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Toolbox for Protein Structure Prediction

  • Protocol
Yeast Cytokinesis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1369))

Abstract

Protein tertiary structure prediction algorithms aim to predict, from amino acid sequence, the tertiary structure of a protein. In silico protein structure prediction methods have become extremely important, as in vitro-based structural elucidation is unable to keep pace with the current growth of sequence databases due to high-throughput next-generation sequencing, which has exacerbated the gaps in our knowledge between sequences and structures.

Here we briefly discuss protein tertiary structure prediction, the biennial competition for the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and its role in shaping the field. We also discuss, in detail, our cutting-edge web-server method IntFOLD2-TS for tertiary structure prediction. Furthermore, we provide a step-by-step guide on using the IntFOLD2-TS web server, along with some real world examples, where the IntFOLD server can and has been used to improve protein tertiary structure prediction and aid in functional elucidation.

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References

  1. Roche DB, Buenavista MT, McGuffin LJ (2014) Assessing the quality of modelled 3D protein structures using the ModFOLD server. Methods Mol Biol 1137:83–103. doi:10.1007/978-1-4939-0366-5_7

    Article  CAS  PubMed  Google Scholar 

  2. Roche DB, Buenavista MT, McGuffin LJ (2012) Predicting protein structures and structural annotation of proteomes. In: Roberts GCK (ed) Encyclopedia of biophysics, vol 1. Springer, Berlin

    Google Scholar 

  3. Roche DB, Buenavista MT, McGuffin LJ (2012) FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions. PLoS One 7(5):e38219. doi:10.1371/journal.pone.0038219

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Kajan L, Hopf TA, Kalas M, Marks DS, Rost B (2014) FreeContact: fast and free software for protein contact prediction from residue co-evolution. BMC Bioinformatics 15:85. doi:10.1186/1471-2105-15-85

    Article  PubMed Central  PubMed  Google Scholar 

  5. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The Protein Data Bank. Nucleic Acids Res 28(1):235–242, doi:gkd090 [pii]

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  6. McGuffin LJ (2008) Protein fold recognition and threading. Computational structural biology. World Scientific, London, pp 37–60

    Book  Google Scholar 

  7. Lee J, Wu S, Zhang Y (2009) Ab initio protein structure prediction. From protein structure to function with bioinformatics. Springer, London, pp 1–26

    Google Scholar 

  8. McGuffin LJ, Roche DB (2011) Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method. Proteins 79(Suppl 10):137–146. doi:10.1002/prot.23120

    Article  CAS  PubMed  Google Scholar 

  9. Moult J, Fidelis K, Kryshtafovych A, Rost B, Tramontano A (2009) Critical assessment of methods of protein structure prediction—round VIII. Proteins 77(Suppl 9):1–4. doi:10.1002/prot.22589

    Article  CAS  PubMed  Google Scholar 

  10. Moult J, Pedersen JT, Judson R, Fidelis K (1995) A large-scale experiment to assess protein structure prediction methods. Proteins 23(3):ii–v. doi:10.1002/prot.340230303

    Article  CAS  PubMed  Google Scholar 

  11. Kryshtafovych A, Fidelis K, Moult J (2014) CASP10 results compared to those of previous CASP experiments. Proteins 82(Suppl 2):164–174. doi:10.1002/prot.24448

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  12. Kryshtafovych A, Krysko O, Daniluk P, Dmytriv Z, Fidelis K (2009) Protein structure prediction center in CASP8. Proteins 77(Suppl 9):5–9. doi:10.1002/prot.22517

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  13. Buenavista MT, Roche DB, McGuffin LJ (2012) Improvement of 3D protein models using multiple templates guided by single-template model quality assessment. Bioinformatics 28(14):1851–1857. doi:10.1093/bioinformatics/bts292

    Article  CAS  PubMed  Google Scholar 

  14. Roche DB, Buenavista MT, Tetchner SJ, McGuffin LJ (2011) The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction. Nucleic acids research 39(Web Server issue):W171–W176. doi:10.1093/nar/gkr184

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  15. Zhou H, Zhou Y (2005) SPARKS 2 and SP3 servers in CASP6. Proteins 61(Suppl 7):152–156. doi:10.1002/prot.20732

    Article  CAS  PubMed  Google Scholar 

  16. Soding J, Biegert A, Lupas AN (2005) The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res 33(Web Server issue):W244–W248. doi:10.1093/nar/gki408

    Article  PubMed Central  PubMed  Google Scholar 

  17. Soding J (2005) Protein homology detection by HMM-HMM comparison. Bioinformatics 21(7):951–960. doi:10.1093/bioinformatics/bti125, bti125 [pii]

    Article  PubMed  Google Scholar 

  18. Margelevicius M, Laganeckas M, Venclovas C (2010) COMA server for protein distant homology search. Bioinformatics 26(15):1905–1906. doi:10.1093/bioinformatics/btq306

    Article  CAS  PubMed  Google Scholar 

  19. Margelevicius M, Venclovas C (2010) Detection of distant evolutionary relationships between protein families using theory of sequence profile-profile comparison. BMC Bioinformatics 11:89. doi:10.1186/1471-2105-11-89

    Article  PubMed Central  PubMed  Google Scholar 

  20. Wu S, Zhang Y (2007) LOMETS: a local meta-threading-server for protein structure prediction. Nucleic Acids Res 35(10):3375–3382. doi:10.1093/nar/gkm251

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. McGuffin LJ, Roche DB (2010) Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments. Bioinformatics 26(2):182–188. doi:10.1093/bioinformatics/btp629

    Article  CAS  PubMed  Google Scholar 

  22. Kryshtafovych A, Barbato A, Fidelis K, Monastyrskyy B, Schwede T, Tramontano A (2014) Assessment of the assessment: evaluation of the model quality estimates in CASP10. Proteins 82(Suppl 2):112–126. doi:10.1002/prot.24347

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. McGuffin LJ (2008) Intrinsic disorder prediction from the analysis of multiple protein fold recognition models. Bioinformatics 24(16):1798–1804. doi:10.1093/bioinformatics/btn326

    Article  CAS  PubMed  Google Scholar 

  24. Roche DB, Buenavista MT, McGuffin LJ (2013) The FunFOLD2 server for the prediction of protein-ligand interactions. Nucleic Acids Res 41(Web Server issue):W303–W307. doi:10.1093/nar/gkt498

    Article  PubMed Central  PubMed  Google Scholar 

  25. Bordoli L, Schwede T (2012) Automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal. Methods Mol Biol 857:107–136. doi:10.1007/978-1-61779-588-6_5

    Article  CAS  PubMed  Google Scholar 

  26. Berman HM, Burley SK, Chiu W, Sali A, Adzhubei A, Bourne PE, Bryant SH, Dunbrack RL Jr, Fidelis K, Frank J, Godzik A, Henrick K, Joachimiak A, Heymann B, Jones D, Markley JL, Moult J, Montelione GT, Orengo C, Rossmann MG, Rost B, Saibil H, Schwede T, Standley DM, Westbrook JD (2006) Outcome of a workshop on archiving structural models of biological macromolecules. Structure 14(8):1211–1217

    Article  CAS  PubMed  Google Scholar 

  27. Berman HM, Westbrook JD, Gabanyi MJ, Tao W, Shah R, Kouranov A, Schwede T, Arnold K, Kiefer F, Bordoli L, Kopp J, Podvinec M, Adams PD, Carter LG, Minor W, Nair R, La Baer J (2009) The protein structure initiative structural genomics knowledgebase. Nucleic Acids Res 37(Database issue):D365–D368. doi:10.1093/nar/gkn790

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. Bindschedler LV, McGuffin LJ, Burgis TA, Spanu PD, Cramer R (2011) Proteogenomics and in silico structural and functional annotation of the barley powdery mildew Blumeria graminis f. sp. hordei. Methods 54(4):432–441. doi:10.1016/j.ymeth.2011.03.006

    Article  CAS  PubMed  Google Scholar 

  29. Pedersen C, Loren V, van Themaat E, McGuffin LJ, Abbott JC, Burgis TA, Barton G, Bindschedler LV, Lu X, Maekawa T, Wessling R, Cramer R, Thordal-Christensen H, Panstruga R, Spanu PD (2012) Structure and evolution of barley powdery mildew effector candidates. BMC Genomics 13:694. doi:10.1186/1471-2164-13-694

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  30. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25(17):3389–3402, doi:gka562 [pii]

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  31. Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, Heger A, Hetherington K, Holm L, Mistry J, Sonnhammer EL, Tate J, Punta M (2014) Pfam: the protein families database. Nucleic Acids Res 42(Database issue):D222–D230. doi:10.1093/nar/gkt1223

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  32. Letunic I, Doerks T, Bork P (2014) SMART: recent updates, new developments and status in 2015. Nucleic Acids Res. doi:10.1093/nar/gku949

    Google Scholar 

  33. Roche DB, Tetchner SJ, McGuffin LJ (2011) FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins. BMC Bioinformatics 12:160. doi:10.1186/1471-2105-12-160

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  34. Jmol: an open-source Java viewer for chemical structures in 3D. http://www.jmol.org/

  35. Zhang Y, Skolnick J (2005) TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res 33(7):2302–2309. doi:10.1093/nar/gki524, 33/7/2302 [pii]

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  36. Tucci V, Kleefstra T, Hardy A, Heise I, Maggi S, Willemsen MH, Hilton H, Esapa C, Simon M, Buenavista MT, McGuffin LJ, Vizor L, Dodero L, Tsaftaris S, Romero R, Nillesen WN, Vissers LE, Kempers MJ, Vulto-van Silfhout AT, Iqbal Z, Orlando M, Maccione A, Lassi G, Farisello P, Contestabile A, Tinarelli F, Nieus T, Raimondi A, Greco B, Cantatore D, Gasparini L, Berdondini L, Bifone A, Gozzi A, Wells S, Nolan PM (2014) Dominant beta-catenin mutations cause intellectual disability with recognizable syndromic features. J Clin Invest 124(4):1468–1482. doi:10.1172/JCI70372

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  37. Fuller SJ, McGuffin LJ, Marshall AK, Giraldo A, Pikkarainen S, Clerk A, Sugden PH (2012) A novel non-canonical mechanism of regulation of MST3 (mammalian Sterile20-related kinase 3). Biochem J 442(3):595–610. doi:10.1042/BJ20112000

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  38. Sugden PH, McGuffin LJ, Clerk A (2013) SOcK, MiSTs, MASK and STicKs: the GCKIII (germinal centre kinase III) kinases and their heterologous protein-protein interactions. Biochem J 454(1):13–30. doi:10.1042/BJ20130219

    Article  CAS  PubMed  Google Scholar 

  39. Dunwell TL, McGuffin LJ, Dunwell JM, Pfeifer GP (2013) The mysterious presence of a 5-methylcytosine oxidase in the Drosophila genome: possible explanations. Cell Cycle 12(21):3357–3365. doi:10.4161/cc.26540

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. Eswar N, Webb B, Marti-Renom MA, Madhusudhan MS, Eramian D, Shen MY, Pieper U, Sali A (2006) Comparative protein structure modeling using Modeller. Curr Protoc Bioinformatics Chapter 5:Unit 5 6. doi:10.1002/0471250953.bi0506s15

    Google Scholar 

  41. Matthews BW (1975) Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim Biophys Acta 405(2):442–451

    Article  CAS  PubMed  Google Scholar 

  42. Roche DB, Tetchner SJ, McGuffin LJ (2010) The binding site distance test score: a robust method for the assessment of predicted protein binding sites. Bioinformatics 26(22):2920–2921. doi:10.1093/bioinformatics/btq543

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

DBR is a recipient of a Young Investigator Fellowship from the Institut de Biologie Computationnelle, Université de Montpellier (ANR Investissements D’Avenir Bio-informatique: projet IBC). This research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 246556 [to D.B.R.].

Author information

Authors and Affiliations

  1. Institut de Biologie Computationnelle, LIRMM, CNRS, Université de Montpellier, Montpellier, France

    Daniel Barry Roche

  2. CEA, DSV, IG, Genoscope, Évry, France

    Daniel Barry Roche

  3. CNRS-UMR8030, Évry, France

    Daniel Barry Roche

  4. Université d’Évry Val d’Essonne, Évry, France

    Daniel Barry Roche

  5. PRES UniverSud Paris, Saint-Aubin, France

    Daniel Barry Roche

  6. School of Biological Sciences, University of Reading, Reading, UK

    Liam James McGuffin

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  1. Daniel Barry Roche
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  2. Liam James McGuffin
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Correspondence to Daniel Barry Roche .

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Editors and Affiliations

  1. Departamento de Biología Molecular, Universidad de Cantabria, Facultad de Medicina, Cardenal Herrera Oria s/n, Instituto de Biomedicina y Biotecnología de Cantabria, Universidad de Cantabria, CSIC, Santander, Spain

    Alberto Sanchez-Diaz

  2. Universidad de Salamanca, Instituto de Biología Funcional y Genómica, CSIC, Salamanca, Spain

    Pilar Perez

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Roche, D.B., McGuffin, L.J. (2016). Toolbox for Protein Structure Prediction. In: Sanchez-Diaz, A., Perez, P. (eds) Yeast Cytokinesis. Methods in Molecular Biology, vol 1369. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3145-3_23

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  • DOI: https://doi.org/10.1007/978-1-4939-3145-3_23

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3144-6

  • Online ISBN: 978-1-4939-3145-3

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