000857532 001__ 857532
000857532 005__ 20240625095114.0
000857532 0247_ $$2doi$$a10.1021/acschemneuro.8b00027
000857532 0247_ $$2Handle$$a2128/21119
000857532 0247_ $$2pmid$$apmid:29506378
000857532 0247_ $$2WOS$$aWOS:000436211800022
000857532 0247_ $$2altmetric$$aaltmetric:34391965
000857532 037__ $$aFZJ-2018-06523
000857532 082__ $$a540
000857532 1001_ $$0P:(DE-Juel1)130822$$aMatthes, Frank$$b0$$ufzj
000857532 245__ $$aReducing Mutant Huntingtin Protein Expression in Living Cells by a Newly Identified RNA CAG Binder
000857532 260__ $$aWashington, DC$$bACS Publ.$$c2018
000857532 3367_ $$2DRIVER$$aarticle
000857532 3367_ $$2DataCite$$aOutput Types/Journal article
000857532 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1674541218_32481
000857532 3367_ $$2BibTeX$$aARTICLE
000857532 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000857532 3367_ $$00$$2EndNote$$aJournal Article
000857532 520__ $$aExpanded CAG trinucleotide repeats in Huntington’s disease (HD) are causative for neurotoxicity. The mutant CAG repeat RNA encodes neurotoxic polyglutamine proteins and can lead to a toxic gain of function by aberrantly recruiting RNA-binding proteins. One of these is the MID1 protein, which induces aberrant Huntingtin (HTT) protein translation upon binding. Here we have identified a set of CAG repeat binder candidates by in silico methods. One of those, furamidine, reduces the level of binding of HTT mRNA to MID1 and other target proteins in vitro. Metadynamics calculations, fairly consistent with experimental data measured here, provide hints about the binding mode of the ligand. Importantly, furamidine also decreases the protein level of HTT in a HD cell line model. This shows that small molecules masking RNA–MID1 interactions may be active against mutant HTT protein in living cells.
000857532 536__ $$0G:(DE-HGF)POF3-574$$a574 - Theory, modelling and simulation (POF3-574)$$cPOF3-574$$fPOF III$$x0
000857532 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x1
000857532 588__ $$aDataset connected to CrossRef
000857532 7001_ $$0P:(DE-HGF)0$$aMassari, Serena$$b1
000857532 7001_ $$0P:(DE-Juel1)169975$$aBochicchio, Anna$$b2
000857532 7001_ $$0P:(DE-HGF)0$$aSchorpp, Kenji$$b3
000857532 7001_ $$0P:(DE-HGF)0$$aSchilling, Judith$$b4
000857532 7001_ $$0P:(DE-HGF)0$$aWeber, Stephanie$$b5
000857532 7001_ $$0P:(DE-HGF)0$$aOffermann, Nina$$b6
000857532 7001_ $$0P:(DE-HGF)0$$aDesantis, Jenny$$b7
000857532 7001_ $$0P:(DE-HGF)0$$aWanker, Erich$$b8
000857532 7001_ $$0P:(DE-Juel1)145614$$aCarloni, Paolo$$b9$$ufzj
000857532 7001_ $$0P:(DE-HGF)0$$aHadian, Kamyar$$b10
000857532 7001_ $$0P:(DE-HGF)0$$aTabarrini, Oriana$$b11$$eCorresponding author
000857532 7001_ $$0P:(DE-Juel1)145921$$aRossetti, Giulia$$b12$$eCorresponding author
000857532 7001_ $$0P:(DE-HGF)0$$aKrauss, Sybille$$b13$$eCorresponding author
000857532 773__ $$0PERI:(DE-600)2528493-9$$a10.1021/acschemneuro.8b00027$$gVol. 9, no. 6, p. 1399 - 1408$$n6$$p1399 - 1408$$tACS chemical neuroscience$$v9$$x1948-7193$$y2018
000857532 8564_ $$uhttps://juser.fz-juelich.de/record/857532/files/acschemneuro.8b00027.pdf$$yOpenAccess
000857532 8564_ $$uhttps://juser.fz-juelich.de/record/857532/files/acschemneuro.8b00027.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000857532 909CO $$ooai:juser.fz-juelich.de:857532$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000857532 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)130822$$aForschungszentrum Jülich$$b0$$kFZJ
000857532 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)169975$$aForschungszentrum Jülich$$b2$$kFZJ
000857532 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145614$$aForschungszentrum Jülich$$b9$$kFZJ
000857532 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145921$$aForschungszentrum Jülich$$b12$$kFZJ
000857532 9131_ $$0G:(DE-HGF)POF3-574$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vTheory, modelling and simulation$$x0
000857532 9131_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x1
000857532 9141_ $$y2018
000857532 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000857532 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000857532 915__ $$0LIC:(DE-HGF)PublisherOA$$2HGFVOC$$aFree to read
000857532 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bACS CHEM NEUROSCI : 2017
000857532 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000857532 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000857532 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000857532 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000857532 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000857532 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000857532 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central
000857532 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000857532 920__ $$lyes
000857532 9201_ $$0I:(DE-Juel1)IAS-5-20120330$$kIAS-5$$lComputational Biomedicine$$x0
000857532 9201_ $$0I:(DE-82)080012_20140620$$kJARA-HPC$$lJARA - HPC$$x1
000857532 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x2
000857532 9201_ $$0I:(DE-Juel1)INM-9-20140121$$kINM-9$$lComputational Biomedicine$$x3
000857532 980__ $$ajournal
000857532 980__ $$aVDB
000857532 980__ $$aI:(DE-Juel1)IAS-5-20120330
000857532 980__ $$aI:(DE-82)080012_20140620
000857532 980__ $$aI:(DE-Juel1)JSC-20090406
000857532 980__ $$aI:(DE-Juel1)INM-9-20140121
000857532 980__ $$aUNRESTRICTED
000857532 9801_ $$aFullTexts