FB2026_02 , released June 18, 2026
Reference Report
Open Close
Reference
Citation
Zhang, Q., Tsoi, H., Peng, S., Li, P.P., Lau, K.F., Rudnicki, D.D., Ngo, J.C., Chan, H.Y. (2016). Assessing a peptidylic inhibitor-based therapeutic approach that simultaneously suppresses polyglutamine RNA- and protein-mediated toxicities in patient cells and Drosophila.  Dis. Model Mech. 9(3): 321--334.
FlyBase ID
FBrf0231137
Publication Type
Research paper
Abstract
Polyglutamine (polyQ) diseases represent a group of progressive neurodegenerative disorders that are caused by abnormal expansion of CAG triplet nucleotides in disease genes. Recent evidence indicates that not only mutant polyQ proteins, but also their corresponding mutant RNAs, contribute to the pathogenesis of polyQ diseases. Here, we describe the identification of a 13-amino-acid peptide, P3, which binds directly and preferentially to long-CAG RNA within the pathogenic range. When administered to cell and Drosophila disease models, as well as to patient-derived fibroblasts, P3 inhibited expanded-CAG-RNA-induced nucleolar stress and suppressed neurotoxicity. We further examined the combined therapeutic effect of P3 and polyQ-binding peptide 1 (QBP1), a well-characterized polyQ protein toxicity inhibitor, on neurodegeneration. When P3 and QBP1 were co-administered to disease models, both RNA and protein toxicities were effectively mitigated, resulting in a notable improvement of neurotoxicity suppression compared with the P3 and QBP1 single-treatment controls. Our findings indicate that targeting toxic RNAs and/or simultaneous targeting of toxic RNAs and their corresponding proteins could open up a new therapeutic strategy for treating polyQ degeneration.
PubMed ID
PubMed Central ID
PMC4833327 (PMC) (EuropePMC)
Associated Information
Comments
Associated Files
Other Information
Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Dis. Model Mech.
    Title
    Disease models & mechanisms
    ISBN/ISSN
    1754-8403 1754-8411
    Data From Reference