Doctor of Philosophy / Department of Biochemistry and Molecular Biophysics / Jianhan Chen / Intrinsically disordered proteins (IDPs) are functional proteins that lack stable tertiary structures under physiological conditions. IDPs are key components of regulatory networks that dictate various aspects of cellular decision-making, and are over-represented in major disease pathways. For example, about 30% of eukaryotic proteins contain intrinsic disordered regions, and over 70% of cancer-associated proteins have been identified as IDPs. The highly heterogeneous nature of IDPs has presented significant challenge for experimental characterization using NMR, X-ray crystallography, or FRET. These challenges represent a unique opportunity for molecular mod- eling to make critical contributions. In this study, computer simulations at multiple scales were utilized to characterize the structural properties of unbound IDPs as well as to obtain a mechanistic understanding of IDP interactions. These studies of IDPs also reveal significant limitations in the current simulation methodology. In particular, successful simulations of biomolecules not only require accurate molecular models, but also depend on the ability to sufficiently sample the com- plex conformational space. By designing a realistic yet computationally tractable coarse-grained protein model, we demonstrated that the popular temperature replica exchange enhanced sampling is ineffective in driving faster reversible folding transitions for proteins. The second original contribution of this dissertation is the development of novel simulation methods for enhanced sampling of protein conformations, specifically, replica exchange with guided-annealing (RE-GA) method and multiscale enhanced sampling (MSES) method. We expect these methods to be highly useful in generating converged conformational ensembles.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/17916 |
| Date | January 1900 |
| Creators | Zhang, Weihong |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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