A novel method for quantitatively predicting non-covalent interactions from protein and nucleic acid sequence

被引:6
|
作者
Wu, Jiansheng [2 ]
Hu, Dong [2 ]
Xu, Xin [2 ]
Ding, Yan [1 ]
Yan, Shancheng [2 ]
Sun, Xiao [1 ]
机构
[1] Southeast Univ, State Key Lab Bioelect, Sch Biol Sci & Med Engn, Nanjing 210096, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Sch Geog & Biol Informat, Nanjing 210046, Peoples R China
基金
中国国家自然科学基金;
关键词
Non-covalent interactions; Support vector machine regression models; Conjoint triad; H-VDW; RANDOM FOREST MODEL; HYDROGEN-BONDS; COMPLEXES; FEATURES; PROGRAM;
D O I
10.1016/j.jmgm.2011.08.001
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Biochemical interactions between proteins and biological macromolecules are dominated by noncovalent interactions. A novel method is presented for quantitatively predicting the number of two most dominant non-covalent interactions, i.e., hydrogen bonds and van der Waals contacts, potentially forming in a hypothetical protein-nucleic acid complex from sequences using support vector machine regression models in conjunction with a hybrid feature. The hybrid feature consists of the sequence-length fraction information, conjoint triad for protein sequences and the gapped dinucleotide composition. The SVR-based models achieved excellent performance. The polarity of amino acids was also found to play a vital role in the formation of hydrogen bonds and van der Waals contacts. We have constructed a web server H-VDW (http://www.cbi.seu.edu.cn/H-VDW/H-VDW.htm) for public access to the SVR models. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:28 / 34
页数:7
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