Peroxisomal interactome mapping enables network-based modelling of function and disease.
Peroxisomal dysfunction contributes to a broad spectrum of multisystem disorders, yet mechanistic understanding and therapeutic options remain limited, posing significant challenges for clinical management. Network-based computational strategies support hypothesis generation, biomarker discovery, and drug repurposing, but their usage is constrained by incomplete human interactome coverage-especially by scarcity of high-confidence protein-protein ... interaction (PPI) data for peroxisomal proteins. We present the first comprehensive map of the peroxisomal interactome, generated using an automated, informatics-guided bioluminescence resonance energy transfer strategy. We profiled PPIs for 92 peroxisomal proteins and six isoforms, validating 68% of known interactions and identifying 333 novel ones. Integration with curated PPIs yielded an expanded peroxisomal interactome, enriched for drug targets and disease-associated proteins. A disease-linked subnetwork enabled prioritization of drug repurposing candidates. Tissue-specific expanded peroxisomal interactome variants, derived from transcriptomic data, revealed distinct functional submodules across nine tissues. Gene ontology analysis of 1,272 non-peroxisomal interactors suggested pathways contributing to tissue-specific vulnerability. Our approach provides a systems-level framework for mechanistic insight in peroxisomal disease, the identification of treatment targets, and application to other organelle systems.
Mesh Terms:
Computational Biology, Gene Ontology, Humans, Peroxisomal Disorders, Peroxisomes, Protein Interaction Mapping, Protein Interaction Maps
Computational Biology, Gene Ontology, Humans, Peroxisomal Disorders, Peroxisomes, Protein Interaction Mapping, Protein Interaction Maps
Life Sci Alliance
Date: Sep. 01, 2026
PubMed ID: 42386525
View in: Pubmed Google Scholar
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