Browse > Article
http://dx.doi.org/10.1186/s40781-015-0077-x

In silico characterisation, homology modelling and structure-based functional annotation of blunt snout bream (Megalobrama amblycephala) Hsp70 and Hsc70 proteins  

Tran, Ngoc Tuan (College of Fisheries, Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education/Key Lab of Freshwater Animal Breeding, Ministry of Agriculture, Huazhong Agricultural University)
Jakovlic, Ivan (College of Fisheries, Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education/Key Lab of Freshwater Animal Breeding, Ministry of Agriculture, Huazhong Agricultural University)
Wang, Wei-Min (College of Fisheries, Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education/Key Lab of Freshwater Animal Breeding, Ministry of Agriculture, Huazhong Agricultural University)
Publication Information
Journal of Animal Science and Technology / v.57, no.12, 2015 , pp. 44.1-44.9 More about this Journal
Abstract
Background: Heat shock proteins play an important role in protection from stress stimuli and metabolic insults in almost all organisms. Methods: In this study, computational tools were used to deeply analyse the physicochemical characteristics and, using homology modelling, reliably predict the tertiary structure of the blunt snout bream (Ma-) Hsp70 and Hsc70 proteins. Derived three-dimensional models were then used to predict the function of the proteins. Results: Previously published predictions regarding the protein length, molecular weight, theoretical isoelectric point and total number of positive and negative residues were corroborated. Among the new findings are: the extinction coefficient (33725/33350 and 35090/34840 - Ma-Hsp70/ Ma-Hsc70, respectively), instability index (33.68/35.56 - both stable), aliphatic index (83.44/80.23 - both very stable), half-life estimates (both relatively stable), grand average of hydropathicity (-0.431/-0.473 - both hydrophilic) and amino acid composition (alanine-lysine-glycine/glycine-lysine-aspartic acid were the most abundant, no disulphide bonds, the N-terminal of both proteins was methionine). Homology modelling was performed by SWISS-MODEL program and the proposed model was evaluated as highly reliable based on PROCHECK's Ramachandran plot, ERRAT, PROVE, Verify 3D, ProQ and ProSA analyses. Conclusions: The research revealed a high structural similarity to Hsp70 and Hsc70 proteins from several taxonomically distant animal species, corroborating a remarkably high level of evolutionary conservation among the members of this protein family. Functional annotation based on structural similarity provides a reliable additional indirect evidence for a high level of functional conservation of these two genes/proteins in blunt snout bream, but it is not sensitive enough to functionally distinguish the two isoforms.
Keywords
Hsp70; Hsc70; Physicochemical characteristics; Homology modelling; Structural similarity; Functional annotation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Lindquist S, Craig EA. The Heat-Shock Proteins. Annu Rev Genet. 1988;22(1):631-77.   DOI
2 Mestril R, Dillmann WH. Heat shock proteins and protection against myocardial ischemia. J Mol Cell Cardiol. 1995;27(1):45-52.   DOI
3 Basu N, Todgham AE, Ackerman PA, Bibeau MR, Nakano K, Schulte PM, et al. Heat shock protein genes and their functional significance in fish. Gene. 2002;295(2):173-83.   DOI
4 Yamashita M, Yabu T, Ojima N. Stress Protein HSP70 in Fish. Aqua-BioScience Monographs. 2010;3(4):111-41.   DOI
5 Basu N, Nakano T, Grau EG, Iwama GK. The Effects of Cortisol on Heat Shock Protein 70 Levels in Two Fish Species. Gen Comp Endocrinol. 2001;124(1):97-105.   DOI
6 Boutet I, Tanguy A, Rousseau S, Auffret M, Moraga D. Molecular identification and expression of heat shock cognate 70 (hsc70) and heat shock protein 70 (hsp70) genes in the Pacific oyster Crassostrea gigas. Cell Stress Chaperones. 2003;8(1):76-85.   DOI
7 Ming J, Xie J, Xu P, Liu W, Ge X, Liu B, et al. Molecular cloning and expression of two HSP70 genes in the Wuchang bream (Megalobrama amblycephala Yih). Fish Shellfish Immunology. 2010;28(3):407-18.   DOI
8 Iwama G, Thomas P, Forsyth R, Vijayan M. Heat shock protein expression in fish. Rev Fish Biol Fish. 1998;8(1):35-56.   DOI
9 Padmini E, Usha RM. Impact of seasonal variation on HSP70 expression quantitated in stressed fish hepatocytes. Comp Biochem Physiol B Biochem Mol Biol. 2008;151(3):278-85.   DOI
10 Welch W, Feramisco J. Disruption of the three cytoskeletal networks in mammalian cells does not affect transcription, translation, or protein translocation changes induced by heat shock. Mol Cell Biol. 1985;5(7):1571-81.   DOI
11 Gething M-J, Sambrook J. Protein folding in the cell. Nature. 1992;355(6355):33-45.   DOI
12 Wallin RP, Lundqvist A, More SH, Von Bonin A, Kiessling R, Ljunggren H-G. Heat-shock proteins as activators of the innate immune system. Trends Immunol. 2002;23(3):130-5.   DOI
13 Luckstadt C, Schill RO, Focken U, Kohler H-R, Becker K. Stress protein HSP70 response of Nile Tilapia Oreochromis niloticus (Linnaeus, 1758) to induced hypoxia and recovery. Verhandlungen der Gesellschaft fur Ichthyologie Band. 2004;4:137-41.
14 Daugaard M, Rohde M, Jaattela M. The heat shock protein 70 family: Highly homologous proteins with overlapping and distinct functions. FEBS Lett. 2007;581(19):3702-10.   DOI
15 Bukau B, Horwich AL. The Hsp70 and Hsp60 chaperone machines. Cell. 1998;92(3):351-66.   DOI
16 Tutar Y, Song Y, Masison DC. Primate chaperones Hsc70 (constitutive) and Hsp70 (induced) differ functionally in supporting growth and prion propagation in Saccharomyces cerevisiae. Genetics. 2006;172(2):851-61.   DOI
17 Yamashita M, Hojo M. Generation of a transgenic zebrafish model overexpressing heat shock protein HSP70. Mar Biotechnol. 2004;6:S1-7.   DOI
18 Ojima N, Yamashita M, Watabe S. Comparative expression analysis of two paralogous Hsp70s in rainbow trout cells exposed to heat stress. Biochimica et Biophysica Acta (BBA)-Gene Structure and Expression. 2005;1681(2):99-106.   DOI
19 Mu W, Wen H, Li J, He F. Cloning and expression analysis of a HSP70 gene from Korean rockfish (Sebastes schlegeli). Fish shellfish immunology. 2013;35(4):1111-21.   DOI
20 Wang P, Zeng S, Xu P, Zhou L, Zeng L, Lu X, et al. Identification and expression analysis of two HSP70 isoforms in mandarin fish Siniperca chuatsi. Fish Sci. 2014;80(4):803-17.   DOI
21 Zhou Z, Ren Z, Zeng H, Yao B. Apparent digestibility of various feedstuffs for bluntnose black bream Megalobrama amblycephala Yih. Aquac Nutr. 2008;14(2):153-65.   DOI
22 Skolnick J, Fetrow JS, Kolinski A. Structural genomics and its importance for gene function analysis. Nat Biotechnol. 2000;18(3):283-7.   DOI
23 CAFS. Fishery Statistic Data: Chinese Academy of Fishery Sciences, Beijing. 2010.
24 MAPRC. Chinese fisheries yearbook: Chinese Agricultural Press, Beijing. 2010.
25 Marti-Renom MA, Stuart AC, Fiser A, Sanchez R, Melo F, Sali A. Comparative Protein Structure Modeling of Genes and Genomes. Annu Rev Biophys Biomol Struct. 2000;29(1):291-325.   DOI
26 Teichmann SA, Murzin AG, Chothia C. Determination of protein function, evolution and interactions by structural genomics. Curr Opin Struct Biol. 2001;11(3):354-63.   DOI
27 Radivojac P, Clark WT, Oron TR, Schnoes AM, Wittkop T, Sokolov A, et al. A large-scale evaluation of computational protein function prediction. Nat Methods. 2013;10(3):221-7.   DOI
28 Gasteiger E, Hoogland C, Gattiker A, Wilkins MR, Appel RD, Bairoch A. Protein identification and analysis tools on the ExPASy server. In: The proteomics protocols handbook: Springer. 2005. p. 571-607.
29 Hirokawa T, Boon-Chieng S, Mitaku S. SOSUI: classification and secondary structure prediction system for membrane proteins. Bioinformatics. 1998;14(4):378-9.   DOI
30 Schwede T, Kopp J, Guex N, Peitsch MC. SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res. 2003;31(13):3381-5.   DOI
31 Arnold K, Bordoli L, Kopp J, Schwede T. The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics. 2006;22(2):195-201.   DOI
32 Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35 suppl 2:W407-10.   DOI
33 Fiser A. Template-based protein structure modeling. In: Fenyo D, editor. Computational Biology: Humana Press. 2004.
34 Cristobal S, Zemla A, Fischer D, Rychlewski L, Elofsson A. A study of quality measures for protein threading models. BMC bioinformatics. 2001;2(1):5.   DOI
35 Sippl MJ. Recognition of errors in three-dimensional structures of proteins. Proteins: Structure Function, and Bioinformatics. 1993;17(4):355-62.   DOI
36 Guex N, Peitsch MC. SWISS-MODEL and the Swiss-Pdb Viewer: An environment for comparative protein modeling. ELECTROPHORESIS. 1997;18(15):2714-23.   DOI
37 Zhang Y, Skolnick J. TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 2005;33(7):2302-9.   DOI
38 Zhang Y. I-TASSER server for protein 3D structure prediction. BMC bioinformatics. 2008;9(1):40.   DOI
39 Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc. 2010;5(4):725-38.   DOI
40 Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y. The I-TASSER Suite: protein structure and function prediction. Nat Methods. 2015;12(1):7-8.   DOI
41 Guruprasad K, Reddy BB, Pandit MW. Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Eng. 1990;4(2):155-61.   DOI
42 Liithy R, Bowie J, Eisenberg D. Assessment of protein models with three-dimensional profiles. Nature. 1992;356(6364):83-5.   DOI
43 Ikai A. Thermostability and aliphatic index of globular proteins. J Biochem. 1980;88(6):1895-8.
44 Hogg PJ. Disulfide bonds as switches for protein function. Trends Biochem Sci. 2003;28(4):210-4.   DOI
45 Ramachandran G, Ramakrishnan C, Sasisekhran V. Stereochemistry of polypeptide chain configuarations. J Mol Biol. 1963;7:95-9.   DOI
46 Colovos C, Yeates TO. Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci. 1993;2(9):1511-9.   DOI
47 Vorobiev S, Strokopytov B, Drubin D, Frieden C, Ono S, Condeelis J, et al. The structure of nonvertebrate actin: implications for the ATP hydrolytic mechanism. Proc Natl Acad Sci. 2003;100(10):5760-5.   DOI
48 Zhang Z, Cellitti J, Teriete P, Pellecchia M, Stec B. New crystal structures of HSC-70 ATP binding domain confirm the role of individual binding pockets and suggest a new method of inhibition. Biochimie. 2015;108:186-92.   DOI
49 Arakawa A, Handa N, Ohsawa N, Shida M, Kigawa T, Hayashi F, et al. The C-terminal BAG domain of BAG5 induces conformational changes of the Hsp70 nucleotide-binding domain for ADP-ATP exchange. Structure. 2010;18(3):309-19.   DOI