Date of Award

12-17-2010

Degree Type

Thesis-Restricted

Degree Name

M.S.

Degree Program

Computer Science

Department

Computer Science

Major Professor

Summa, Christopher

Second Advisor

Taylor, Christopher

Third Advisor

Rick, Steven

Abstract

The structures obtained from homology modeling methods are of intermediate resolution 1-3Ã… from true structure. Energy minimization methods allow us to refine the proteins and obtain native like structures. Previous work shows that some of these methods performed well on soluble proteins. So we extended this work on membrane proteins. Prediction of membrane protein structures is a particularly important, since they are important biological drug targets, and since their number is vanishingly small, as a result of the inherent difficulties in working with these molecules experimentally. Hence there is a pressing need for alternative computational protein structure prediction methods. This work tests the ability of common molecular mechanics potential functions (AMBER99/03) and a hybrid knowledge-based potential function (KB_0.1) to refine near-native structures of membrane proteins in vacuo. A web based utility for protein refinement has been developed and deployed based on the KB_0.1 potential to refine proteins.

Rights

The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation

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