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Experiment-Guided Molecular Modeling of Protein-Protein Complexes Involving GPCRs.


ABSTRACT: Experimental structure determination for G protein-coupled receptors (GPCRs) and especially their complexes with protein and peptide ligands is at its infancy. In the absence of complex structures, molecular modeling and docking play a large role not only by providing a proper 3D context for interpretation of biochemical and biophysical data, but also by prospectively guiding experiments. Experimentally confirmed restraints may help improve the accuracy and information content of the computational models. Here we present a hybrid molecular modeling protocol that integrates heterogeneous experimental data with force field-based calculations in the stochastic global optimization of the conformations and relative orientations of binding partners. Some experimental data, such as pharmacophore-like chemical fields or disulfide-trapping restraints, can be seamlessly incorporated in the protocol, while other types of data are more useful at the stage of solution filtering. The protocol was successfully applied to modeling and design of a stable construct that resulted in crystallization of the first complex between a chemokine and its receptor. Examples from this work are used to illustrate the steps of the protocol. The utility of different types of experimental data for modeling and docking is discussed and caveats associated with data misinterpretation are highlighted.

SUBMITTER: Kufareva I 

PROVIDER: S-EPMC4551442 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Experiment-Guided Molecular Modeling of Protein-Protein Complexes Involving GPCRs.

Kufareva Irina I   Handel Tracy M TM   Abagyan Ruben R  

Methods in molecular biology (Clifton, N.J.) 20150101


Experimental structure determination for G protein-coupled receptors (GPCRs) and especially their complexes with protein and peptide ligands is at its infancy. In the absence of complex structures, molecular modeling and docking play a large role not only by providing a proper 3D context for interpretation of biochemical and biophysical data, but also by prospectively guiding experiments. Experimentally confirmed restraints may help improve the accuracy and information content of the computation  ...[more]

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