The molecular structure and function of fibrocystin, the key gene product implicated in autosomal recessive polycystic kidney disease (ARPKD)

IF 1 4区 生物学 Q4 GENETICS & HEREDITY
Travis A K Bannell, Joseph J B Cockburn
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引用次数: 0

Abstract

Autosomal recessive polycystic kidney disease is an early onset inherited hepatorenal disorder affecting around 1 in 20,000 births with no approved specific therapies. The disease is almost always caused by variations in the polycystic kidney and hepatic disease 1 gene, which encodes fibrocystin (FC), a very large, single-pass transmembrane glycoprotein found in primary cilia, urine and urinary exosomes. By comparison to proteins involved in autosomal dominant PKD, our structural and molecular understanding of FC has lagged far behind such that there are no published experimentally determined structures of any part of the protein. Bioinformatics analyses predict that the ectodomain contains a long chain of immunoglobulin-like plexin-transcription factor domains, a protective antigen 14 domain, a tandem G8-TMEM2 homology region and a sperm protein, enterokinase and agrin domain. Here we review current knowledge on the molecular function of the protein from a structural perspective.

Abstract Image

纤维胱氨酸是常染色体隐性遗传性多囊肾病(ARPKD)的关键基因产物,其分子结构和功能。
常染色体隐性多囊肾病是一种早期发病的遗传性肝肾疾病,约每20000名新生儿中就有1名患有该疾病,但没有批准的特定治疗方法。这种疾病几乎总是由多囊肾病和肝病1基因的变异引起的,该基因编码纤维胱氨酸(FC),这是一种在原发性纤毛、尿液和尿液外泌体中发现的非常大的单程跨膜糖蛋白。与常染色体显性PKD相关的蛋白质相比,我们对FC的结构和分子理解远远落后,以至于没有发表实验确定的蛋白质任何部分的结构。生物信息学分析预测,胞外结构域包含免疫球蛋白样丛蛋白转录因子结构域的长链、保护性抗原14结构域、串联G8-TMEM2同源区以及精子蛋白、肠激酶和农业蛋白结构域。在这里,我们从结构的角度回顾了目前关于蛋白质分子功能的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of Human Genetics
Annals of Human Genetics 生物-遗传学
CiteScore
4.20
自引率
0.00%
发文量
34
审稿时长
3 months
期刊介绍: Annals of Human Genetics publishes material directly concerned with human genetics or the application of scientific principles and techniques to any aspect of human inheritance. Papers that describe work on other species that may be relevant to human genetics will also be considered. Mathematical models should include examples of application to data where possible. Authors are welcome to submit Supporting Information, such as data sets or additional figures or tables, that will not be published in the print edition of the journal, but which will be viewable via the online edition and stored on the website.
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