Abstract
Membrane proteins are of particular biological and pharmaceutical importance, and computational modeling and structure prediction approaches play an important role in studies of membrane proteins. Developing an accurate model quality assessment program is of significance to the structure prediction of membrane proteins. Few such programs are proposed that can be applied to a broad range of membrane protein classes and perform with high accuracy. We developed a new model scoring function Interaction-based Quality assessment (IQ), based on the analysis of four types of inter-residue interactions within the transmembrane domains of helical membrane proteins. This function was tested using three high-quality model sets: all 206 models of GPCR Dock 2008, all 284 models of GPCR Dock 2010, and all 92 helical membrane protein models of the HOMEP set. For all three sets, the scoring function can select the native structures among all of the models with the success rates of 93, 85, and 100% respectively. For comparison, these three model sets were also adopted for a recently published model assessment program for membrane protein structures, ProQM, which gave the success rates of 85, 79, and 92% separately. These results suggested that IQ outperforms ProQM when only the transmembrane regions of the models are considered. This scoring function should be useful for the computational modeling of membrane proteins.
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Acknowledgments
The authors thank Dr. Vagmita Pabuwal at our group at the University of the Sciences in Philadelphia for helpful discussion and technical support. We thank Drs. Irina Kufareva and Raymond Stevens for sharing with us the GPCR Dock 2010 dataset of membrane protein models, and Drs. Lucy R. Forrest and Barry Honig for sharing with us the HOMEP dataset of membrane protein models. We thank our anonymous reviewers for constructive comments. This work was supported by the National Institutes of Health grant R15-GM084404.
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Heim, A.J., Li, Z. Developing a high-quality scoring function for membrane protein structures based on specific inter-residue interactions. J Comput Aided Mol Des 26, 301–309 (2012). https://doi.org/10.1007/s10822-012-9556-z
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DOI: https://doi.org/10.1007/s10822-012-9556-z