↓ Skip to main content

PLOS

High-Resolution Modeling of Transmembrane Helical Protein Structures from Distant Homologues

Overview of attention for article published in PLoS Computational Biology, May 2014
Altmetric Badge

Mentioned by

twitter
5 X users

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
95 Mendeley
citeulike
1 CiteULike
Title
High-Resolution Modeling of Transmembrane Helical Protein Structures from Distant Homologues
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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Korea, Republic of 1 1%
Ireland 1 1%
India 1 1%
Denmark 1 1%
United States 1 1%
Unknown 89 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 37%
Researcher 19 20%
Student > Bachelor 7 7%
Student > Postgraduate 6 6%
Student > Master 6 6%
Other 11 12%
Unknown 11 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 34%
Biochemistry, Genetics and Molecular Biology 27 28%
Chemistry 9 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Computer Science 4 4%
Other 9 9%
Unknown 10 11%