Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases

Autor: Meenakshisundaram Balasubramaniam, Srinivas Ayyadevara, Akshatha Ganne, Samuel Kakraba, Narsimha Reddy Penthala, Xiuxia Du, Peter A. Crooks, Sue T. Griffin, Robert J. Shmookler Reis
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: iScience, Vol 20, Iss , Pp 248-264 (2019)
Druh dokumentu: article
ISSN: 2589-0042
DOI: 10.1016/j.isci.2019.09.026
Popis: Summary: Diagnosis of neurodegenerative diseases hinges on “seed” proteins detected in disease-specific aggregates. These inclusions contain diverse constituents, adhering through aberrant interactions that our prior data indicate are nonrandom. To define preferential protein-protein contacts mediating aggregate coalescence, we created click-chemistry reagents that cross-link neighboring proteins within human, APPSw-driven, neuroblastoma-cell aggregates. These reagents incorporate a biotinyl group to efficiently recover linked tryptic-peptide pairs. Mass-spectroscopy outputs were screened for all possible peptide pairs in the aggregate proteome. These empirical linkages, ranked by abundance, implicate a protein-adherence network termed the “aggregate contactome.” Critical hubs and hub-hub interactions were assessed by RNAi-mediated rescue of chemotaxis in aging nematodes, and aggregation-driving properties were inferred by multivariate regression and neural-network approaches. Aspirin, while disrupting aggregation, greatly simplified the aggregate contactome. This approach, and the dynamic model of aggregate accrual it implies, reveals the architecture of insoluble-aggregate networks and may reveal targets susceptible to interventions to ameliorate protein-aggregation diseases. : Neuroscience; Molecular Neuroscience; Neural Networks; Proteomics Subject Areas: Neuroscience, Molecular Neuroscience, Neural Networks, Proteomics
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