000888467 001__ 888467
000888467 005__ 20210130010943.0
000888467 0247_ $$2doi$$a10.1002/ijch.202000007
000888467 0247_ $$2ISSN$$a0021-2148
000888467 0247_ $$2ISSN$$a1869-5868
000888467 0247_ $$2Handle$$a2128/26554
000888467 0247_ $$2WOS$$aWOS:000550773000008
000888467 037__ $$aFZJ-2020-04935
000888467 082__ $$a540
000888467 1001_ $$0P:(DE-HGF)0$$aReinartz, Ines$$b0
000888467 245__ $$aFRET Dyes Significantly Affect SAXS Intensities of Proteins
000888467 260__ $$aWeinheim$$bWiley-VCH$$c2020
000888467 3367_ $$2DRIVER$$aarticle
000888467 3367_ $$2DataCite$$aOutput Types/Journal article
000888467 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1608045321_18852
000888467 3367_ $$2BibTeX$$aARTICLE
000888467 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000888467 3367_ $$00$$2EndNote$$aJournal Article
000888467 520__ $$aStructural analyses in biophysics aim at revealing a relationship between a molecule's dynamic structure and its physiological function. Förster resonance energy transfer (FRET) and small‐angle X‐ray scattering (SAXS) are complementary experimental approaches to this. Their concomitant application in combined studies has recently opened a lively debate on how to interpret FRET measurements in the light of SAXS data with the popular example of the radius of gyration, commonly derived from both FRET and SAXS. There still is a lack of understanding in how to mutually relate and interpret quantities equally obtained from FRET or SAXS, and to what extent FRET dyes affect SAXS intensities in combined applications. In the present work, we examine the interplay of FRET and SAXS from a computational simulation perspective. Molecular simulations are a valuable complement to experimental approaches and supply instructive information on dynamics. As FRET depends not only on the mutual separation but also on the relative orientations, the dynamics, and therefore also the shapes of the dyes, we utilize a novel method for simulating FRET‐dye‐labeled proteins to investigate these aspects in atomic detail. We perform structure‐based simulations of four different proteins with and without dyes in both folded and unfolded conformations. In‐silico derived radii of gyration are different with and without dyes and depend on the chosen dye pair. The dyes apparently influence the dynamics of unfolded systems. We find that FRET dyes attached to a protein have a significant impact on theoretical SAXS intensities calculated from simulated structures, especially for small proteins. Radii of gyration from FRET and SAXS deviate systematically, which points to further underlying mechanisms beyond prevalent explanation approaches.
000888467 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x0
000888467 536__ $$0G:(DE-Juel1)hkf6_20200501$$aForschergruppe Schug (hkf6_20200501)$$chkf6_20200501$$fForschergruppe Schug$$x1
000888467 588__ $$aDataset connected to CrossRef
000888467 7001_ $$0P:(DE-HGF)0$$aWeiel, Marie$$b1
000888467 7001_ $$0P:(DE-Juel1)173652$$aSchug, Alexander$$b2$$eCorresponding author
000888467 773__ $$0PERI:(DE-600)2066481-3$$a10.1002/ijch.202000007$$gVol. 60, no. 7, p. 725 - 734$$n7$$p725 - 734$$tIsrael journal of chemistry$$v60$$x1869-5868$$y2020
000888467 8564_ $$uhttps://juser.fz-juelich.de/record/888467/files/ijch.202000007.pdf$$yOpenAccess
000888467 909CO $$ooai:juser.fz-juelich.de:888467$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000888467 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)173652$$aForschungszentrum Jülich$$b2$$kFZJ
000888467 9131_ $$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$$x0
000888467 9141_ $$y2020
000888467 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2020-09-04
000888467 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000888467 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)3001$$2StatID$$aDEAL Wiley$$d2020-09-04$$wger
000888467 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000888467 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bISR J CHEM : 2018$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2020-09-04
000888467 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2020-09-04
000888467 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
000888467 9201_ $$0I:(DE-Juel1)NIC-20090406$$kNIC$$lJohn von Neumann - Institut für Computing$$x1
000888467 980__ $$ajournal
000888467 980__ $$aVDB
000888467 980__ $$aUNRESTRICTED
000888467 980__ $$aI:(DE-Juel1)JSC-20090406
000888467 980__ $$aI:(DE-Juel1)NIC-20090406
000888467 9801_ $$aFullTexts