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Identification of Extracellular Segments by Mass Spectrometry Improves Topology Prediction of Transmembrane Proteins

Transmembrane proteins play crucial role in signaling, ion transport, nutrient uptake, as well as in maintaining the dynamic equilibrium between the internal and external environment of cells. Despite their important biological functions and abundance, less than 2% of all determined structures are t...

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Detalles Bibliográficos
Autores principales: Langó, Tamás, Róna, Gergely, Hunyadi-Gulyás, Éva, Turiák, Lilla, Varga, Julia, Dobson, László, Várady, György, Drahos, László, Vértessy, Beáta G., Medzihradszky, Katalin F., Szakács, Gergely, Tusnády, Gábor E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5304180/
https://www.ncbi.nlm.nih.gov/pubmed/28211907
http://dx.doi.org/10.1038/srep42610
Descripción
Sumario:Transmembrane proteins play crucial role in signaling, ion transport, nutrient uptake, as well as in maintaining the dynamic equilibrium between the internal and external environment of cells. Despite their important biological functions and abundance, less than 2% of all determined structures are transmembrane proteins. Given the persisting technical difficulties associated with high resolution structure determination of transmembrane proteins, additional methods, including computational and experimental techniques remain vital in promoting our understanding of their topologies, 3D structures, functions and interactions. Here we report a method for the high-throughput determination of extracellular segments of transmembrane proteins based on the identification of surface labeled and biotin captured peptide fragments by LC/MS/MS. We show that reliable identification of extracellular protein segments increases the accuracy and reliability of existing topology prediction algorithms. Using the experimental topology data as constraints, our improved prediction tool provides accurate and reliable topology models for hundreds of human transmembrane proteins.