Network pattern of residue packing in helical membrane proteins and its application in membrane protein structure prediction.
De novo protein structure prediction plays an important role in studies of helical membrane proteins as well as structure-based drug design efforts. Developing an accurate scoring function for protein structure discrimination and validation remains a current challenge. Network approaches based on overall network patterns of residue packing have proven useful in soluble protein structure discrimination. It is thus of interest to apply similar approaches to the studies of residue packing in membrane proteins. In this work, we first carried out such analysis on a set of diverse, non-redundant and high-resolution membrane protein structures. Next, we applied the same approach to three test sets. The first set includes nine structures of membrane proteins with the resolution worse than 2.5 A; the other two sets include a total of 101 G-protein coupled receptor models, constructed using either de novo or homology modeling techniques. Results of analyses indicate the two criteria derived from studying high-resolution membrane protein structures are good indicators of a high-quality native fold and the approach is very effective for discriminating native membrane protein folds from less-native ones. These findings should be of help for the investigation of the fundamental problem of membrane protein structure prediction.
Pabuwal
Vagmita
V
Departments of Chemistry and Biochemistry, University of Sciences in Philadelphia, Philadelphia, PA 19104, USA.
Li
Zhijun
Z
D000818:Animals; D001185:Artificial Intelligence; D002417:Cattle; D030562:Databases, Protein; D008565:Membrane Proteins / Q000737:chemistry*; D008956:Models, Chemical; D017433:Protein Structure, Secondary; D012243:Rhodopsin / Q000737:chemistry; D017386:Sequence Homology, Amino Acid
D008565:Membrane Proteins; D012243:Rhodopsin