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Assessment of the transmembrane domain structures in GPCR Dock 2013 models.


ABSTRACT: The community-wide blind prediction of G-protein coupled receptor (GPCR) structures and ligand docking has been conducted three times and the quality of the models was primarily assessed by the accuracy of ligand binding modes. The seven transmembrane (TM) helices of the receptors were taken as a whole; thus the model quality within the 7TM domains has not been evaluated. Here we evaluate the 7TM domain structures in the models submitted for the last round of prediction - GPCR Dock 2013. Applying the 7?×?7 RMSD matrix analysis described in our prior work, we show that the models vary widely in prediction accuracy of the 7TM structures, exhibiting diverse structural differences from the targets. For the prediction of the 5-hydroxytryptamine receptors, the top 7TM models are rather close to the targets, which however are not ranked top by ligand-docking. On the other hand, notable deviations of the TMs are found in in the previously identified top docking models that closely resemble other receptors. We further reveal reasons of success and failure in ligand docking for the models. This current assessment not only complements the previous assessment, but also provides important insights into the current status of GPCR modeling and ligand docking.

SUBMITTER: Wang T 

PROVIDER: S-EPMC5820147 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Assessment of the transmembrane domain structures in GPCR Dock 2013 models.

Wang Ting T   Liu Haiguang H   Duan Yong Y  

Journal of structural biology 20171121 3


The community-wide blind prediction of G-protein coupled receptor (GPCR) structures and ligand docking has been conducted three times and the quality of the models was primarily assessed by the accuracy of ligand binding modes. The seven transmembrane (TM) helices of the receptors were taken as a whole; thus the model quality within the 7TM domains has not been evaluated. Here we evaluate the 7TM domain structures in the models submitted for the last round of prediction - GPCR Dock 2013. Applyin  ...[more]

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