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

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 aggre...

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Detalles Bibliográficos
Autores principales: Balasubramaniam, Meenakshisundaram, Ayyadevara, Srinivas, Ganne, Akshatha, Kakraba, Samuel, Penthala, Narsimha Reddy, Du, Xiuxia, Crooks, Peter A., Griffin, Sue T., Shmookler Reis, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817627/
https://www.ncbi.nlm.nih.gov/pubmed/31593839
http://dx.doi.org/10.1016/j.isci.2019.09.026
Descripción
Sumario: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, APP(Sw)-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.