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J Am Chem Soc. 2016 Aug 10;138(31):9826-39. doi: 10.1021/jacs.6b02382. Epub 2016 Aug 2.

Capturing a Dynamic Chaperone-Substrate Interaction Using NMR-Informed Molecular Modeling.

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Department of Molecular, Cellular and Developmental Biology, and the Howard Hughes Medical Institute, University of Michigan , Ann Arbor, Michigan 48109, United States.
Department of Chemistry, University of Michigan , Ann Arbor, Michigan 48109, United States.
Biophysics Program, University of Michigan , Ann Arbor, Michigan 48109, United States.


Chaperones maintain a healthy proteome by preventing aggregation and by aiding in protein folding. Precisely how chaperones influence the conformational properties of their substrates, however, remains unclear. To achieve a detailed description of dynamic chaperone-substrate interactions, we fused site-specific NMR information with coarse-grained simulations. Our model system is the binding and folding of a chaperone substrate, immunity protein 7 (Im7), with the chaperone Spy. We first used an automated procedure in which NMR chemical shifts inform the construction of system-specific force fields that describe each partner individually. The models of the two binding partners are then combined to perform simulations on the chaperone-substrate complex. The binding simulations show excellent agreement with experimental data from multiple biophysical measurements. Upon binding, Im7 interacts with a mixture of hydrophobic and hydrophilic residues on Spy's surface, causing conformational exchange within Im7 to slow down as Im7 folds. Meanwhile, the motion of Spy's flexible loop region increases, allowing for better interaction with different substrate conformations, and helping offset losses in Im7 conformational dynamics that occur upon binding and folding. Spy then preferentially releases Im7 into a well-folded state. Our strategy has enabled a residue-level description of a dynamic chaperone-substrate interaction, improving our understanding of how chaperones facilitate substrate folding. More broadly, we validate our approach using two other binding partners, showing that this approach provides a general platform from which to investigate other flexible biomolecular complexes through the integration of NMR data with efficient computational models.

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