Campus Access Only
All rights reserved. This publication is intended for use solely by faculty, students, and staff of University of the Pacific. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, now known or later developed, including but not limited to photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author or the publisher.
Date of Award
Thesis - Pacific Access Restricted
Master of Science (M.S.)
First Committee Member
Second Committee Member
Third Committee Member
The automated protein structure analysis (APSA) has been developed that describes protein structure via its backbone in a novel way. APSA generates a smooth line for the backbone which is completely described using curvature κ and torsion τ as a function of arc lengths. Diagrams of κ(s) and τ(s) reveal conformational features as typical patterns. In this way ideal and natural helices (α, 310 and π) and β-strands (left and right-handed, parallel and antiparallel) can be rapidly distinguished, their distortions classified, and a detailed picture of secondary structure developed. Such foundations make it possible to qualitatively and quantitatively compare domain structure utilizing calculated κ(s) and τ(s) patterns of proteins. Focusing on the torsion diagrams alone, 16 regions of τ(s) values that correspond to unique groups of conformations have been identified and encoded into 16 letters. The entire protein backbone is described, effectively projecting its three-dimensional (3D) conformation into a one-dimensional (1D) string of letters called the primary code (3D-ID projection), which is APSA's conformational equivalent of a protein's primary structure. The secondary structure is obtained from specific patterns of the primary code (resulting in secondary code). The letter code is used to describe supersecondary structure, which involves a unique characterization of the tum. It contains sufficient information to reconstruct the overall shape of a protein in an unambiguous 1D→3D translation step. Therefore, it is possible to classify supersecondary structure with the help of the letter code in form of a novel labeling system (F.#.M.X.O.L.N.R.U.S) that collects information on the relative orientations of tum and flanking structures (helices, strands). The overall shape of supersecondary structure is obtained by partitioning the surrounding space into octants and cones and assigning the parts of a supersecondary structure to these sub spaces via its labels. This approach can be easily extended to tertiary structure.
Ranganathan, Sushilee. (2008). Automated and accurate description of protein structure -- from secondary to tertiary structure. University of the Pacific, Thesis - Pacific Access Restricted. https://scholarlycommons.pacific.edu/uop_etds/707
To access this thesis/dissertation you must have a valid pacific.edu email address and log-in to Scholarly Commons.Find in PacificSearch
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).