Characterization of Intrinsically Disordered Peptide Ensembles



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Intrinsically disordered proteins/peptides (IDPs) are a category of proteins that possess a poorly defined equilibrium structure. IDPs have been shown to play a central role in biological systems, however atomistic details about their binding mechanisms, selectivity, and specificity are poorly understood. The structures of IDPs are particularly challenging to study directly using experimental techniques due to their rapid inter-conversion of ensemble conformations. Similarly, theoretical techniques such as molecular dynamics simulations (MD), are typically parameterized via experimentally determined observables of stable proteins and therefore contain inherent biasing. Moreover, MD data refinement requires clustering of uniquely sampled structures in order to produce a non-biased ensemble. The work presented within this dissertation aims to remedy these IDP structure determination challenges by using circular dichroism (CD) to refine the conformations obtained from all-atom MD trajectories, and cluster the resulting conformations to remove degenerate structures in order to produce an unbiased ensemble with atomic resolution. The future application of the generated structure ensembles towards IDP binding mechanism determination using a Markov State Model (MSM) is discussed and outlined.



IDP, proteins, disordered proteins, circular dichroism, molecular dynamics, clustering, Markov State Model


Portions of this document appear in: Ezerski, Jacob C., and Margaret S. Cheung. "CATS: A Tool for Clustering the Ensemble of Intrinsically Disordered Peptides on a Flat Energy Landscape." The Journal of Physical Chemistry B 122, no. 49 (2018): 11807-11816.