期刊论文详细信息
BMC Research Notes
Molecular modeling and molecular dynamics simulations based structural analysis of the SG2NA protein variants
Shyamal K Goswami1  Abhinav Grover2  Chetna Tyagi2  Sangeeta Soni1 
[1] School of Life Sciences, Jawaharlal Nehru University, New Delhi 110067, India;School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India
关键词: Striatin;    Disorder prediction;    Molecular dynamics simulations;    Molecular modeling;    SG2NA;   
Others  :  1131927
DOI  :  10.1186/1756-0500-7-446
 received in 2014-03-11, accepted in 2014-07-01,  发布年份 2014
PDF
【 摘 要 】

Background

SG2NA is a member of the striatin sub-family of WD-40 repeat proteins. Striatin family members have been associated with diverse physiological functions. SG2NA has also been shown to have roles in cell cycle progression, signal transduction etc. They have been known to interact with a number of proteins including Caveolin and Calmodulin and also propagate the formation of a multimeric protein unit called striatin-interacting phosphatase and kinase. As a pre-requisite for such interaction ability, these proteins are known to be unstable and primarily disordered in their arrangement. Earlier we had identified that it has multiple isoforms (namely 35, 78, 87 kDa based on its molecular weight) which are generated by alternative splicing. However, detailed structural information of SG2NA is still eluding the researchers.

Results

This study was aimed towards three-dimensional molecular modeling and characterization of SG2NA protein and its isoforms. One structure out of five was selected for each variant having the least value for C score. Out of these, m35 kDa with a C score value of −3.21was the most poorly determined structure in comparison to m78 kDa and m87 kDa variants with C scores of −1.16 and −1.97 respectively. Further evaluation resulted in about 61.6% residues of m35 kDa, 76.6% residues of m78 kDa and 72.1% residues of m87 kDa falling in the favorable regions of Ramchandran Plot. Molecular dynamics simulations were also carried out to obtain biologically relevant structural models and compared with previous atomic coordinates. N-terminal region of all variants was found to be highly disordered.

Conclusion

This study provides first-hand detailed information to understand the structural conformation of SG2NA protein variants (m35 kDa, m78 kDa and m87 kDa). The WD-40 repeat domain was found to constitute antiparallel strands of β-sheets arranged circularly. This study elucidates the crucial structural features of SG2NA proteins which are involved in various protein-protein interactions and also reveals the extent of disorder present in the SG2NA structure crucial for excessive interaction and multimeric protein complexes. The study also potentiates the role of computational approaches for preliminary examination of unknown proteins in the absence of experimental information.

【 授权许可】

   
2014 Soni et al.; licensee BioMed Central Ltd.

【 预 览 】
附件列表
Files Size Format View
20150303120320595.pdf 3199KB PDF download
Figure 7. 114KB Image download
Figure 6. 270KB Image download
Figure 5. 297KB Image download
Figure 4. 303KB Image download
Figure 3. 67KB Image download
Figure 2. 237KB Image download
Figure 1. 252KB Image download
【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

【 参考文献 】
  • [1]Muro Y, Chan EK, Landberg G, Tan EM: A cell-cycle nuclear autoantigen containing WD-40 motifs expressed mainly in S and G2 phase cells. Biochem Biophys Res Commun 1995, 207(3):1029-1037.
  • [2]Castets F, Rakitina T, Gaillard S, Moqrich A, Mattei MG, Monneron A: Zinedin, SG2NA, and striatin are calmodulin-binding, WD repeat proteins principally expressed in the brain. J Biol Chem 2000, 275(26):19970-19977.
  • [3]Benoist M, Gaillard S, Castets F: The striatin family: a new signaling platform in dendritic spines. J Physiol Paris 2006, 99(2–3):146-153.
  • [4]Sanghamitra M, Talukder I, Singarapu N, Sindhu KV, Kateriya S, Goswami SK: WD-40 repeat protein SG2NA has multiple splice variants with tissue restricted and growth responsive properties. Gene 2008, 420(1):48-56.
  • [5]Gordon J, Hwang J, Carrier KJ, Jones CA, Kern QL, Moreno CS, Karas RH, Pallas DC: Protein phosphatase 2a (PP2A) binds within the oligomerization domain of striatin and regulates the phosphorylation and activation of the mammalian Ste20-Like kinase Mst3. BMC Biochem 2011, 12:54. BioMed Central Full Text
  • [6]Gaillard S, Bartoli M, Castets F, Monneron A: Striatin, a calmodulin-dependent scaffolding protein, directly binds caveolin-1. FEBS Lett 2001, 508(1):49-52.
  • [7]Breitman M, Zilberberg A, Caspi M, Rosin-Arbesfeld R: The armadillo repeat domain of the APC tumor suppressor protein interacts with Striatin family members. Biochim Biophys Acta 2008, 1783(10):1792-1802.
  • [8]Bernelot Moens SJ, Schnitzler GR, Nickerson M, Guo H, Ueda K, Lu Q, Aronovitz MJ, Nickerson H, Baur WE, Hansen U, Iyer LK, Karas RH: Rapid estrogen receptor signaling is essential for the protective effects of estrogen against vascular injury. Circulation 2012, 126(16):1993-2004.
  • [9]Hyodo T, Ito S, Hasegawa H, Asano E, Maeda M, Urano T, Takahashi M, Hamaguchi M, Senga T: Misshapen-like kinase 1 (MINK1) is a novel component of striatin-interacting phosphatase and kinase (STRIPAK) and is required for the completion of cytokinesis. J Biol Chem 2012, 287(30):25019-25029.
  • [10]Chen YK, Chen CY, Hu HT, Hsueh YP: CTTNBP2, but not CTTNBP2NL, regulates dendritic spinogenesis and synaptic distribution of the striatin-PP2A complex. Mol Biol Cell 2012, 23(22):4383-4392.
  • [11]Kean MJ, Ceccarelli DF, Goudreault M, Sanches M, Tate S, Larsen B, Gibson LC, Derry WB, Scott IC, Pelletier L, Baillie GS, Sicheri F, Gingras AC: Structure-function analysis of core STRIPAK Proteins: a signaling complex implicated in Golgi polarization. J Biol Chem 2011, 286(28):25065-25075.
  • [12]Bailly YJ, Castets F: Phocein: A potential actor in vesicular trafficking at Purkinje cell dendritic spines. Cerebellum 2007, 6(4):1-9.
  • [13]Castets F, Bartoli M, Barnier JV, Baillat G, Salin P, Moqrich A, Bourgeois JP, Denizot F, Rougon G, Calothy G, Monneron A: A novel calmodulin-binding protein, belonging to the WD-repeat family, is localized in dendrites of a subset of CNS neurons. J Cell Biol 1996, 134(4):1051-1062.
  • [14]Chen HW, Marinissen MJ, Oh SW, Chen X, Melnick M, Perrimon N, Gutkind JS, Hou SX: CKA, a novel multidomain protein, regulates the JUN N-terminal kinase signal transduction pathway in Drosophila. Mol Cell Biol 2002, 22(6):1792-1803.
  • [15]Church DM, Goodstadt L, Hillier LW, Zody MC, Goldstein S, She X, Bult CJ, Agarwala R, Cherry JL, DiCuccio M, Hlavina W, Kapustin Y, Meric P, Maglott D, Birtle Z, Marques AC, Graves T, Zhou S, Teague B, Potamousis K, Churas C, Place M, Herschleb J, Runnheim R, Forrest D, Amos-Landgraf J, Schwartz DC, Cheng Z, Lindblad-Toh K, Eichler EE, et al.: Lineage-specific biology revealed by a finished genome assembly of the mouse. PLoS Biol 2009, 7(5):e1000112.
  • [16]BLAST, NCBI http://blast.ncbi.nlm.nih.gov/ webcite
  • [17]Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A: The Proteomics Protocols Handbook. Edited by Walker JM. Totowa, NJ: The Proteomics Protocols Handbook, Humana Press; 2005:571-607.
  • [18]Guruprasad K, Reddy BV, 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):155-161.
  • [19]Ikai A: Thermostability and aliphatic index of globular proteins. J Biochem 1980, 88(6):1895-1898.
  • [20]Jeong JH, Kim SW, Yoon SM, Park JK, Lee JS: Characterization of the conserved region of the mxaF gene that encodes the large subunit of methanol dehydrogenase from a marine methylotrophic bacterium. Mol Cells 2002, 13(3):369-376.
  • [21]Pelton JT, McLean LR: Spectroscopic methods for analysis of protein secondary structure. Anal Biochem 2000, 277(2):167-176.
  • [22]Kyte J, Doolittle RF: A simple method for displaying the hydropathic character of a protein. J Mol Biol 1982, 157(1):105-132.
  • [23]McGuffin LJ, Bryson K, Jones DT: The PSIPRED protein structure prediction server. Bioinform Appl Note 1999, 16(4):404-405.
  • [24]Roy A, Kucukural A, Zhang Y: I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc 2010, 5(4):725-738.
  • [25]Zhang Y: I-TASSER server for protein 3D structure prediction. BMC Bioinformatics 2008, 9:40. BioMed Central Full Text
  • [26]Laurie ATR, Jackson RM: Q-SiteFinder: an energy-based method for the prediction of protein–ligand binding sites. Bioinformatics 2005, 21(9):1908-1916.
  • [27]Vaguine AA, Richelle J, Wodak SJ: SFCHECK: a unified set of procedures for evaluating the quality of macromolecular structure-factor data and their agreement with the atomic model. Acta Crystallogr D Biol Crystallogr 1999, 55(Pt 1):191-205.
  • [28]Case DA, Darden T, Cheatham TE, Simmerling CL, Wang J, Duke RE, Luo R, Crowley MWR, Zhang W, Merz KM, Wang B, Hayik S, Roitberg A, Seabra G, Kolossvary I, Wong KF, Paesani F, Vanicek J, Wu X, Brozell SR, Steinbrecher T, Gohlke H, Yang L, Tan C, Mongan J, Hornak V, Cui G, Mathews DH, Seetin MG, et al.: AMBER 10. San Francisco: University of California; 2008.
  • [29]MacKerell AD Jr, Banavali N, Foloppe N: Development and current status of the CHARMM force field for nucleic acids. Biopolymers 2000, 56(4):257-265.
  • [30]Xu D, Zhang Y: Ab initio protein structure assembly using continuous structure fragments and optimized knowledge-based force field. Proteins 2012, 80(7):1715-1735.
  • [31]Wu S, Zhang Y: MUSTER: Improving protein sequence profile-profile alignments by using multiple sources of structure information. Proteins 2008, 72(2):547-556.
  • [32]Dosztányi Z, Csizmok V, Tompa P, Simon I: IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics 2005, 21(16):3433-3434.
  • [33]Wedemeyer WJ, Welker E, Narayan M, Scheraga HA: Disulfide bonds and protein folding. Biochemistry 2000, 39(23):7032.
  • [34]Jones DT: Protein secondary structure prediction based on position-specific scoring matrices. J Mol Biol 1999, 292(2):195-202.
  文献评价指标  
  下载次数:49次 浏览次数:26次