DocumentCode :
2074456
Title :
Protein structure prediction based on multi-level description
Author :
Onizuka, Kentaro ; Tsuda, Hiroshi ; Ishikawa, Masato ; Aiba, Akira ; Asai, Kiyoshi ; Ito, Katunobu
Author_Institution :
Inst. for New Generation Comput. Technol., Tokyo, Japan
Volume :
5
fYear :
1994
fDate :
4-7 Jan. 1994
Firstpage :
355
Lastpage :
364
Abstract :
Proposes novel prediction schemes for protein 3D structure prediction that include both local and global factors of protein structure formation. The authors have developed a powerful description scheme for protein conformation, MLD (Multi-Level Description) in order to model the protein structure formation. In this scheme, the description is reconstructable into the three-dimensional conformation with a tolerable error. The MLD scheme facilitates the modeling of 1) the relation between the local conformation and the primary structure at that region at various scales (i.e., primary constraints), and 2) the geometric constraints between the neighboring local conformations. Hence, in these prediction schemes, the problem of protein 3D structure prediction is formulated as a combinatorial optimization problem; the 3D conformation of a protein is predicted as the optimal MLD that satisfies most of the constraints. The authors implemented several schemes to solve this problem. They prove that the degree of prediction accuracy is much improved by introducing the geometric constraints.<>
Keywords :
biology computing; molecular biophysics; molecular configurations; physics computing; proteins; MLD; combinatorial optimization; geometric constraints; multi-level description; prediction accuracy; prediction schemes; protein 3D structure prediction; protein conformation; protein structure formation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences, 1994. Proceedings of the Twenty-Seventh Hawaii International Conference on
Conference_Location :
Wailea, HI, USA
Print_ISBN :
0-8186-5090-7
Type :
conf
DOI :
10.1109/HICSS.1994.323561
Filename :
323561
Link To Document :
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