Jump to ContentJump to Main Navigation
Pattern Discovery in Biomolecular DataTools, Techniques, and Applications$
Users without a subscription are not able to see the full content.

Jason T. L. Wang, Bruce A. Shapiro, and Dennis Shasha

Print publication date: 1999

Print ISBN-13: 9780195119404

Published to Oxford Scholarship Online: November 2020

DOI: 10.1093/oso/9780195119404.001.0001

Show Summary Details
Page of

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 14 June 2021

RNA Structure Analysis: A Multifaceted Approach

RNA Structure Analysis: A Multifaceted Approach

Chapter:
(p.183) Chapter 11 RNA Structure Analysis: A Multifaceted Approach
Source:
Pattern Discovery in Biomolecular Data
Author(s):

Bruce A. Shapiro

Wojciech Kasprzak

Publisher:
Oxford University Press
DOI:10.1093/oso/9780195119404.003.0018

Genomic information (nucleic acid and amino acid sequences) completely determines the characteristics of the nucleic acid and protein molecules that express a living organism’s function. One of the greatest challenges in which computation is playing a role is the prediction of higher order structure from the one-dimensional sequence of genes. Rules for determining macromolecule folding have been continually evolving. Specifically in the case of RNA (ribonucleic acid) there are rules and computer algorithms/systems (see below) that partially predict and can help analyze the secondary and tertiary interactions of distant parts of the polymer chain. These successes are very important for determining the structural and functional characteristics of RNA in disease processes and hi the cell life cycle. It has been shown that molecules with the same function have the potential to fold into similar structures though they might differ in their primary sequences. This fact also illustrates the importance of secondary and tertiary structure in relation to function. Examples of such constancy in secondary structure exist in transfer RNAs (tRNAs), 5s RNAs, 16s RNAs, viroid RNAs, and portions of retroviruses such as HIV. The secondary and tertiary structure of tRNA Phe (Kim et al., 1974), of a hammerhead ribozyme (Pley et al., 1994), and of Tetrahymena (Cate et al., 1996a, 1996b) have been shown by their crystal structure. Currently little is known of tertiary interactions, but studies on tRNA indicate these are weaker than secondary structure interactions (Riesner and Romer, 1973; Crothers and Cole, 1978; Jaeger et al., 1989b). It is very difficult to crystallize and/or get nuclear magnetic resonance spectrum data for large RNA molecules. Therefore, a logical place to start in determining the 3D structure of RNA is computer prediction of the secondary structure. The sequence (primary structure) of an RNA molecule is relatively easy to produce. Because experimental methods for determining RNA secondary and tertiary structure (when the primary sequence folds back on itself and forms base pairs) have not kept pace with the rapid discovery of RNA molecules and their function, use of and methods for computer prediction of secondary and tertiary structures have increasingly been developed.

Keywords:   Annealing mutation, Bioinformatics, Capsid, Enterovirus, GenBank, Http, MIMD machine, Network file system, Phosphodiester linkages, RasMol

Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .