Degree Type

Dissertation

Date of Award

2016

Degree Name

Doctor of Philosophy

Department

Biochemistry, Biophysics and Molecular Biology

Major

Bioinformatics and Computational Biology

First Advisor

Robert L. Jernigan

Abstract

A large number of protein structures have had their structures determined. However, there is still little information about their dynamics and functions. It is widely accepted that protein functionality is usually accompanied by conformational changes, and that there exists an ensemble of many structures of a given protein with different conformational states, yet the underlying mechanisms for the transitions between these states are still unclear.

Here we take a novel approach and investigate such transitions by applying forces to the structures, originating from the exothermic reactions such as ATP hydrolysis. We use the directed force application approach as well as the Metropolis Monte Carlo force application simulations within the framework of elastic network models (ENMs). The directed force application reveals the existence of strongly preferred directions of forces that can drive a protein structure towards its known end state.

When forces are applied more randomly with the Metropolis Monte Carlo method, the initial form is usually able to pass over energy barriers toward the target form and can finally achieve RMSDs of around 4 Å, matching the resolution level of the coarse-grained models themselves. Our free energy landscape agrees with the concept that native structures mostly fall in low energy regions. These landscapes are generated by computing the free energies by sampling conformations interpolated from known experimental structures, and are able in this way to suggest possible conformational transition pathways. The transitions by the application of forces are then projected onto the landscapes, and it is observed that they follow relatively low energy pathways that are overall energetically favorable. The comparison of these conformational transitions with the ENM normal modes for GroEL demonstrates that these transitions correspond well to following the low frequency modes.

Copyright Owner

Jie Liu

Language

en

File Format

application/pdf

File Size

205 pages

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