Title page for ETD etd-05172006-182808


Type of Document Dissertation
Author Asbury, Thomas M
URN etd-05172006-182808
Title From Data to Structure: Using Orientational Information Within PISEMA Spectra to Build Atomic Models
Degree PhD
Department Molecular Biophysics, Institute of
Advisory Committee
Advisor Name Title
Richard Bertram Committee Chair
Jack R. Quine Committee Member
Michael S. Chapman Committee Member
Piyush Kumar Committee Member
Timothy A. Cross Committee Member
Keywords
  • solid-state NMR
  • membrane proteins
  • Influenza A
  • structural biology
Date of Defense 2006-05-01
Availability unrestricted
Abstract
Atomic structure determination of membrane proteins is an important

problem. Because of the difficulties in crystallization and

traditional NMR techniques using membrane proteins, other experimental

methods are being developed and investigated.

One such method, the solid-state NMR PISEMA

(Polar Inversion Spin-Exchange at the Magic Angle)

experiment, determines orientational contraints for the target membrane protein.

These constraints can be used to build a high resolution atomic model.

This dissertation presents a detailed analysis

of the PISEMA experimental data set and how it can

be used to derive atomic structure. One of the aspects of

the data set is that it is degenerate, that is, the orientational information

measured by the data does not uniquely describe atomic locations.

Thus, there are many possible structures that would provide the same data.

An important goal of this work is to enumerate and characterize

these degeneracies throughout each phase of model building and provide

computational tools to manage them.

The process of building atomic models from PISEMA data

involves three major steps: assignment, initial model building

and atomic refinement. For each step we present new

software that is intended to aid in the model building process.

The tools are designed to be used consecutively with limited,

though significant, human intervention.

The last section of the dissertation presents an application of

our tools to a new PISEMA data set, from which we derive

the first high-resolution atomic structure of the transmembrane

portion of the M2 proton channel from the Influenza A virus

in the presence of amantadine.For this case,

we explain both the data processing and

decision making that determined the final atomic model.

It is likely that this semi-automated procedure will be

applicable to other

transmembrane protein PISEMA data sets.

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