Analysis of Huntington's disease modifiers using the hyperbolic mapping of the protein interaction network

AC Vagiona, P Mier, S Petrakis… - International Journal of …, 2022 - mdpi.com
International Journal of Molecular Sciences, 2022mdpi.com
Huntington's disease (HD) is caused by the production of a mutant huntingtin (HTT) with an
abnormally long poly-glutamine (polyQ) tract, forming aggregates and inclusions in neurons.
Previous work by us and others has shown that an increase or decrease in polyQ-triggered
aggregates can be passive simply due to the interaction of proteins with the aggregates. To
search for proteins with active (functional) effects, which might be more effective in finding
therapies and mechanisms of HD, we selected among the proteins that interact with HTT a …
Huntington’s disease (HD) is caused by the production of a mutant huntingtin (HTT) with an abnormally long poly-glutamine (polyQ) tract, forming aggregates and inclusions in neurons. Previous work by us and others has shown that an increase or decrease in polyQ-triggered aggregates can be passive simply due to the interaction of proteins with the aggregates. To search for proteins with active (functional) effects, which might be more effective in finding therapies and mechanisms of HD, we selected among the proteins that interact with HTT a total of 49 pairs of proteins that, while being paralogous to each other (and thus expected to have similar passive interaction with HTT), are located in different regions of the protein interaction network (suggesting participation in different pathways or complexes). Three of these 49 pairs contained members with opposite effects on HD, according to the literature. The negative members of the three pairs, MID1, IKBKG, and IKBKB, interact with PPP2CA and TUBB, which are known negative factors in HD, as well as with HSP90AA1 and RPS3. The positive members of the three pairs interact with HSPA9. Our results provide potential HD modifiers of functional relevance and reveal the dynamic aspect of paralog evolution within the interaction network.
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