Title |
High-Resolution Modeling of Transmembrane Helical Protein Structures from Distant Homologues
|
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Published in |
PLoS Computational Biology, May 2014
|
DOI | 10.1371/journal.pcbi.1003636 |
Pubmed ID | |
Authors |
Kuang-Yui M. Chen, Jiaming Sun, Jason S. Salvo, David Baker, Patrick Barth |
Abstract |
Eukaryotic transmembrane helical (TMH) proteins perform a wide diversity of critical cellular functions, but remain structurally largely uncharacterized and their high-resolution structure prediction is currently hindered by the lack of close structural homologues. To address this problem, we present a novel and generic method for accurately modeling large TMH protein structures from distant homologues exhibiting distinct loop and TMH conformations. Models of the adenosine A2AR and chemokine CXCR4 receptors were first ranked in GPCR-DOCK blind prediction contests in the receptor structure accuracy category. In a benchmark of 50 TMH protein homolog pairs of diverse topology (from 5 to 12 TMHs), size (from 183 to 420 residues) and sequence identity (from 15% to 70%), the method improves most starting templates, and achieves near-atomic accuracy prediction of membrane-embedded regions. Unlike starting templates, the models are of suitable quality for computer-based protein engineering: redesigned models and redesigned X-ray structures exhibit very similar native interactions. The method should prove useful for the atom-level modeling and design of a large fraction of structurally uncharacterized TMH proteins from a wide range of structural homologues. |
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Demographic breakdown
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Geographical breakdown
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Researcher | 19 | 20% |
Student > Bachelor | 7 | 7% |
Student > Postgraduate | 6 | 6% |
Student > Master | 6 | 6% |
Other | 11 | 12% |
Unknown | 11 | 12% |
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Other | 9 | 9% |
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