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  • 1
    Publication Date: 1997-07-11
    Description: An integrated human-mouse positional candidate approach was used to identify the gene responsible for the phenotypes observed in a mouse model of Niemann-Pick type C (NP-C) disease. The predicted murine NPC1 protein has sequence homology to the putative transmembrane domains of the Hedgehog signaling molecule Patched, to the cholesterol-sensing regions of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase and SREBP cleavage-activating protein (SCAP), and to the NPC1 orthologs identified in human, the nematode Caenorhabditis elegans, and the yeast Saccharomyces cerevisiae. The mouse model may provide an important resource for studying the role of NPC1 in cholesterol homeostasis and neurodegeneration and for assessing the efficacy of new drugs for NP-C disease.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Loftus, S K -- Morris, J A -- Carstea, E D -- Gu, J Z -- Cummings, C -- Brown, A -- Ellison, J -- Ohno, K -- Rosenfeld, M A -- Tagle, D A -- Pentchev, P G -- Pavan, W J -- New York, N.Y. -- Science. 1997 Jul 11;277(5323):232-5.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Laboratory of Genetic Disease Research, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, MD 20892, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/9211850" target="_blank"〉PubMed〈/a〉
    Keywords: Amino Acid Sequence ; Animals ; Base Sequence ; Cholesterol/*metabolism ; *Disease Models, Animal ; Homeostasis ; Humans ; Hydroxymethylglutaryl CoA Reductases/chemistry ; Intracellular Signaling Peptides and Proteins ; Lysosomes/metabolism ; Membrane Proteins/chemistry ; Mice ; Mice, Inbred BALB C ; Mice, Inbred C57BL ; Mice, Mutant Strains ; Molecular Sequence Data ; Mutation ; Niemann-Pick Diseases/*genetics/metabolism ; Phenotype ; Protein Sorting Signals/chemistry ; Proteins/chemistry/*genetics/physiology ; Sequence Homology, Amino Acid
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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