DocumentCode
510103
Title
Peptide QSARs Study by a Novel Structure Representation Strategy
Author
You, Wei ; Ye, Yumei ; Chen, Yu ; Tian, Hongman ; Yang, Honglu ; Zhong, Yunlu
Author_Institution
Dept. of Mech. & Electr. Eng., North China Inst. of Sci. & Technol., Beijing, China
Volume
1
fYear
2009
fDate
7-8 Nov. 2009
Firstpage
231
Lastpage
234
Abstract
The authors proposed a novel structure representation strategy __ ¿Interaction-Distance¿ theory to study the quantitative structure-activity relationships (QSARs) of peptide. The ¿Interaction-Distance¿ theory stated that: I. In a peptide chain, there exists interaction between any two amino acids; II. The value of interaction lies on not only the types the two amino acids, but also the distance between them; III. The structure of the peptide may be represented by TIV (total interaction value) value__ the sum of all of the interaction values in peptide. The merit of the strategy is that the structures of all peptides comprising of different numbers of amino acids may be represented by the TIV score. The strategy is helpful of studying the peptides QSARs conveniently. In the end, QSARs of several peptides were studied by the strategy.
Keywords
bioinformatics; biological techniques; molecular biophysics; molecular configurations; neural nets; organic compounds; TIV score; amino acid interaction; interaction distance theory; peptide QSAR study; peptide chain; peptide structure; quantitative structure-activity relationship; structure representation strategy; total interaction value; Amino acids; Artificial intelligence; Artificial neural networks; Biological system modeling; Biological systems; Computational intelligence; Drugs; Equations; Peptides; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-3835-8
Electronic_ISBN
978-0-7695-3816-7
Type
conf
DOI
10.1109/AICI.2009.440
Filename
5376106
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