期刊
BIOPHYSICAL JOURNAL
卷 95, 期 11, 页码 5281-5295出版社
CELL PRESS
DOI: 10.1529/biophysj.108.132241
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资金
- National Institutes of Health [R01-GM52032, R24 GM069736]
- United States Environmental Protection Agency [GAD-R-832721-010]
The field of protein structure prediction has seen significant advances in recent years. Researchers have followed a multitude of approaches, including methods based on comparative modeling, fold recognition and threading, and first-principles techniques. It is noteworthy that the structure prediction of membrane proteins is comparatively less studied by researchers in the field. A membrane protein is characterized by a protein structure that extends into or through the lipid-lipid bilayer of a cell. The structure is influenced by the combination of the hydrophobic bilayer region, the direct interaction with the bilayer, and the aqueous external environment. Due to the difficulty in obtaining reliable experimental structures, accurate computational prediction of membrane proteins is of paramount importance. An optimization model has been developed to predict the interhelical interactions in alpha-helical membrane proteins. A database of alpha-helical membrane proteins of known structure and limited sequence identity can be constructed to develop interaction probabilities. By then maximizing the occurrence of highly probable pariwise or three-residue interactions, realistic contacts can be predicted by imposing a number of geometrical constraints. The development of these low distance contacts can provide additional distance restraints for first principles-based approaches to the tertiary structure prediction problem. The proposed approach is shown to successfully predict interhelical contacts in several membrane protein systems, including bovine rhodopsin and the recently released human beta 2 adrenergic receptor protein structure.
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