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1000 Titel
  • GPCR-SSFE 2.0—a fragment-based molecular modeling web tool for Class A G-protein coupled receptors
1000 Autor/in
  1. Worth, Catherine L. |
  2. Kreuchwig, Franziska |
  3. Tiemann, Johanna K.S. |
  4. Kreuchwig, Annika |
  5. Ritschel, Michele |
  6. Kleinau, Gunnar |
  7. Hildebrand, Peter W. |
  8. Krause, Gerd |
1000 Erscheinungsjahr 2017
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2017-06-05
1000 Erschienen in
1000 Quellenangabe
  • 45(W1): W408–W415,
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2017
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1093/nar/gkx399 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570183/ |
1000 Ergänzendes Material
  • https://academic.oup.com/nar/article/45/W1/W408/3861266#supplementary-data |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • G-protein coupled receptors (GPCRs) are key players in signal transduction and therefore a large proportion of pharmaceutical drugs target these receptors. Structural data of GPCRs are sparse yet important for elucidating the molecular basis of GPCR-related diseases and for performing structure-based drug design. To ameliorate this problem, GPCR-SSFE 2.0 (http://www.ssfa-7tmr.de/ssfe2/), an intuitive web server dedicated to providing three-dimensional Class A GPCR homology models has been developed. The updated web server includes 27 inactive template structures and incorporates various new functionalities. Uniquely, it uses a fingerprint correlation scoring strategy for identifying the optimal templates, which we demonstrate captures structural features that sequence similarity alone is unable to do. Template selection is carried out separately for each helix, allowing both single-template models and fragment-based models to be built. Additionally, GPCR-SSFE 2.0 stores a comprehensive set of pre-calculated and downloadable homology models and also incorporates interactive loop modeling using the tool SL2, allowing knowledge-based input by the user to guide the selection process. For visual analysis, the NGL viewer is embedded into the result pages. Finally, blind-testing using two recently published structures shows that GPCR-SSFE 2.0 performs comparably or better than other state-of-the art GPCR modeling web servers.
1000 Fachgruppe
  1. Biologie |
  2. Medizin |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/V29ydGgsIENhdGhlcmluZSBMLg==|https://frl.publisso.de/adhoc/creator/S3JldWNod2lnLCBGcmFuemlza2E=|https://frl.publisso.de/adhoc/creator/VGllbWFubiwgSm9oYW5uYSBLLlMu|https://frl.publisso.de/adhoc/creator/S3JldWNod2lnLCBBbm5pa2E=|https://frl.publisso.de/adhoc/creator/Uml0c2NoZWwsIE1pY2hlbGU=|https://frl.publisso.de/adhoc/creator/S2xlaW5hdSwgR3VubmFy|https://frl.publisso.de/adhoc/creator/SGlsZGVicmFuZCwgUGV0ZXIgVy4=|https://frl.publisso.de/adhoc/creator/S3JhdXNlLCBHZXJk
1000 Förderer
  1. Deutsche Forschungsgemeinschaft (DFG) |
  2. Leibniz Association |
1000 Fördernummer
  1. KR 1273/4-2; DFG HI 1502/1-2; BI 893/8
  2. -
1000 Förderprogramm
  1. -
  2. Open Access fund
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft (DFG) |
    1000 Förderprogramm -
    1000 Fördernummer KR 1273/4-2; DFG HI 1502/1-2; BI 893/8
  2. 1000 joinedFunding-child
    1000 Förderer Leibniz Association |
    1000 Förderprogramm Open Access fund
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6406148.rdf
1000 Erstellt am 2018-01-04T15:32:07.273+0100
1000 Erstellt von 218
1000 beschreibt frl:6406148
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet Tue May 22 08:21:43 CEST 2018
1000 Objekt bearb. Tue May 22 08:21:43 CEST 2018
1000 Vgl. frl:6406148
1000 Oai Id
  1. oai:frl.publisso.de:frl:6406148 |
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