DocumentCode :
2960719
Title :
Approaches to prediction of protein structure
Author :
Ahmed, Walaa Fathy ; Gomaa, Walid
Author_Institution :
Collage of Comput. & Inf. Technol., Arab Acad. for Sci. & Technol. & Maritime Transp., Alexandria, Egypt
fYear :
2011
fDate :
27-30 Dec. 2011
Firstpage :
284
Lastpage :
284
Abstract :
Protein structure prediction (PSP) is one of the most important and challenging problems in bioinformatics today. This is due to the fact that the biological function of the protein is determined by its structure. While there is a gap between the number of known protein sequences and the number of known structures, protein structure prediction aims at reducing this sequence-structure gap. Protein structure can be experimentally determined using either X-ray crystallography or Nuclear Magnetic Resonance (NMR). However, these empirical techniques are very time consuming, so computational models and the associated algorithms have been developed for protein structure prediction. Such computational models fall into three categories: the homology approach, threading, and the ab initio approach. In this paper we give a general introductory background to the area and a literature survey about the ab initio approach in particular. This approach depends on the chemical and physical properties of the constituent amino acids. Not all ab initio algorithms have the same performance, so we represent the general success keys for any such algorithm.
Keywords :
X-ray crystallography; bioinformatics; organic compounds; proteins; X-ray crystallography; bioinformatics; constituent amino acids; nuclear magnetic resonance; protein sequences; protein structure prediction; Amino acids; Computational modeling; Educational institutions; Heuristic algorithms; Prediction algorithms; Proteins;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Systems and Applications (AICCSA), 2011 9th IEEE/ACS International Conference on
Conference_Location :
Sharm El-Sheikh
ISSN :
2161-5322
Print_ISBN :
978-1-4577-0475-8
Electronic_ISBN :
2161-5322
Type :
conf
DOI :
10.1109/AICCSA.2011.6126616
Filename :
6126616
Link To Document :
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