A similarity search algorithm to predict protein structures

An, Jiyuan and Chen, Yi-Ping Phoebe 2006, A similarity search algorithm to predict protein structures, Lecture notes in computer science, vol. 4252, pp. 1305-1312.

Attached Files
Name Description MIMEType Size Downloads

Title A similarity search algorithm to predict protein structures
Author(s) An, Jiyuan
Chen, Yi-Ping Phoebe
Journal name Lecture notes in computer science
Volume number 4252
Start page 1305
End page 1312
Publisher Springer-Verlag
Place of publication Berlin, Germany
Publication date 2006
ISSN 0302-9743
1611-3349
Summary Accurate prediction of protein structures is very important for many applications such as drug discovery and biotechnology. Building side chains is an essential to get any reliable prediction of the protein structure for any given a protein main chain conformation. Most of the methods that predict side chain conformations use statistically generated data from known protein structures. It is a computationally intractable problem to search suitable side chains from all possible rotamers simultaneously using information of known protein structures. Reducing the number of possibility is a main issue to predict side chain conformation. This paper proposes an enumeration based similarity search algorithm to predict side chain conformations. By introducing “beam search” technique, a significant number of unrelated side chain rotamers can easily be eliminated. As a result, we can search for suitable residue side chains from all possible side chain conformations.
Notes Book: "Knowledge-Based Intelligent Information and Engineering Systems"
Language eng
Field of Research 080610 Information Systems Organisation
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2006, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30003692

Document type: Journal Article
Collection: School of Engineering and Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 345 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Mon, 07 Jul 2008, 09:00:24 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.