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Title page for ETD etd-07182012-180909


Type of Document Dissertation
Author Alexander, Nathan Scott
Author's Email Address nathan.s.alexander@vanderbilt.edu
URN etd-07182012-180909
Title Protein structure elucidation from computational techniques and sparse EPR data
Degree PhD
Department Chemistry
Advisory Committee
Advisor Name Title
Jens Meiler Committee Chair
Heidi E. Hamm Committee Member
Michael P. Stone Committee Member
Terry P. Lybrand Committee Member
Keywords
  • protein structure prediction
  • spin label
  • EPR
  • structural biology
Date of Defense 2012-04-24
Availability unrestricted
Abstract
Computational methods that allow application of electron paramagnetic resonance (EPR) spectroscopy data for protein structure prediction were developed. An implicit cone-model for the spin label enabled EPR distance information to be incorporated into structure prediction methods. The small, soluble proteins T4-lysozyme and αA-crystallin were used to demonstrate the ability of EPR measurements to guide atomic-detail protein structure prediction. In addition, a spin label rotamer library was developed and incorporated into Rosetta, allowing structural interpretation of distances and dynamics observed through EPR. These methods were applied to investigate the overall structure of the GPCR rhodopsin in complex with the conjugate G-protein transducin, as well as de novo protein structure prediction of membrane proteins. The results show the ability to utilize data from EPR to aid in the prediction of membrane protein structures approaching atomic-detail accuracy. In addition, significant conformational changes were predicted to occur as transducin binds to rhodopsin, and the formation and disruption of stabilizing residue interactions were mapped according to Rosetta energy changes.
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