ESSENTIAL DYNAMICS OF PROTEINS USING GEOMETRICAL SIMULATIONS AND SUBSPACE ANALYSIS

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David, C. (2012). ESSENTIAL DYNAMICS OF PROTEINS USING GEOMETRICAL SIMULATIONS AND SUBSPACE ANALYSIS. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Essential dynamics is the application of principal component analysis to a dynamic trajectory derived from a simulation protocol in order to extract biologically relevant information contained in the high dimensional data. In this work, we apply the methodology of essential dynamics to protein trajectories derived from geometrical simulations, which are based on the perturbation of geometrical constraints inherent in a protein. Specifically, we show that the geometrical simulation model is highly efficient for the determination of native state dynamics. Furthermore, by the application of subspace analysis to the essential subspaces of multiple sets of proteins that were simulated under multiple modeling paradigms, we show that the geometrical modeling paradigm is internally consistent and provides results that are qualitatively and quantitatively similar to results obtained from the more commonly employed methods of elastic network models and molecular dynamics. The geometrical paradigm is therefore established as a viable alternative or co-model for the investigation of native state protein dynamics with application to both small, single domain proteins as well as large, multi domain systems.

Details
Author

David, Charles

Title

ESSENTIAL DYNAMICS OF PROTEINS USING GEOMETRICAL SIMULATIONS AND SUBSPACE ANALYSIS

Physical Description

1 online resource (159 pages) : PDF

Date

2012

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Essential dynamics is the application of principal component analysis to a dynamic trajectory derived from a simulation protocol in order to extract biologically relevant information contained in the high dimensional data. In this work, we apply the methodology of essential dynamics to protein trajectories derived from geometrical simulations, which are based on the perturbation of geometrical constraints inherent in a protein. Specifically, we show that the geometrical simulation model is highly efficient for the determination of native state dynamics. Furthermore, by the application of subspace analysis to the essential subspaces of multiple sets of proteins that were simulated under multiple modeling paradigms, we show that the geometrical modeling paradigm is internally consistent and provides results that are qualitatively and quantitatively similar to results obtained from the more commonly employed methods of elastic network models and molecular dynamics. The geometrical paradigm is therefore established as a viable alternative or co-model for the investigation of native state protein dynamics with application to both small, single domain proteins as well as large, multi domain systems.

Genre

doctoral dissertations

Subjects--Topics

Physics
Bioinformatics
Biophysics

Degree

Ph.D.

Keywords

Comparative Modeling
Essential Dynamics
Geometrical Simulation
PCA
Protein Dynamics
Subspace Analysis

Subject Area

Information Technology

Advisor(s)

Jacobs, Donald

Committee Members

Livesay, Dennis
Fodor, Anthony
Nesmelov, Yuri

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2012.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

David_uncc_0694D_10357

Permalink

http://hdl.handle.net/20.500.13093/etd:352