A knowledge-based scale for the analysis and prediction of buried and exposed faces of transmembrane domain proteins | Zendy

Thijs Beuming | Zendy; Harel Weinstein | Zendy

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A knowledge-based scale for the analysis and prediction of buried and exposed faces of transmembrane domain proteins

Author(s) -

Thijs Beuming,

Harel Weinstein

Publication year - 2004

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bth143

Subject(s) - domain (mathematical analysis) , scale (ratio) , computer science , transmembrane protein , transmembrane domain , computational biology , artificial intelligence , pattern recognition (psychology) , biology , mathematics , genetics , geography , cartography , membrane , mathematical analysis , receptor

The dearth of structural data on alpha-helical membrane proteins (MPs) has hampered thus far the development of reliable knowledge-based potentials that can be used for automatic prediction of transmembrane (TM) protein structure. While algorithms for identifying TM segments are available, modeling of the TM domains of alpha-helical MPs involves assembling the segments into a bundle. This requires the correct assignment of the buried and lipid-exposed faces of the TM domains.

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