July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
NEI Ocular Proteome Database: A Description of Inherited Eye Disease Proteins and Their Stability Changes by a Computational Global Mutagenesis.
Author Affiliations & Notes
  • Claudia Kassouf
    Ophthalmic Genetics and Visual Function Branch, National Eye Institute/National Institute of Health, Bethesda, Maryland, United States
  • Caitlyn McCafferty
    Ophthalmic Genetics and Visual Function Branch, National Eye Institute/National Institute of Health, Bethesda, Maryland, United States
  • Yuri V Sergeev
    Ophthalmic Genetics and Visual Function Branch, National Eye Institute/National Institute of Health, Bethesda, Maryland, United States
  • Francisca Wood Ortiz
    Ophthalmic Genetics and Visual Function Branch, National Eye Institute/National Institute of Health, Bethesda, Maryland, United States
  • Footnotes
    Commercial Relationships   Claudia Kassouf, None; Caitlyn McCafferty, None; Yuri Sergeev, None; Francisca Wood Ortiz, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 386. doi:
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      Claudia Kassouf, Caitlyn McCafferty, Yuri V Sergeev, Francisca Wood Ortiz; NEI Ocular Proteome Database: A Description of Inherited Eye Disease Proteins and Their Stability Changes by a Computational Global Mutagenesis.. Invest. Ophthalmol. Vis. Sci. 2019;60(9):386.

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

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Abstract

Purpose : Missense mutations are associated with many inherited eye diseases. Often, the knowledge of protein atomic structure and evaluation of protein stability are critical for understanding molecular mechanisms. Currently, robust tools which evaluates protein structure stability changes at the atomic level don't exist. Recently we developed a method, the unfolding mutation screen (UMS), which generates the effect of all possible missense mutations within a protein and created a small database of 15 disease-related proteins and their mutant variant. Here we report a database extension available for the public.

Methods : Prediction of genetic disease phenotype at the atomic level of protein structure was previously described (Sergeev et al, 2010, 2013). All the information to generate protein structures was obtained from public databases. Protein structures were obtained through homology modeling, using both their Uniprot’s FASTA sequences and other homologous protein models from the database of protein structures (RCSB). A global landscape of stability changes to the protein caused by each possible missense mutation was calculated using a semi-empirical Gibbs free energy (FoldX) and converted into unfolding propensities as described (McCafferty& Sergeev, Sci. Reports, 2016). The accuracy of the predictions is about 77.9 ± 9.1% and was previously verified for 1391 mutant variants of 16 protein crystal structures and thermodynamic data.

Results : A publicly available library of 102 ocular protein structures was built using the global mutagenesis pipeline. Each protein on the website has a description of its structure and function, related diseases, UMS calculations through stability heat maps, a downloadable PDB file of the structure, molecular modeling parameters, and links to its UniProt, HGMD, and LOVD pages. The proteins span 150 inherited eye diseases such as human cataracts, glaucoma, retinal degeneration and others, with over a million missense mutations evaluated. The database is located at https://neicommons.nei.nih.gov/#/proteomeData.

Conclusions : The ocular proteome database offers the first collection of atomic structures and global mutagenesis analysis of eye-disease related proteins. Researchers and clinicians alike can access the database to examine the protein stability effects of newly discovered or poorly understood missense variants.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

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