the latter’s potential utility in drug discovery. Druggability predictions further prioritized ligandable sites across fibrils. Together, our findings establish a structure-based framework for identifying disease-relevant features and mapping them onto suitablein vitromodels, guiding the rational development of polymorph-specific diagnostics and therapeutics for amyloid-related disorders with improved translational potential.