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

Abstract

Diagnosis of neurodegenerative diseases hinges on detection of “seed” proteins 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 crosslink 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, reveal the architecture of insoluble-aggregate networks and highlight influential proteins asnovel targets to ameliorate protein-aggregation diseases.

Keywords: Alzheimer’s Disease, Neurodegeneration, Protein Aggregation, Protein Interaction, NSAID, Nonsteroidal Anti-Inflammatory Drug, Disordered Proteins, Neural Network