Comparing four different approaches for the determination of inter-residue interactions provides insight for the structure prediction of helical membrane proteins.
Studying inter-residue interactions provides insight into the folding and stability of both soluble and membrane proteins and is essential for developing computational tools for protein structure prediction. As the first step, various approaches for elucidating such interactions within protein structures have been proposed and proven useful. Since different approaches may grasp different aspects of protein structural folds, it is of interest to systematically compare them. In this work, we applied four approaches for determining inter-residue interactions to the analysis of three distinct structure datasets of helical membrane proteins and compared their correlation to the three individual quality measures of structures in these datasets. These datasets included one of 35 structures of rhodopsin receptors and bacterial rhodopsins determined at various resolutions, one derived from the HOMEP benchmark dataset previously reported, and one comprising of 139 homology models. It was found that the correlation between the average number of inter-residue interactions obtained by applying the four approaches and the available structure quality measures varied quite significantly among them. The best correlation was achieved by the approach focusing exclusively on favorable inter-residue interactions. These results provide interesting insight for the development of objective quality measure for the structure prediction of helical membrane proteins.
Gao
Jun
J
Department of Bioinformatics, University of the Sciences in Philadelphia, Philadelphia, PA 19104, USA.
Li
Zhijun
Z
D000596:Amino Acids / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D008958:Models, Molecular; D017433:Protein Structure, Secondary; D012243:Rhodopsin / Q000737:chemistry*; D040681:Structural Homology, Protein
D000596:Amino Acids; D012243:Rhodopsin