A Novel Adrenocorticotropin Receptor Mutation Alters Its Structure and Function, Causing Familial Glucocorticoid Deficiency

Artigas, Rocío; González, Ángel F.; Riquelme, Erick; Carvajal, Cristián A.; Cattani, Andreina; Martínez‐Aguayo, Alejandro; Kalergis, Alexis M.; Pérez-Acle, Tomás; Fardella, Carlos E.

doi:10.1210/jc.2008-0048

Cited by 13 publications

(9 citation statements)

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“…1). The majority of the MC2R mutations have been previously reported, [13][14][15][16][17][18][19][20][21][22][23][24][25] and of these the S74I mutation was present in 18 patients. All nine mutations have previously been reported for FGD type 2.…”

Section: Resultsmentioning

confidence: 98%

Phenotypic characteristics of familial glucocorticoid deficiency (FGD) type 1 and 2

Chung

Chan

Metherell

et al. 2010

Clinical Endocrinology

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ContextFamilial glucocorticoid deficiency (FGD) is a rare autosomal recessive disorder as a result of mutation in genes encoding either the ACTH receptor [melanocortin 2 receptor (MC2R)] or its accessory protein [melanocortin 2 receptor accessory protein (MRAP)[. The disorder is known as FGD type 1 and 2, respectively.ObjectiveThe aim of the study was to compare the phenotype/genotype relationships between FGD 1 and 2.Design and patientsForty patients with missense MC2R mutations and 22 patients with MRAP mutations were included. Forty-four of these patients had been referred for genetic screening and 18 were patients published by other authors.ResultsThe median age at presentation for FGD type 1 was variable at 2·0 years; range 0·02–16 years, and this was associated with unusually tall stature, mean height SDS + 1·75 ± 1·53 (mean ± SD). In contrast, FGD type 2 presented at a much earlier median age (0·08 years; range at birth to 1·6 years) (P < 0·01) and patients were of normal height SDS + 0·12 ± 1·35 (P < 0·001). No differences in baseline cortisol or ACTH levels were seen between FGD types 1 and 2.ConclusionFGD type 2 appears to present earlier. This may reflect the functional significance of the underlying mutations in that all MRAP mutations are nonsense or splice site mutations that result in abolition of a functional protein, whereas most of the MC2R mutations are missense mutations and give rise to proteins with some residual function. Tall stature is associated with mutations in MC2R but not in MRAP. There were no other significant clinical distinctions between the two.

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Section: Resultsmentioning

confidence: 98%

Phenotypic characteristics of familial glucocorticoid deficiency (FGD) type 1 and 2

Chung

Chan

Metherell

et al. 2010

Clinical Endocrinology

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“…However, neither mg nor md can rescue the obesity associated with MC4R-null mutations (21), and neither mutant is protected from obesity caused by ubiquitous overexpression of AGRP, 4 the physiological MC4R…”

Section: Mgmentioning

confidence: 99%

“…The five G-protein-coupled receptors of the melanocortin receptor (MCR) family regulate diverse physiological processes, including pigmentation, corticosteroid production, food intake and energy metabolism, sexual behavior, inflammation, and exocrine gland function (3)(4)(5)(6)(7)(8)(9)(10). Naturally occurring MCR agonists are derived from proopiomelanocortin, a precursor protein that is post-translationally processed in a tissuespecific manner by the proprotein convertases PC1 and PC2 (11).…”

mentioning

confidence: 99%

Mahoganoid and Mahogany Mutations Rectify the Obesity of the Yellow Mouse by Effects on Endosomal Traffic of MC4R Protein

Overton

Leibel

2011

Journal of Biological Chemistry

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The ubiquitous overexpression of agouti-signaling protein (ASP), a paracrine-signaling molecule that regulates pigmenttype switching in the hair follicle of the mouse, is responsible for the obesity and yellow pelage of the Yellow mouse (A y ). Mahogany (Attractin, Atrn/mg) and mahoganoid (Mahogunin Ring Finger-1, Mgrn1/md) are mutations epistatic to A y . These mutations have been described as suppressors of ASP action, blocking its antagonizing effects on the melanocortin 1 and 4 receptors (MC1R and MC4R) in the skin and the brain, respectively, via unknown mechanisms. Here, we describe the molecular bases for the md-and mg-dependent rescue of the A y phenotype at the MC4R. We show that overexpression of ASP inhibits the rise in cAMP levels in response to ␣-melanocyte-stimulating hormone, an MC4R agonist, by blocking ligand binding and by directing MC4R trafficking to the lysosome. Loss-of-function of either attractin or MGRN1 blocks ASP-dependent MC4R degradation and promotes increased trafficking of internalized MC4R to the cell surface, but it does not restore ␣-melanocytestimulating hormone-dependent cAMP signaling. We propose that MGRN1 and attractin are components of an evolutionarily conserved receptor trafficking pathway and that the md and mg mutations rescue the A y phenotypes by a primarily cAMP-independent mechanism promoting trafficking of MC4R and likely MC1R away from the lysosome toward the cell surface.

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“…These methods, commonly known as comparative modelling techniques, are suitable under some restrictions, to produce models able to be used as sources for protein engineering (Colombres et al, 2008;Eyzaguirre et al, 2004) and computer-based drug design Lizama et al, 2009;Vasquez et al, 2007), to explore structure-function relationships (Artigas et al, 2008b;Barria et al, 2009;Carvajal et al, 2003;Ehrenfeld et al, 2008;Stange et al, 2008;Strobel et al, 2005;Tischler et al, 2005), and signal-transducing mechanisms (Gonzalez et al, 2008;Inestrosa et al, 2005;Strobel et al, 2004), among a variety of applications.…”

Section: New Challenges For Bioinformatics and Computational Chemistrmentioning

confidence: 99%

Nanoinformatics: an emerging area of information technology at the intersection of bioinformatics, computational chemistry and nanobiotechnology

et al. 2011

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After the progress made during the genomics era, bioinformatics was tasked with supporting the fl ow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fi elds. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent fi eld. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientifi c fi elds, such as bioinformatics and computational chemistry.

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A Novel Adrenocorticotropin Receptor Mutation Alters Its Structure and Function, Causing Familial Glucocorticoid Deficiency

Abstract: We propose a molecular explanation for the reduced activity exhibited by the MC2R alanine 126 by serine mutant.

Cited by 13 publications

References 48 publications

Phenotypic characteristics of familial glucocorticoid deficiency (FGD) type 1 and 2

Phenotypic characteristics of familial glucocorticoid deficiency (FGD) type 1 and 2

Mahoganoid and Mahogany Mutations Rectify the Obesity of the Yellow Mouse by Effects on Endosomal Traffic of MC4R Protein

Nanoinformatics: an emerging area of information technology at the intersection of bioinformatics, computational chemistry and nanobiotechnology

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