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Sequence identification, structure prediction and validation of tannase from Aspergillusniger N5-5 |
Shuai Zhanga,b, Feng-Chao Cuic, Yong Caoa, Yun-Qi Lic |
a College of Food Science, South China Agricultural University, Guangzhou 510642, China;
b College of Chemistry and Chemical Engineering, Zhaoqing University, Zhaoqing 526061, China;
c Key Laboratory of Synthetic Rubber, Changchun Institute of Applied Chemistry Chinese Academy of Sciences, Changchun 130022, China |
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Abstract Tannases produced by filamentous fungi are in a family of important hydrolases of gallotannins and have broad industry applications. But until now, the 3-D structures of fungi tannases have not been reported. The protein sequence deduced from the cDNA sequence obtained using RT-PCR amplification was identified as tannase through sequence alignment and phylogenetic analysis. Structure models based on the tannase sequence were collected using I-TASSER, and the model with the best match to the surface charge density-pH titration profile was selected as the final structure for tannase from Aspergillusniger N5-5. This work provides an effective method for protein structure research. The structure constructed in this work should be very important to understand the enzyme bioactivities and further developments of fungi tannases.
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Received: 15 December 2015
Published: 23 April 2016
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Fund:The authors are grateful to the National Natural Science Foundation of China (No. 21374117) and the 100 Talents Program of Chinese Academy of Sciences for financial support. |
Corresponding Authors:
Yong Cao
E-mail: caoyong2181@scau.edu.cn
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[1] |
C.N. Aguilar, R. Rodríguez, G. Gutié rrez-Sá nchez, et al., Microbial tannases: advances and perspectives, Appl. Microbiol. Biotechnol. 76 (2007) 47-59.
|
[2] |
M. Srivastava, S.K. Gupta, P.C. Abhilash, N. Singh, Structure prediction and binding sites analysis of curcin protein of Jatropha curcas using computational approaches, J. Mol. Model. 18 (2012) 2971-2979.
|
[3] |
Y. Zhang, Progress and challenges in protein structure prediction, Curr. Opin. Struct. Biol. 18 (2008) 342-348.
|
[4] |
J.Y. Yang, R.X. Yan, A. Roy, et al., The I-TASSER suite: protein structure and function prediction, Nat. Methods 12 (2015) 7-8.
|
[5] |
Y. Zhang, Interplay of I-TASSER and QUARK for template-based and ab initio protein structure prediction in CASP10, Proteins 82 (2014) 175-187.
|
[6] |
K. Tamura, G. Stecher, D. Peterson, A. Filipski, S. Kumar, MEGA6: molecular evolutionary genetics analysis version 6.0, Mol. Biol. Evol. 30 (2013) 2725-2729.
|
[7] |
M. Wayengera, Searching for new clues about the molecular cause of endomyocardial fibrosis by way of in silico proteomics and analytical chemistry, PLoS ONE 4 (2009) e7420.
|
[8] |
Y. Zhang, I-TASSER: fully automated protein structure prediction in CASP8, Proteins 77 (2009) 100-113.
|
[9] |
H.J. Butt, K. Graf, M. Kappl, Physics and Chemistry of Interfaces, Wiley-VCH, Weinheim, 2004p. 64.
|
[10] |
P.B. Lorenz, Surface conductance and electrokinetic properties of kaolinite beds, Clays Clay Miner. 17 (1969) 223-231.
|
[11] |
Y.Q. Li, L.J. An, Q.R. Huang, Replica exchange Monte Carlo simulation of human serum albumin-catechin complexes, J. Phys. Chem. B 118 (2014) 10362-10372.
|
[12] |
Y.Q. Li, Q. Zhao, Q.R. Huang, Understanding complex coacervation in serum albumin and pectin mixtures using a combination of the Boltzmann equation and Monte Carlo simulation, Carbohydr. Polym. 101 (2014) 544-553.
|
[13] |
N.S. Bujang, N.A. Harrison, N.Y. Su, A phylogenetic study of endo-beta-1, 4-glucanase in higher termites, Insect. Soc. 61 (2014) 29-40.
|
[14] |
Y. Zhang, J. Skolnick, TM-align: a protein structure alignment algorithm based on the TM-score, Nucleic Acids Res. 33 (2005) 2302-2309.
|
|
|
|