Prediction of Metal Ion-Binding Sites in Proteins Using the Fragment Transformation Method

被引:76
作者
Lu, Chih-Hao [1 ]
Lin, Yu-Feng [1 ,2 ]
Lin, Jau-Ji [2 ,3 ,4 ]
Yu, Chin-Sheng [5 ,6 ]
机构
[1] China Med Univ, Grad Inst Mol Syst Biomed, Taichung, Taiwan
[2] Natl Chiao Tung Univ, Inst Bioinformat & Syst Biol, Hsinchu, Taiwan
[3] Acad Sinica, Bioinformat Program, Taiwan Int Grad Program, Inst Informat Sci, Taipei 115, Taiwan
[4] Natl Yang Ming Univ, Inst Biomed Informat, Taipei 112, Taiwan
[5] Feng Chia Univ, Dept Informat Engn & Comp Sci, Taichung 40724, Taiwan
[6] Feng Chia Univ, Masters Program Biomed Informat & Biomed Engn, Taichung 40724, Taiwan
关键词
CRYSTAL-STRUCTURE; ZINC-BINDING; ESCHERICHIA-COLI; NEURAL-NETWORKS; IDENTIFICATION; SEQUENCE; CLASSIFICATION; TEMPLATES; EVOLUTION; REDUCTASE;
D O I
10.1371/journal.pone.0039252
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The structure of a protein determines its function and its interactions with other factors. Regions of proteins that interact with ligands, substrates, and/or other proteins, tend to be conserved both in sequence and structure, and the residues involved are usually in close spatial proximity. More than 70,000 protein structures are currently found in the Protein Data Bank, and approximately one-third contain metal ions essential for function. Identifying and characterizing metal ion-binding sites experimentally is time-consuming and costly. Many computational methods have been developed to identify metal ion-binding sites, and most use only sequence information. For the work reported herein, we developed a method that uses sequence and structural information to predict the residues in metal ion-binding sites. Six types of metal ion-binding templates-those involving Ca2+, Cu2+, Fe3+, Mg2+, Mn2+, and Zn2+-were constructed using the residues within 3.5 angstrom of the center of the metal ion. Using the fragment transformation method, we then compared known metal ion-binding sites with the templates to assess the accuracy of our method. Our method achieved an overall 94.6 % accuracy with a true positive rate of 60.5 % at a 5 % false positive rate and therefore constitutes a significant improvement in metal-binding site prediction.
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页数:12
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