Date of Award

Winter 2017

Project Type

Dissertation

Program or Major

Chemical Engineering

Degree Name

Doctor of Philosophy

First Advisor

Harish Vashisth

Second Advisor

Russell T. Carr

Third Advisor

Kang Wu

Abstract

I used molecular dynamics (MD) simulations as a primary tool to study folding and dynamics of signaling and regulatory proteins. Specifically, I have studied two classes of proteins: the first part of my thesis reports studies on peptides and receptors of the insulin family, and the second part reports on studies of regulatory proteins from the G-protein coupled receptor family. The first problem that I investigated was understanding the folding mechanism of the insulin B-chain and its mimetic peptide (S371) which were studied using enhanced sampling simulation methods. I validated our simulation approaches by predicting the known solution structure of the insulin B-chain helix and then applied them to study the folding of the mimetic peptide S371. Potentials of mean force (PMFs) along the reaction coordinate for each peptide are further resolved using the metadynamics method. I further proposed receptor-bound models of S371 that provide mechanistic explanations for competing binding properties of S371 and a tandem hormone-binding element of the receptor known as the C-terminal (CT) peptide. Next, I studied the all-atom structural models of peptides containing 51 residues from the transmembrane regions of IR and the type-1 insulin-like growth factor receptor (IGF1R) in a lipid membrane. In these models, the transmembrane regions of both receptors adopt helical conformations with kinks at Pro961 (IR) and Pro941 (IGF1R), but the C-terminal residues corresponding to the juxta-membrane region of each receptor adopt unfolded and flexible conformations in IR as opposed to a helix in IGF1R. I also observe that the N-terminal residues in IR form a kinked-helix sitting at the membrane-solvent interface, while homologous residues in IGF1R are unfolded and flexible. These conformational differences result in a larger tilt-angle of the membrane-embedded helix in IGF1R in comparison to IR to compensate for interactions with water molecules at the membrane-solvent interfaces. The metastable/stable states for the transmembrane domain of IR, observed in a lipid bilayer, are consistent with a known NMR structure of this domain determined in detergent micelles, and similar states in IGF1R are consistent with a previously reported model of the dimerized transmembrane domains of IGF1R. I further studied dimerization propensities of IR transmembrane domains using three different constructs in a lipid bilayer (isolated helices, ectodomain-anchored helices, and kinase-anchored helices). These studies revealed that the transmembrane domains can dimerize in isolation and in kinase-anchored forms, but not significantly in the ectodomain construct. The final studies in my thesis are focused on interplay of protein dynamics and small-molecule inhibition in a set of regulatory proteins known as the Regulators of G-protein Signaling (RGS) proteins. Thiadiazolidinone (TDZD) compounds have been shown to inhibit the protein-protein interaction between RGS and the alpha subunit of G-proteins by covalent modification of cysteine residues in RGS proteins. However, some of these cysteines in RGS proteins are not surface-exposed. I hypothesized that transient binding pockets expose cysteine residues differentially between different RGS isoforms. To explore this hypothesis, long time-scale classical MD simulations were used to probe the dynamics of three RGS proteins (RGS4, RGS8, and RGS19), and characterize flexibility in various helical motifs. The results from simulation studies were validated by hydrogen-deuterium exchange (HDX) studies, and revealed motions indicating solvent exposure of buried cysteine residues, thereby providing insights into inhibitor binding mechanisms. In addition, I used different published HDX models which have resulted in a comprehensive comparison of existing models. Furthermore, I developed the new HDX models with optimized parameters which had comparable accuracy and more computational efficiency compared to other models. Overall, my thesis has resulted in the development and applications of several state-of-the-art computational methods that have provided a detailed mechanistic understanding of peptide and small-molecule based inhibitors and their interactions with large proteins that are potentially useful in designing novel approaches to target protein-protein interactions.

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