New Algorithms for Protein Structure Analysis: From Nonparametric Density Estimation to Characterization of Molecular Volume Spatial Distributions

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Farmer, J. (2018). New Algorithms for Protein Structure Analysis: From Nonparametric Density Estimation to Characterization of Molecular Volume Spatial Distributions. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

The Flexibility and Stability Test (FAST) is a C++ class library designed in the early 2000’s to execute free energy decomposition and reconstitution operations applied to protein structures. The library has been substantially expanded to include structural bioinformatics tools useful in the analysis of protein dynamics. Motivated to advance FAST by improving modeling aspects on atomic packing and solvation, two new algorithms have been developed and implemented, enabling high throughput nonparametric probability density estimation and spatial characterization of cavity volume in proteins. In two separate studies involving molecular dynamics trajectories, novel methods were developed for the analysis of statistical significance in the dynamics of beta-lactamase mutants. Additionally, the core methodologies developed through these studies have been validated as critical components of the FAST library, which aims to advance the field of computational biology and structural bioinformatics as a next generation simulation software for protein and drug design.

Details
Author

Farmer, Jenny

Title

New Algorithms for Protein Structure Analysis: From Nonparametric Density Estimation to Characterization of Molecular Volume Spatial Distributions

Physical Description

1 online resource (121 pages) : PDF

Date

2018

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

The Flexibility and Stability Test (FAST) is a C++ class library designed in the early 2000’s to execute free energy decomposition and reconstitution operations applied to protein structures. The library has been substantially expanded to include structural bioinformatics tools useful in the analysis of protein dynamics. Motivated to advance FAST by improving modeling aspects on atomic packing and solvation, two new algorithms have been developed and implemented, enabling high throughput nonparametric probability density estimation and spatial characterization of cavity volume in proteins. In two separate studies involving molecular dynamics trajectories, novel methods were developed for the analysis of statistical significance in the dynamics of beta-lactamase mutants. Additionally, the core methodologies developed through these studies have been validated as critical components of the FAST library, which aims to advance the field of computational biology and structural bioinformatics as a next generation simulation software for protein and drug design.

Genre

doctoral dissertations

Subjects--Topics

Bioinformatics
Biophysics
Physics

Degree

Ph.D.

Subject Area

Bioinformatics

Advisor(s)

Jacobs, Donald

Committee Members

Nesmelova, Irina
Gibas, Cynthia
Guo, Jun-tao
Akella, Srinivas

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2018.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

Farmer_uncc_0694D_11886

Permalink

http://hdl.handle.net/20.500.13093/etd:851