Degree Type

Dissertation

Date of Award

2008

Degree Name

Doctor of Philosophy

Department

Theses & dissertations (Interdisciplinary)

Major

Bioinformatics and Computational Biology

First Advisor

Robert L. Jernigan

Second Advisor

Zhijun Wu

Third Advisor

Drena Dobbs

Abstract

Because of its appealing simplicity, the elastic network model (ENM) has been widely accepted and applied to study many molecular motion problems, such as the molecular mechanisms of chaperonin GroEL-GroES function, allosteric changes in hemoglobin, ribosome motions, motor-protein motions, and conformational changes in general. In this dissertation, the ENM is employed to study various protein dynamics problems, and its validity is also examined by comparing with experimental data. First, we apply principal component analysis (PCA) to identify the essential protein motions from multiple structures (X-ray, NMR and MD) of the HIV-1 protease. We find significant similarities between the first few of these key motions and the first few low-frequency normal modes from the ENM, suggesting that the ENM provides a coarse-grained and structurally-based explanation for the experimentally observed conformational changes. Second, we extend these approaches from a single protein (HIV-1 protease) to thousands of proteins whose multiple NMR structures are available. We also find close correspondence between the experimentally observed dynamics and the ENM predicted ones, indicating the validity of using the ENM to computationally predict protein dynamics. Third, we develop a regression model for the isotropic B-factor predictions by combining the protein rigid body motions with the ENM. The new model shows significant improvements in B-factor predictions. Fourth, we further examine the validity of using the ENM to study protein motions. We use the anisotropic form of ENM to predict the anisotropic temperature factors of proteins. It presents a timely and important evaluation of the model, shows the extent of its accuracy in reproducing experimental anisotropic temperature factors, and suggests ways to improve the model. Finally, we apply the ENM to study a dataset of 170 protein pairs having "open" and "closed" structures, and try to address how well a conformational change can be predicted by the ENM and how to improve the model. The results indicate that the applicability of ENM for explaining conformational changes is not limited by either the size of the studied protein or even the scale of the conformational change. Instead, it depends strongly on how collective the transition is.

DOI

https://doi.org/10.31274/rtd-180813-17026

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/

Copyright Owner

Lei Yang

Language

en

Proquest ID

AAI3316179

OCLC Number

274129191

ISBN

9780549688105

File Format

application/pdf

File Size

116 pages

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