RNA Structure Refinement Using the ERRASER-Phenix Pipeline

  • Fang-Chieh Chou
  • Nathaniel Echols
  • Thomas C. Terwilliger
  • Rhiju Das
Part of the Methods in Molecular Biology book series (MIMB, volume 1320)

Abstract

The final step of RNA crystallography involves the fitting of coordinates into electron density maps. The large number of backbone atoms in RNA presents a difficult and tedious challenge, particularly when experimental density is poor. The ERRASER-Phenix pipeline can improve an initial set of RNA coordinates automatically based on a physically realistic model of atomic-level RNA interactions. The pipeline couples diffraction-based refinement in Phenix with the Rosetta-based real-space refinement protocol ERRASER (Enumerative Real-Space Refinement ASsisted by Electron density under Rosetta). The combination of ERRASER and Phenix can improve the geometrical quality of RNA crystallographic models while maintaining or improving the fit to the diffraction data (as measured by Rfree). Here we present a complete tutorial for running ERRASER-Phenix through the Phenix GUI, from the command-line, and via an application in the Rosetta On-line Server that Includes Everyone (ROSIE).

Key words

RNA structure Structure prediction X-ray crystallography Refinement Force field 

References

  1. 1.
    Golden BL, Kim H, Chase E (2005) Crystal structure of a phage Twort group I ribozyme-product complex. Nat Struct Mol Biol 12:82–89PubMedCrossRefGoogle Scholar
  2. 2.
    Serganov A, Huang L, Patel DJ (2008) Structural insights into amino acid binding and gene control by a lysine riboswitch. Nature 455:1263–1267PubMedCentralPubMedCrossRefGoogle Scholar
  3. 3.
    Dunkle JA, Wang L, Feldman MB, Pulk A, Chen VB, Kapral GJ, Noeske J, Richardson JS, Blanchard SC, Cate JH (2011) Structures of the bacterial ribosome in classical and hybrid states of tRNA binding. Science 332:981–984PubMedCentralPubMedCrossRefGoogle Scholar
  4. 4.
    Davis IW, Leaver-Fay A, Chen VB, Block JN, Kapral GJ, Wang X, Murray LW, Arendall WB 3rd, Snoeyink J, Richardson JS, Richardson DC (2007) MolProbity: all-atom contacts and structure validation for proteins and nucleic acids. Nucleic Acids Res 35(suppl 2):W375–W383PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    Chen VB, Arendall WB 3rd, Headd JJ, Keedy DA, Immormino RM, Kapral GJ, Murray LW, Richardson JS, Richardson DC (2010) MolProbity: all-atom structure validation for macromolecular crystallography. Acta Cryst D 66:12–21CrossRefGoogle Scholar
  6. 6.
    Das R, Baker D (2007) Automated de novo prediction of native-like RNA tertiary structures. Proc Natl Acad Sci U S A 104:14664–14669PubMedCentralPubMedCrossRefGoogle Scholar
  7. 7.
    Das R, Karanicolas J, Baker D (2010) Atomic accuracy in predicting and designing noncanonical RNA structure. Nat Methods 7:291–294PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Sripakdeevong P, Kladwang W, Das R (2011) An enumerative stepwise ansatz enables atomic-accuracy RNA loop modeling. Proc Natl Acad Sci U S A 108:20573–20578PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    DiMaio F, Terwilliger TC, Read RJ, Wlodawer A, Oberdorfer G, Wagner U, Valkov E, Alon A, Fass D, Axelrod HL, Das D, Vorobiev SM, Iwaï H, Pokkuluri PR, Baker D (2011) Improved molecular replacement by density- and energy-guided protein structure optimization. Nature 473:540–543PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    DiMaio F, Tyka MD, Baker ML, Chiu W, Baker D (2009) Refinement of protein structures into low-resolution density maps using Rosetta. J Mol Biol 392:181–190PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Adams PD, Afonine PV, Bunkoczi G, Chen VB, Davis IW, Echols N, Headd JJ, Hung LW, Kapral GJ, Grosse-Kunstleve RW, McCoy AJ, Moriarty NW, Oeffner R, Read RJ, Richardson DC, Richardson JS, Terwilligen TC, Zwart PH (2010) PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Cryst D 66:213–221CrossRefGoogle Scholar
  12. 12.
    Chou FC, Sripakdeevong P, Dibrov SM, Hermann T, Das R (2013) Correcting pervasive errors in RNA crystallography through enumerative structure prediction. Nat Methods 10:74–76PubMedCentralPubMedCrossRefGoogle Scholar
  13. 13.
    Lyskov S, Chou FC, Conchuir SO, Der BS, Drew K, Kuroda D, Xu J, Weitzner BD, Renfrew PD, Sripakdeevong P, Borgo B, Havranek JJ, Kuhlman B, Kortemme T, Bonneau R, Gray JJ, Das R (2013) Serverification of molecular modeling applications: the Rosetta online server that includes everyone (ROSIE). PLoS One 8:e63906PubMedCentralPubMedCrossRefGoogle Scholar
  14. 14.
    Leaver-Fay A, Tyka M, Lewis SM, Lange OF, Thompson J, Jacak R, Kaufman K, Renfrew PD, Smith CA, Sheffler W, Davis IW, Cooper S, Treuille A, Mandell DJ, Richter F, Ban YE, Fleishman SJ, Corn J, Kortemme T, Gray JJ, Kuhlman B, Baker D, Bradley P (2011) ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules. Methods Enzymol 487:545–574PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Afonine PV, Grosse-Kunstleve RW, Echols N, Headd JJ, Moriarty NW, Mustyakimov M, Terwilliger TC, Urzhumtsev A, Zwart PH, Adams PD (2012) Towards automated crystallographic structure refinement with phenix.refine. Acta Cryst D 68:352–367CrossRefGoogle Scholar
  16. 16.
    Sheldrick G (2008) A short history of SHELX. Acta Cryst A 64:112–122CrossRefGoogle Scholar
  17. 17.
    Vagin AA, Steiner RA, Lebedev AA, Potterton L, McNicholas S, Long F, Murshdov GN (2004) REFMAC5 dictionary: organization of prior chemical knowledge and guidelines for its use. Acta Cryst D 12:2184–2195CrossRefGoogle Scholar
  18. 18.
    Brunger AT (2007) Version 1.2 of the crystallography and NMR system. Nat Protocols 2:2728–2733PubMedCrossRefGoogle Scholar
  19. 19.
    Praznikar J, Afonine PV, Guncar G, Adams PD, Turk D (2009) Averaged kick maps: less noise, more signal…and probably less bias. Acta Cryst D 65:921–931CrossRefGoogle Scholar
  20. 20.
    Echols N, Grosse-Kunstleve RW, Afonine PV, Bunkoczi G, Chen VB, Headd JJ, McCoy AJ, Moriarty NW, Read RJ, Richardsson DC, Richardson JS, Terwillerger TC, Adams PD (2012) Graphical tools for macromolecular crystallography in PHENIX. J Appl Crystallogr 45:581–586PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Word JM, Lovell SC, LaBean TH, Taylor HC, Zalis ME, Presley BK, Richardson JS, Richardson DC (1999) Visualizing and quantifying molecular goodness-of-fit: small-probe contact dots with explicit hydrogen atoms. J Mol Biol 285:1711–1733PubMedCrossRefGoogle Scholar
  22. 22.
    Murray LJW, Arendall WB, Richardson DC, Richardson JS (2003) RNA backbone is rotameric. Proc Natl Acad Sci U S A 100:13904–13909PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Richardson JS, Schneider B, Murray LW, Kapral GJ, Immormino RM, Headd JJ, Richardson DC, Ham D, Hershkovits E, Williams LD, Keating KS, Pyle AM, Micallef D, Westbrook J, Berman HM, RNA Ontology Consortium (2008) RNA backbone: consensus all-angle conformers and modular string nomenclature (an RNA Ontology Consortium contribution). RNA 14:465–481PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Fang-Chieh Chou
    • 1
  • Nathaniel Echols
    • 2
  • Thomas C. Terwilliger
    • 3
  • Rhiju Das
    • 1
  1. 1.Department of BiochemistryStanford UniversityStanfordUSA
  2. 2.Physical Biosciences DivisionLawrence Berkeley National LaboratoryBerkeleyUSA
  3. 3.Bioscience DivisionLos Alamos National LaboratoryLos AlamosUSA

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