Studying RNA–Protein Complexes Using X-Ray Crystallography

  • Protocol
  • First Online:
Protein-Ligand Interactions

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2263))

Abstract

A wide range of biological processes rely on complexes between ribonucleic acids (RNAs) and proteins. Determining the three-dimensional structures of RNA–protein complexes is crucial to elucidate the relationship between structure and biological function. X-ray crystallography represents the most widely used technique to characterize RNA–protein complexes at atomic resolution; however, determining their three-dimensional structures remains challenging. RNase contamination can ruin crystallization experiments by degrading RNA in complex with protein, leading to sample heterogeneity, and the conformational flexibility inherent in both protein and RNA can limit crystallizability. Furthermore, the three-dimensional structure can be difficult to accurately model at the typical diffraction limit of 2.5 Å resolution or lower for RNA–protein complex crystals. At this resolution, phosphates, which are electron dense, and bases, which are large, rigid, and planar, tend to be well resolved and easy to position in the electron density map, whereas other features, e.g., sugar atoms, can be difficult to accurately position. This chapter focuses on methods that can be used to overcome the unique problems faced when crystallizing RNA–protein complexes and determining their three-dimensional structures using X-ray crystallography.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Protocol
EUR 44.95
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 106.99
Price includes VAT (Germany)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 139.09
Price includes VAT (Germany)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
EUR 213.99
Price includes VAT (Germany)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Hentze MW, Castello A, Schwarzl T et al (2018) A brave new world of RNA-binding proteins. Nat Rev Mol Cell Biol 19:327–341

    Google Scholar 

  2. Rould MA, Perona JJ, Söll D et al (1989) Structure of E. coli glutaminyl-tRNA synthetase complexed with tRNA(Gln) and ATP at 2.8 A resolution. Science 246:1135–1142

    Article  CAS  Google Scholar 

  3. Berman HM, Battistuz T, Bhat TN et al (2002) The protein data bank. Acta Crystallogr D Biol Crystallogr D58:899–907

    Article  CAS  Google Scholar 

  4. Connelly CM, Moon MH, Schneekloth JS (2016) The emerging role of RNA as a therapeutic target for small molecules. Cell Chem Biol 23:1077–1090

    Article  CAS  Google Scholar 

  5. Collaborative Computational Project, Number 4 (1994) The CCP4 suite: programs for protein crystallography. Acta Crystallogr D Biol Crystallogr D50:760–763

    Article  Google Scholar 

  6. Emsley P, Cowtan K (2004) Coot: model-building tools for molecular graphics. Acta Crystallogr D Biol Crystallogr D60:2126–2132

    Article  CAS  Google Scholar 

  7. Emsley P, Lohkamp B, Scott WG et al (2010) Features and development of Coot. Acta Crystallogr D Biol Crystallogr D66:486–501

    Article  Google Scholar 

  8. Chojnowski G, Waleń T, Bujnicki JM (2014) RNA Bricks—a database of RNA 3D motifs and their interactions. Nucleic Acids Res 42:D123–D131

    Article  CAS  Google Scholar 

  9. Petrov AI, Zirbel CL, Leontis NB (2013) Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas. RNA 19:1327–1340

    Article  CAS  Google Scholar 

  10. Popenda M, Szachniuk M, Blazewicz M et al (2010) RNA FRABASE 2.0: an advanced web-accessible database with the capacity to search the three-dimensional fragments within RNA structures. BMC Bioinformatics 11:231

    Article  Google Scholar 

  11. Pan X, Shen HB (2018) Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks. Bioinformatics 34:3427–3436

    Article  CAS  Google Scholar 

  12. Tuszynska I, Magnus M, Jonak K et al (2015) NPDock: a web server for protein–nucleic acid docking. Nucleic Acids Res 43(W1):W425–W430

    Article  CAS  Google Scholar 

  13. Chauvot de Beauchene I, de Vries SJ, Zacharias M (2016) Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins. Nucleic Acids Res 44:4565–4580

    Article  CAS  Google Scholar 

  14. Rio DC (2014) Electrophoretic mobility shift assays for RNA-protein complexes. Cold Spring Harb Protoc 2014:435–440

    PubMed  Google Scholar 

  15. Oubridge C, Ito N, Teo CH et al (1995) Crystallisation of RNA-protein complexes. II. The application of protein engineering for crystallisation of the U1A protein-RNA complex. J Mol Biol 249:409–423

    Article  CAS  Google Scholar 

  16. Obayashi E, Oubridge C, Krummel DP et al (2007) Crystallization of RNA-Protein complexes. Methods Mol Biol 363:259–276

    Article  CAS  Google Scholar 

  17. Yakhnin AV, Yakhnin H, Babitzke P (2012) Gel mobility shift assays to detect protein-RNA interactions. Methods Mol Biol 905:201–211

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Ke A, Doudna JA (2004) Crystallization of RNA and RNA–protein complexes. Methods 34:408–414

    Article  CAS  Google Scholar 

  19. Newman J, Egan D, Walter TS et al (2005) Towards rationalization of crystallization screening for small- to medium-sized academic laboratories: the PACT/JCSG+ strategy. Acta Crystallogr D Biol Crystallogr D61:1426–1431

    Article  CAS  Google Scholar 

  20. Leslie AGW (1992) Recent changes to the MOSFLM package for processing film and image plate data. Jnt CCP4/ESF-EACMB Newslett Protein Crystallogr 26

    Google Scholar 

  21. Potterton E, Briggs P, Turkenburg M et al (2003) A graphical user interface to the CCP4 program suite. Acta Crystallogr D Biol Crystallogr D59:1131–1137

    Article  CAS  Google Scholar 

  22. Winter (2010) xia2: an expert system for macromolecular crystallography data reduction. J Appl Crystallogr 43:186–190

    Article  CAS  Google Scholar 

  23. Chojnowski G, Bujnicki JM, Bochtler M (2012) RIBER/DIBER: a software suite for crystal content analysis in the studies of protein-nucleic acid complexes. Bioinformatics 28:880–881

    Article  CAS  Google Scholar 

  24. Waterhouse A, Bertoni M, Bienert S et al (2018) SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res 46(W1):W296–W303

    Article  CAS  Google Scholar 

  25. Yang J, Yan R, Roy A et al (2015) The I-TASSER suite: protein structure and function prediction. Nat Methods 12:7–8

    Article  CAS  Google Scholar 

  26. McCoy AJ, Grosse-Kunstleve RW, Adams PD et al (2007) Phaser crystallographic software. J Appl Crystallogr 40:658–674

    Article  CAS  Google Scholar 

  27. Adams PD, Afonine PV, Bunkóczi G et al (2010) PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr D Biol Crystallogr D66:213–221

    Article  Google Scholar 

  28. Keating KS, Pyle AM (2012) RCrane: semi-automated RNA model building. Acta Crystallogr D Biol Crystallogr 68:985–995

    Article  CAS  Google Scholar 

  29. Davis IW, Leaver-Fay A, Chen VB et al (2007) MolProbity: all-atom contacts and structure validation for proteins and nucleic acids. Nucleic Acids Res 35:W375–W383

    Article  Google Scholar 

  30. Krüger DM, Neubacher S, Grossmann TN (2018) Protein-RNA interactions: structural characteristics and hotspot amino acids. RNA 24:1457–1465

    Article  Google Scholar 

  31. Chen WF, Rety S, Guo HL et al (2018) Molecular mechanistic insights into Drosophila DHX36-mediated G-quadruplex unfolding: a structure-based model. Structure 26:403–415

    Article  CAS  Google Scholar 

Download references

Acknowledgments

We would like to thank Dr. Paul Owen at Cancer Research UK Therapeutic Discovery Laboratories (London, UK) for providing Fig. 3 and interpreting the data and Dr. Tobias Schmidt at the Cancer Research UK Beatson Institute (Glasgow, UK) for providing the data and analysis for Figs. 2 and 4.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrew P. Turnbull .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Turnbull, A.P., Wu, X. (2021). Studying RNA–Protein Complexes Using X-Ray Crystallography. In: Daviter, T., Johnson, C.M., McLaughlin, S.H., Williams, M.A. (eds) Protein-Ligand Interactions. Methods in Molecular Biology, vol 2263. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1197-5_20

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-1197-5_20

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1196-8

  • Online ISBN: 978-1-0716-1197-5

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Navigation