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Conformation and Dynamics of the Troponin I C‑Terminal Domain: Combining Single-Molecule and Computational Approaches for a Disordered Protein Region

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journal contribution
posted on 23.09.2015, 00:00 by Lauren Ann Metskas, Elizabeth Rhoades
In recent years, single-molecule Förster resonance energy transfer (smFRET) has emerged as a critical and flexible tool in structural biology, particularly in the study of highly dynamic regions and molecular assemblies. The usefulness of smFRET can be further extended by combining it with computational approaches, marrying the coarse-grained experimental data with higher-resolution in silico calculations. Here we use smFRET to determine six pairwise distances within the intrinsically disordered C-terminal domain of the troponin I subunit (TnIC) of the cardiac troponin complex. We used published conflicting structures of TnIC as starting models for molecular dynamics simulations, which were validated through successful comparison with smFRET measurements before extracting information on conformational dynamics. We find that pairwise distances between residues fluctuate widely in silico, but simulations are generally in good agreement with longer time scale smFRET measurements after averaging across time. Finally, Monte Carlo simulations establish that the lower-energy conformers of TnIC are indeed varied, but that the highest-sampled clusters resemble the published, conflicting models. In this way, we find that the controversial structures are simply stabilized local minima of this dynamic region, and a population including all three would still be consistent with spectroscopic measurements. Taken together, the combined approaches described here allow us to critically evaluate existing models of TnIC, giving insight into the conformation and dynamics of TnIC’s disordered state prior to its probable disorder–order transition. Moreover, they provide a framework for combining computational and experimental methods with different time scales for the study of disordered and dynamic protein states.