DocumentCode :
2527494
Title :
Wavelet Transform Based Protein Decoy Discrimination
Author :
Chen, Minxin ; Liu, Bingchuan ; Yan, Wenying ; Shen, Bairong
Author_Institution :
Center for Syst. Biol., Soochow Univ., Suzhou, China
fYear :
2009
fDate :
11-13 June 2009
Firstpage :
1
Lastpage :
4
Abstract :
A decoy discrimination method using wavelet analysis is presented in this paper. Through discrete wavelet decomposition and reconstruction, low frequencies of physicochemical properties from amino acid sequences and solvent accessibility area of residues from the protein three dimensional conformations are extracted and compared to find the profile similarity between the protein sequence and its three dimensional conformation. With the assumption that the protein native state conformation should have more profile similarity to its sequence than any other decoys, a scoring function evaluating the similarity is developed. This method was trained and tested by the first_decoys set in rosetta decoy set. The test results show that 73% protein native structure has the top 5 largest score. Considering the simplicity of our method, wavelet analysis is a promising way to deal with the decoy discrimination problem.
Keywords :
biochemistry; biology computing; discrete wavelet transforms; molecular biophysics; molecular configurations; proteins; sequences; signal reconstruction; amino acid sequences; discrete wavelet decomposition; discrete wavelet reconstruction; physicochemical properties; protein decoy discrimination method; protein native state conformation; protein native structure; rosetta decoy set; scoring function; solvent accessibility; three-dimensional conformation; wavelet transform; Amino acids; Discrete wavelet transforms; Potential energy; Protein engineering; Sequences; Signal processing; Solvents; Testing; Wavelet analysis; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
Type :
conf
DOI :
10.1109/ICBBE.2009.5163759
Filename :
5163759
Link To Document :
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