A two-step discriminated method to identify thermophilic proteins

被引：61

作者：

Tang, Hua ^{[1
]}

Cao, Ren-Zhi ^{[2
]}

Wang, Wen ^{[2
]}

Liu, Tie-Shan ^{[3
]}

Wang, Li-Ming ^{[3
]}

He, Chun-Mei ^{[3
]}

机构：

[1] Southwest Med Univ, Dept Pathophysiol, Luzhou 646000, Peoples R China

[2] Pacific Lutheran Univ, Dept Comp Sci, Tacoma, WA 98447 USA

[3] Shandong Acad Agr Sci, Maize Inst, Jinan 250100, Peoples R China

来源：

INTERNATIONAL JOURNAL OF BIOMATHEMATICS | 2017年 / 10卷 / 04期

关键词：

Thermostability; thermophilic protein; fragment; support vector machine; AMINO-ACID-COMPOSITION; SUPPORT VECTOR MACHINE; MESOPHILIC PROTEINS; FEATURE-SELECTION; PREDICTION; THERMOSTABILITY; QUALITY; MODEL;

D O I：

10.1142/S1793524517500504

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Improving thermostability of an enzyme can accelerate the relevant chemical reaction. Thus, the analysis and prediction of thermophilic proteins are conducive to protein engineering and enzyme design. In this study, a novel method based on two-step discrimination was proposed to distinguish between thermophilic and non-thermophilic proteins. The model was rigorously benchmarked on an objective dataset including 915 thermophilic proteins and 793 non-thermophilic proteins. Results showed that the overall accuracy of our method is 94.44% in 5-fold cross-validation, which is higher than those of other published methods. We believe that the two-step discriminated strategy will become a promising method in the relevant field of protein bioinformatics.

引用

页数：8

共 31 条

[1] Positive and negative design in stability and thermal adaptation of natural proteins [J].

Berezovsky, Igor N. ;

Zeldovich, Konstantin B. ;

Shakhnovich, Eugene I. .

PLOS COMPUTATIONAL BIOLOGY, 2007, 3 (03) :498-507

[2] THERMUS AQUATICUS GEN N AND SP N A NONSPORULATING EXTREME THERMOPHILE [J].

BROCK, TD ;

FREEZE, H .

JOURNAL OF BACTERIOLOGY, 1969, 98 (01) :289-&

[3] Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11 [J].

Cao, Renzhi ;

Bhattacharya, Debswapna ;

Adhikari, Badri ;

Li, Jilong ;

Cheng, Jianlin .

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2016, 84 :247-259

[4] Integrated protein function prediction by mining function associations, sequences, and protein-protein and gene-gene interaction networks [J].

Cao, Renzhi ;

Cheng, Jianlin .

METHODS, 2016, 93 :84-91

[5] Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation [J].

Cao, Renzhi ;

Cheng, Jianlin .

BMC GENOMICS, 2015, 16

[6] Large-scale model quality assessment for improving protein tertiary structure prediction [J].

Cao, Renzhi ;

Bhattacharya, Debswapna ;

Adhikari, Badri ;

Li, Jilong ;

Cheng, Jianlin .

BIOINFORMATICS, 2015, 31 (12) :116-123

[7] SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines [J].

Cao, Renzhi ;

Wang, Zheng ;

Wang, Yiheng ;

Cheng, Jianlin .

BMC BIOINFORMATICS, 2014, 15

[8] Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment [J].

Cao, Renzhi ;

Wang, Zheng ;

Cheng, Jianlin .

BMC STRUCTURAL BIOLOGY, 2014, 14

[9] Prediction of ketoacyl synthase family using reduced amino acid alphabets [J].

Chen, Wei ;

Feng, Pengmian ;

Lin, Hao .

JOURNAL OF INDUSTRIAL MICROBIOLOGY & BIOTECHNOLOGY, 2012, 39 (04) :579-584

[10] Identification of voltage-gated potassium channel subfamilies from sequence information using support vector machine [J].

Chen, Wei ;

Lin, Hao .

COMPUTERS IN BIOLOGY AND MEDICINE, 2012, 42 (04) :504-507

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