Skip to main content
SpringerLink
Log in

Exploring Protein Conformational Diversity

  • Protocol
  • First Online:
Book cover Computational Methods in Protein Evolution

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1851))

Abstract

The native state of proteins is composed of conformers in dynamical equilibrium. In this chapter, different issues related to conformational diversity are explored using a curated and experimentally based database called CoDNaS (Conformational Diversity in the Native State). This database is a collection of redundant structures for the same sequence. CoDNaS estimates the degree of conformational diversity using different global and local structural similarity measures. It allows the user to explore how structural differences among conformers change as a function of several structural features providing further biological information. This chapter explores the measurement of conformational diversity and its relationship with sequence divergence. Also, it discusses how proteins with high conformational diversity could affect homology modeling techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Gerstein M, Lesk AM, Chothia C (1994) Structural mechanisms for domain movements in proteins. Biochemistry 33:6739–6749

    Article  CAS  Google Scholar 

  2. Gerstein M, Krebs W (1998) A database of macromolecular motions. Nucleic Acids Res 26:4280–4290

    Article  CAS  Google Scholar 

  3. Gu Y, Li D-W, Brüschweiler R (2015) Decoding the mobility and time scales of protein loops. J Chem Theory Comput 11:1308–1314

    Article  CAS  Google Scholar 

  4. Gora A, Brezovsky J, Damborsky J (2013) Gates of enzymes. Chem Rev 113:5871–5923

    Article  CAS  Google Scholar 

  5. Perutz MF, Bolton W, Diamond R et al (1964) Structure of haemoglobin. An X-ray examination of reduced horse haemoglobin. Nature 203:687–690

    Article  CAS  Google Scholar 

  6. Popovych N, Sun S, Ebright RH et al (2006) Dynamically driven protein allostery. Nat Struct Mol Biol 13:831–838

    Article  CAS  Google Scholar 

  7. Dunker AK, Keith Dunker A, Silman I et al (2008) Function and structure of inherently disordered proteins. Curr Opin Struct Biol 18:756–764

    Article  CAS  Google Scholar 

  8. Boehr DD, McElheny D, Dyson HJ et al (2006) The dynamic energy landscape of dihydrofolate reductase catalysis. Science 313:1638–1642

    Article  CAS  Google Scholar 

  9. Tsai CJ, Del Sol A, Nussinov R (2009) Protein allostery, signal transmission and dynamics: a classification scheme of allosteric mechanisms. Mol BioSyst 5:207–216

    Article  CAS  Google Scholar 

  10. Hilser VJ (2010) Biochemistry. An ensemble view of allostery. Science 327:653–654

    Article  CAS  Google Scholar 

  11. James LC, Roversi P, Tawfik DS (2003) Antibody multispecificity mediated by conformational diversity. Science 299:1362–1367

    Article  CAS  Google Scholar 

  12. Smock RG, Gierasch LM (2009) Sending signals dynamically. Science 324:198–203

    Article  CAS  Google Scholar 

  13. Yogurtcu ON, Bora Erdemli S, Nussinov R et al (2008) Restricted mobility of conserved residues in protein-protein interfaces in molecular simulations. Biophys J 94:3475–3485

    Article  CAS  Google Scholar 

  14. Lynch TJ, Bell DW, Sordella R et al (2004) Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 350:2129–2139

    Article  CAS  Google Scholar 

  15. Tokuriki N, Stricher F, Serrano L et al (2008) How protein stability and new functions trade off. PLoS Comput Biol 4:e1000002

    Article  Google Scholar 

  16. Zea DJ, Miguel Monzon A, Fornasari MS et al (2013) Protein conformational diversity correlates with evolutionary rate. Mol Biol Evol 30:1500–1503

    Article  CAS  Google Scholar 

  17. Zea DJ, Monzon AM, Gonzalez C et al (2016) Disorder transitions and conformational diversity cooperatively modulate biological function in proteins. Protein Sci 25:1138–1146

    Article  CAS  Google Scholar 

  18. Best RB, Lindorff-Larsen K, DePristo MA et al (2006) Relation between native ensembles and experimental structures of proteins. Proc Natl Acad Sci U S A 103:10901–10906

    Article  CAS  Google Scholar 

  19. Burra PV, Zhang Y, Godzik A et al (2009) Global distribution of conformational states derived from redundant models in the PDB points to non-uniqueness of the protein structure. Proc Natl Acad Sci U S A 106:10505–10510

    Article  CAS  Google Scholar 

  20. Berman HM, Westbrook J, Feng Z et al (2000) The Protein Data Bank. Nucleic Acids Res 28:235–242

    Article  CAS  Google Scholar 

  21. Wei G, Xi W, Nussinov R et al (2016) Protein ensembles: how does nature harness thermodynamic fluctuations for life? The diverse functional roles of conformational ensembles in the cell. Chem Rev 116:6516. https://doi.org/10.1021/acs.chemrev.5b00562

    Article  CAS  PubMed  Google Scholar 

  22. Marino-Buslje C, Monzon AM, Zea DJ et al (2017) On the dynamical incompleteness of the Protein Data Bank. Brief Bioinform. https://doi.org/10.1093/bib/bbx084

  23. Monzon AM, Juritz E, Fornasari MS et al (2013) CoDNaS: a database of conformational diversity in the native state of proteins. Bioinformatics 29:2512–2514

    Article  CAS  Google Scholar 

  24. Monzon AM, Rohr CO, Fornasari MS et al (2016) CoDNaS 2.0: a comprehensive database of protein conformational diversity in the native state. Database 2016:baw038

    Article  Google Scholar 

  25. Altschul SF, Gish W, Miller W et al (1990) Basic local alignment search tool. J Mol Biol 215:403–410

    Article  CAS  Google Scholar 

  26. Ortiz AR, Strauss CEM, Olmea O (2002) MAMMOTH (matching molecular models obtained from theory): an automated method for model comparison. Protein Sci 11:2606–2621

    Article  CAS  Google Scholar 

  27. The UniProt Consortium (2017) UniProt: the universal protein knowledgebase. Nucleic Acids Res 45:D158–D169

    Article  Google Scholar 

  28. Sillitoe I, Lewis TE, Cuff A et al (2015) CATH: comprehensive structural and functional annotations for genome sequences. Nucleic Acids Res 43:D376–D381

    Article  CAS  Google Scholar 

  29. Bairoch A (2000) The ENZYME database in 2000. Nucleic Acids Res 28:304–305

    Article  CAS  Google Scholar 

  30. Potenza E, Di Domenico T, Walsh I et al (2015) MobiDB 2.0: an improved database of intrinsically disordered and mobile proteins. Nucleic Acids Res 43:D315–D320

    Article  CAS  Google Scholar 

  31. Ashburner M, Ball CA, Blake JA et al (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25:25–29

    Article  CAS  Google Scholar 

  32. Qin H, Shi J, Noberini R et al (2008) Crystal structure and NMR binding reveal that two small molecule antagonists target the high affinity ephrin-binding channel of the EphA4 receptor. J Biol Chem 283:29473–29484

    Article  CAS  Google Scholar 

  33. Qin H, Lim L, Song J (2012) Protein dynamics at Eph receptor-ligand interfaces as revealed by crystallography, NMR and MD simulations. BMC Biophys 5:2

    Article  CAS  Google Scholar 

  34. Bowden TA, Aricescu AR, Nettleship JE et al (2009) Structural plasticity of eph receptor A4 facilitates cross-class ephrin signaling. Structure 17:1386–1397

    Article  CAS  Google Scholar 

  35. Monzon AM, Zea DJ, Fornasari MS et al (2017) Conformational diversity analysis reveals three functional mechanisms in proteins. PLoS Comput Biol 13:1–29

    Article  Google Scholar 

  36. Parisi G, Zea DJ, Monzon AM et al (2015) Conformational diversity and the emergence of sequence signatures during evolution. Curr Opin Struct Biol 32:58–65

    Article  CAS  Google Scholar 

  37. Gutteridge A, Thornton J (2005) Conformational changes observed in enzyme crystal structures upon substrate binding. J Mol Biol 346:21–28

    Article  CAS  Google Scholar 

  38. Mesecar AD, Stoddard BL, Koshland DE Jr (1997) Orbital steering in the catalytic power of enzymes: small structural changes with large catalytic consequences. Science 277:202

    Article  CAS  Google Scholar 

  39. Koshland DE (1998) Conformational changes: how small is big enough? Nat Med 4:1112–1114

    Article  CAS  Google Scholar 

  40. Rashin AA, Rashin AHL, Jernigan RL (2010) Diversity of function-related conformational changes in proteins: coordinate uncertainty, fragment rigidity, and stability. Biochemistry 49:5683–5704

    Article  CAS  Google Scholar 

  41. Juritz E, Palopoli N, Fornasari S et al (2013) Protein conformational diversity modulates sequence divergence. Mol Biol Evol 30:79–87

    Article  CAS  Google Scholar 

  42. Liu Y, Bahar I (2012) Sequence evolution correlates with structural dynamics. Mol Biol Evol 29:2253–2263

    Article  CAS  Google Scholar 

  43. Saldaño TE, Monzon AM, Parisi G et al (2016) Evolutionary conserved positions define protein conformational diversity. PLoS Comput Biol 12:e1004775

    Article  Google Scholar 

  44. Jeon J, Nam H-J, Choi YS et al (2011) Molecular evolution of protein conformational changes revealed by a network of evolutionarily coupled residues. Mol Biol Evol 28:2675–2685

    Article  CAS  Google Scholar 

  45. Codoñer FM, Fares MA (2008) Why should we care about molecular coevolution? Evol Bioinformatics Online 4:29–38

    Google Scholar 

  46. de Oliveira SHP, Shi J, Deane CM (2017) Comparing co-evolution methods and their application to template-free protein structure prediction. Bioinformatics 33:373–381

    PubMed  Google Scholar 

  47. Morcos F, Jana B, Hwa T et al (2013) Coevolutionary signals across protein lineages help capture multiple protein conformations. Proc Natl Acad Sci U S A 110:20533–20538

    Article  CAS  Google Scholar 

  48. Rodriguez-Rivas J, Marsili S, Juan D et al (2016) Conservation of coevolving protein interfaces bridges prokaryote–eukaryote homologies in the twilight zone. Proc Natl Acad Sci U S A 113:15018–15023

    Article  CAS  Google Scholar 

  49. Zea DJ, Monzon AM, Parisi G, et al (2018) How is structural divergence related to evolutionary information?, Molecular Phylogenetics and Evolution, Available online 25 June 2018, ISSN 1055-7903, https://doi.org/10.1016/j.ympev.2018.06.033

    Article  Google Scholar 

  50. Sfriso P, Duran-Frigola M, Mosca R et al (2016) Residues coevolution guides the systematic identification of alternative functional conformations in proteins. Structure 24:116–126

    Article  CAS  Google Scholar 

  51. Chothia C, Lesk AM (1986) The relation between the divergence of sequence and structure in proteins. EMBO J 5:823–826

    Article  CAS  Google Scholar 

  52. Koehl P, Levitt M (2002) Sequence variations within protein families are linearly related to structural variations. J Mol Biol 2836:551–562

    Article  Google Scholar 

  53. Hubbard TJ, Blundell TL (1987) Comparison of solvent-inaccessible cores of homologous proteins: definitions useful for protein modelling. Protein Eng 1:159–171

    Article  CAS  Google Scholar 

  54. Russell RB, Barton GJ (1994) Structural features can be unconserved in proteins with similar folds. An analysis of side-chain to side-chain contacts secondary structure and accessibility. J Mol Biol 244:332. https://doi.org/10.1006/jmbi.1994.1733

    Article  CAS  PubMed  Google Scholar 

  55. Wen B, Lampe JN, Roberts AG et al (2005) Evolutionary plasticity of protein families: coupling between sequence and structure variation. Proteins 61:535–544

    Article  Google Scholar 

  56. Illergård K, Ardell DH, Elofsson A (2009) Structure is three to ten times more conserved than sequence--a study of structural response in protein cores. Proteins 77:499–508

    Article  Google Scholar 

  57. Monzon AM, Zea DJ, Marino-Buslje C et al (2017) Homology modeling in a dynamical world. Protein Sci 26:2195

    Article  CAS  Google Scholar 

  58. Sikic K, Tomic S, Carugo O (2010) Systematic comparison of crystal and NMR protein structures deposited in the protein data bank. Open Biochem J 4:83–95

    Article  CAS  Google Scholar 

  59. Kufareva I, Abagyan R (2012) Methods of protein structure comparison. In: Orry AJW, Abagyan R (eds) Homology modeling: methods and protocols. Humana Press, Totowa, NJ, pp 231–257

    Google Scholar 

  60. Siew N, Elofsson A, Rychlewski L et al (2000) MaxSub: an automated measure for the assessment of protein structure prediction quality. Bioinformatics 16:776–785

    Article  CAS  Google Scholar 

  61. Velankar S, Dana JM, Jacobsen J et al (2013) SIFTS: structure integration with function, taxonomy and sequences resource. Nucleic Acids Res 41:D483–D489

    Article  CAS  Google Scholar 

  62. Zea DJ, Anfossi D, Nielsen M et al (2016) MIToS.jl: Mutual information tools for protein sequence analysis in the Julia language. Bioinformatics 33(4):564–565

    Google Scholar 

  63. Zoete V, Michielin O, Karplus M (2002) Relation between sequence and structure of HIV-1 protease inhibitor complexes: a model system for the analysis of protein flexibility. J Mol Biol 315:21–52

    Article  CAS  Google Scholar 

  64. Hrabe T, Li Z, Sedova M et al (2016) PDBFlex: exploring flexibility in protein structures. Nucleic Acids Res 44:D423–D428

    Article  CAS  Google Scholar 

  65. Maguid S, Fernández-Alberti S, Parisi G et al (2006) Evolutionary conservation of protein backbone flexibility. J Mol Evol 63:448–457

    Article  CAS  Google Scholar 

  66. Pettersen EF, Goddard TD, Huang CC et al (2004) UCSF chimera--a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612

    Article  CAS  Google Scholar 

  67. Lee RA, Razaz M, Hayward S (2003) The DynDom database of protein domain motions. Bioinformatics 19:1290–1291

    Article  CAS  Google Scholar 

  68. Amemiya T, Koike R, Kidera A et al (2012) PSCDB: a database for protein structural change upon ligand binding. Nucleic Acids Res 40:D554–D558

    Article  CAS  Google Scholar 

Download references

Acknowledgments

Authors would like to thank Paula Benencio for helping us with manuscript proofreading.

Author information

Authors and Affiliations

  1. Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, CONICET, Bernal, Argentina

    Alexander Miguel Monzon, Maria Silvina Fornasari & Gustavo Parisi

  2. Structural Bioinformatics Unit, Fundación Instituto Leloir, CONICET, Buenos Aires, Argentina

    Diego Javier Zea

Authors
  1. Alexander Miguel Monzon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maria Silvina Fornasari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Diego Javier Zea
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gustavo Parisi
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. GlaxoSmithKline, Cellzome – a GSK company Meyerhofstrasse 1, Heidelberg, Baden-Württemberg, Germany

    Tobias Sikosek

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Monzon, A.M., Fornasari, M.S., Zea, D.J., Parisi, G. (2019). Exploring Protein Conformational Diversity. In: Sikosek, T. (eds) Computational Methods in Protein Evolution. Methods in Molecular Biology, vol 1851. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8736-8_20

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-8736-8_20

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8735-1

  • Online ISBN: 978-1-4939-8736-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation