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Event Date and Time
Gore 104
Dr. Paul Robustelli, DE Shaw Research
Many proteins that perform important biological functions are completely or partially disordered under physiological conditions. These so-called “intrinsically disordered proteins” do not adopt a well-defined three-dimensional structure in isolation, but instead populate a heterogeneous ensemble of rapidly interconverting conformational states. If a sufficiently accurate physical model (“force field”) is used, atomistic molecular dynamics (MD) simulations can serve as a valuable tool for characterizing the structural and dynamic properties of intrinsically disordered proteins. By comparing long-timescale MD simulations of ordered and disordered proteins to experimental data, we have systematically identified limitations in current physical models and have developed new force fields that provide substantially improved accuracy in simulations of disordered proteins while maintaining state-of-the-art accuracy for folded proteins. These new force fields have enabled us to study mechanisms of molecular recognition in intrinsically disordered proteins in atomistic detail. In unbiased MD simulations of an intrinsically disordered protein and its physiological binding partner we observed a large number of spontaneous folding-upon-binding events, where the disordered protein undergoes a transition to a defined structure in the bound complex, allowing us to carefully dissect and characterize the coupled folding-upon-binding mechanisms. In a second application, unbiased MD simulations of α-synuclein, an intrinsically disordered protein associated with Parkinson’s disease, and Fasudil, a small molecule drug that has been shown to inhibit α-synuclein misfolding and attenuate Parkinson’s pathology in mouse models, reproduce a binding interaction observed by NMR spectroscopy experiments. These simulations have enabled us to rationalize the molecule’s affinity for the experimentally observed binding site using a dynamic binding mechanism model in which α-synuclein remains flexible as it interacts with the small molecule in a variety of binding modes. Based on this mechanism, we have conducted a computational screen of small molecules selected to modify the bound ensemble and the affinity of the interaction. NMR measurements of a representative series of small molecules are in line with predictions of relative binding affinities and have provided support for details of the simulated binding mechanism and its perturbations. We are currently exploring the possibility of using dynamic binding mechanisms observed in MD simulations to rationally design molecules that exhibit improved binding to intrinsically disordered proteins.