Networks of protein-protein interactions in neurodegenerative diseases

Coordinator:    Prof. Dr. Erich Wanker
Institution: Max-Delbrück-Centrum für Molekulare Medizin (MDC) Berlin-Buch
Subproject 1 has focused on the generation and bioinformatic analysis of protein-protein interaction (PPI) networks. Based on these data functional modules were to be identified that play an essential role in neurodegenerative diseases (NDs). In addition, computational methods have been developed to predict potential disease modulators, which we then investigated experimentally.
In the course of the project, over 20,000 PPIs for 1,000 ND-related target proteins (Fig. 1) were identified, a large number of which could be validated using independent methods. The screens were carried out with the classical Y2H method as well as with advanced technologies such as cytoY2H and MYTH for membrane proteins. The PPIs were validated  with optimized FRET and LUMIER as well as with pull-down, co-immunoprecipitation and functional assays.
Extensive protein networks were created that facilitate systematic analysis of disease processes at the molecular level and the identification of new associations between the proteins involved. By incorporating mass spectrometric investigations, new protein complexes were predicted or identified that most probably play an important role in various NDs. One of them consists of the proteins Parkin and α-synuclein, which are important in Parkinson (PD) and APP, which is crucial for the development of Alzheimer's disease (AD). Our studies showed that both proteins influence APP processing and the formation of amyloid-beta peptides and therefore play an important role not only in PD but also in AD.
Furthermore an empirical system for the accurate assessment of PPI data was developed (Venkatesan et al., Nat Methods, 2009) and could be successfully applied during the project. Based on topological and ontological criteria, the quality of each generated PPI was validated.
The PPI networks generated in this subproject contain highly relevant new information about disease processes that will enable the establishment of new research areas and that are important for the development of innovative therapeutic strategies. The networks contain many newly identified interactions which could be confirmed by validation experiments. The data are of high quality and therefore of considerable value to the scientific community and the public.

Figure 1: Some ND disease proteins on which the generation of the PPI-networks were based.

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