DocumentCode :
2412659
Title :
Accurate prediction of ATP-binding residues using sequence and sequence-derived structural descriptors
Author :
Chen, Ke ; Mizianty, Marcin J ; Kurgan, Lukasz
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
fYear :
2010
fDate :
18-21 Dec. 2010
Firstpage :
43
Lastpage :
48
Abstract :
ATP is a ubiquitous nucleotide that provides energy for cellular activities, catalyzes chemical reactions, and is involved in cellular signaling. The knowledge of the ATP-protein interactions helps with annotation of protein functions and finds applications in drug design. We propose a high-throughput machine learning-based predictor, ATPsite, which identifies ATP-binding residues from protein sequences. Statistical tests show that ATPsite significantly outperforms existing ATPint predictor and other solutions which utilize sequence alignment and residue conservation scoring. The improvements stem from the usage of novel custom-designed input features that are based on the sequence, evolutionary profiles, and the sequence-predicted structural descriptors including secondary structure, solvent accessibility, and dihedral angles. A simple consensus of the ATPsite with the sequence-alignment based predictor is shown to give further improvements.
Keywords :
DNA; bioinformatics; cellular biophysics; learning (artificial intelligence); molecular biophysics; molecular configurations; proteins; ATP-binding residues; ATP-protein interactions; ATPint; ATPsite; cellular signaling; evolutionary profiles; machine learning; nucleotide; sequence-predicted structural descriptors; Accuracy; Kernel; Protein engineering; Proteins; Solvents; Support vector machines; Training; ATP binding; binding residues; protein-ATP interaction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2010 IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-8306-8
Electronic_ISBN :
978-1-4244-8307-5
Type :
conf
DOI :
10.1109/BIBM.2010.5706533
Filename :
5706533
Link To Document :
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