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Structural Modeling of a Novel CAPN5 Mutation that Causes Uveitis and Neovascular Retinal Detachment
Author(s) -
Alexander G. Bassuk,
Steven Yeh,
Shu Wu,
Daniel Martín,
Stephen H. Tsang,
Lokesh Gakhar,
Vinit B. Mahajan
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0122352
Subject(s) - missense mutation , mutation , proliferative vitreoretinopathy , biology , medicine , genetics , retinal detachment , retinal , ophthalmology , gene
CAPN5 mutations have been linked to autosomal dominant neovascular inflammatory vitreoretinopathy (ADNIV), a blinding autoimmune eye disease. Here, we link a new CAPN5 mutation to ADNIV and model the three-dimensional structure of the resulting mutant protein. In our study, a kindred with inflammatory vitreoretinopathy was evaluated by clinical eye examinations, DNA sequencing, and protein structural modeling to investigate the disease-causing mutation. Two daughters of an affected mother demonstrated symptoms of stage III ADNIV, with posterior uveitis, cystoid macular edema, intraocular fibrosis, retinal neovascularization, retinal degeneration, and cataract. The women also harbored a novel guanine to thymine (c.750G>T, p.Lys250Asn) missense mutation in exon 6 of CAPN5 , a gene that encodes a calcium-activated cysteine protease, calpain-5. Modeling based on the structures of all known calpains revealed the mutation falls within a calcium-sensitive flexible gating loop that controls access to the catalytic groove. Three-dimensional modeling placed the new mutation in a region adjacent to two previously identified disease-causing mutations, all three of which likely disrupt hydrogen bonding within the gating loop, yielding a CAPN5 with altered enzymatic activity. This is the third case of a CAPN5 mutation leading to inherited uveitis and neovascular vitreoretinopathy, suggesting patients with ADNIV features should be tested for CAPN5 mutations. Structural modeling of novel variants can be used to support mechanistic consequences of the disease-causing variants.

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