OpenSSL SSL_connect: Connection reset by peer in connection to v2.sherpa.ac.uk:443 PuSH - Publication Server of Helmholtz Zentrum München: Structural and functional protein network analyses predict novel signaling functions for rhodopsin.

PuSH - Publication Server of Helmholtz Zentrum München

Kiel, C.* ; Vogt, A. ; Campagna, A.* ; Chatr-aryamontri, A.* ; Swiatek-de Lange, M. ; Beer, M. ; Bolz, S.* ; Mack, A.F.* ; Kinkl, N.* ; Cesareni, G.* ; Serrano, L.* ; Ueffing, M.

Structural and functional protein network analyses predict novel signaling functions for rhodopsin.

Mol. Syst. Biol. 7:551 (2011)
Publ. Version/Full Text Volltext DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Orchestration of signaling, photoreceptor structural integrity, and maintenance needed for mammalian vision remain enigmatic. By integrating three proteomic data sets, literature mining, computational analyses, and structural information, we have generated a multiscale signal transduction network linked to the visual G protein-coupled receptor (GPCR) rhodopsin, the major protein component of rod outer segments. This network was complemented by domain decomposition of protein-protein interactions and then qualified for mutually exclusive or mutually compatible interactions and ternary complex formation using structural data. The resulting information not only offers a comprehensive view of signal transduction induced by this GPCR but also suggests novel signaling routes to cytoskeleton dynamics and vesicular trafficking, predicting an important level of regulation through small GTPases. Further, it demonstrates a specific disease susceptibility of the core visual pathway due to the uniqueness of its components present mainly in the eye. As a comprehensive multiscale network, it can serve as a basis to elucidate the physiological principles of photoreceptor function, identify potential disease-associated genes and proteins, and guide the development of therapies that target specific branches of the signaling pathway.
Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords protein interaction network; rhodopsin signaling; structural modeling
ISSN (print) / ISBN 1744-4292
e-ISSN 1744-4292
Journal Molecular Systems Biology
Quellenangaben Volume: 7, Issue: , Pages: , Article Number: 551 Supplement: ,
Publisher EMBO Press
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) CF Metabolomics & Proteomics (CF-MPC)