April 2010
Volume 51, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2010
Correlation Between Protein Stability And Retinitis Pigmentosa
Author Affiliations & Notes
  • E. P. Rakoczy
    Centre for Ophthalmology and Visual Science, University of Western Australia, Crawley, Australia
  • C. Kiel
    Systems Biology Research Unit, Center for Genomic Regulation, Barcelona, Spain
  • R. McKeone
    Molecular Ophthalmology, Lions Eye Institute, Perth, Australia
  • F. Stricher
    Systems Biology Research Unit, Center for Genomic Regulation, Barcelona, Spain
  • L. Serrano-Pubull
    Systems Biology Research Unit, Center for Genomic Regulation, Barcelona, Spain
  • Footnotes
    Commercial Relationships  E.P. Rakoczy, None; C. Kiel, None; R. McKeone, None; F. Stricher, None; L. Serrano-Pubull, None.
  • Footnotes
    Support  Save Sight Foundation of Western Australia, University of Western Australia
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 4094. doi:
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      E. P. Rakoczy, C. Kiel, R. McKeone, F. Stricher, L. Serrano-Pubull; Correlation Between Protein Stability And Retinitis Pigmentosa. Invest. Ophthalmol. Vis. Sci. 2010;51(13):4094.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : To map the correlation between energy changes of rhodopsin missense-mutations and their potential affect on clinical severity of Retinitis Pigmentosa (RP).

Methods: : Data mining of the available literature revealed 353 individuals carrying single point mutations of the rhodopsin gene that were positively associated with adRP. Five structural predictions of Bovine-Rhodopsin were selected from the Protein Data Bank (RCSB PDB) for analysis of the protein’s stability using the Build Model program FOLDX.

Results: : Phenotypic subtyping was available for 52 of the 103 mutations. In total 56% of the cases were Type 1 (T1), 38% were Type 2 (T2) and 6% of the mutations appeared to be asymptomatic. The average age of individuals with daytime vision loss was 19 years for T1 patients and 35 for T2 patients. Visual acuity was 0.52 for T1 patients and 0.83 for patients with a T2 subtype. Asymptomatic mutations did not show energy changes (av: 0.6 kcal/mol) significant enough to be associated with rhodopsin instability. The average change for T2 was 7.1 kcal/mol and for T1 9.6kcal/mol confirming a strong correlation between mutation associated destabilising energy change and protein stability. In 59 mutations, FoldX predicted strong destabilising energy changes (>2kcal/mol) and in 10 mutations destabilising energy changes were weak (1.1-2kcal/mol). In 31 mutations the energy change was <1.1 kcal/mol thus energy change itself did not influence rhodopsin stability. However due to the fundamental functional role of the mutated residues, these mutations were associated with disease. Of these, 2 were involved in the formation of the rhodopsin-dimer, 1 was associated with transducin-complex stability, 4 were phosphorylation or glycosylation sites, 10 were involved in lipid-protein contact, 11 were folded normally but cellular transport was impaired, 1 mutation was the binding motif for ciliary transport whereas a molecular explanation for disease symptoms in two of the mutations has yet to be identified. There was a statistically significant inverse correlation between FoldX predicted energy change and both the best eye visual acuity and the size of the visual field in mutations located at the N- terminus.

Conclusions: : These results tentatively suggest that system biology might be a useful tool to predict the progression of the loss of visual acuity and visual field for certain types of eye diseases.

Keywords: retinal degenerations: cell biology • genetics • clinical (human) or epidemiologic studies: biostatistics/epidemiology methodology 
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