Skip to main content
SpringerLink
Log in

Validation of protein backbone structures calculated from NMR angular restraints using Rosetta

  • Article
  • Published:
Journal of Biomolecular NMR Aims and scope Submit manuscript

A Correction to this article was published on 27 August 2022

This article has been updated

Abstract

Multidimensional solid-state NMR spectra of oriented membrane proteins can be used to infer the backbone torsion angles and hence the overall protein fold by measuring dipolar couplings and chemical shift anisotropies, which depend on the orientation of each peptide plane with respect to the external magnetic field. However, multiple peptide plane orientations can be consistent with a given set of angular restraints. This ambiguity is further exacerbated by experimental uncertainty in obtaining and interpreting such restraints. The previously developed algorithms for structure calculations using angular restraints typically involve a sequential walkthrough along the backbone to find the torsion angles between the consecutive peptide plane orientations that are consistent with the experimental data. This method is sensitive to experimental uncertainty in interpreting the peak positions of as low as ± 10 Hz, often yielding high structural RMSDs for the calculated structures. Here we present a significantly improved version of the algorithm which includes the fitting of several peptide planes at once in order to prevent propagation of error along the backbone. In addition, a protocol has been devised for filtering the structural solutions using Rosetta scoring functions in order to find the structures that both fit the spectrum and satisfy bioinformatics restraints. The robustness of the new algorithm has been tested using synthetic angular restraints generated from the known structures for two proteins: a soluble protein 2gb1 (56 residues), chosen for its diverse secondary structure elements, i.e. an alpha-helix and two beta-sheets, and a membrane protein 4a2n, from which the first two transmembrane helices (having a total of 64 residues) have been used. Extensive simulations have been performed by varying the number of fitted planes, experimental error, and the number of NMR dimensions. It has been found that simultaneously fitting two peptide planes always shifted the distribution of the calculated structures toward lower structural RMSD values as compared to fitting a single torsion-angle pair. For each protein, irrespective of the simulation parameters, Rosetta was able to distinguish the most plausible structures, often having structural RMSDs lower than 2 Å with respect to the original structure. This study establishes a framework for de-novo protein structure prediction using a combination of solid-state NMR angular restraints and bioinformatics.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Change history

References

  • Alford RF, Leman JK, Weitzner BD, Duran AM, Tilley DC, Elazar A, Gray JJ (2015) An integrated framework advancing membrane protein modeling and design. PLoS Comput Biol 11:1–23

    Article  Google Scholar 

  • Bertram R, Asbury T, Fabiola F, Quine JR, Cross TA, Chapman MS (2003) Atomic refinement with correlated solid-state NMR restraints. JMR 163:300–309

    Google Scholar 

  • Bryson M, Tian F, Prestegard JH, Valafar H (2008) REDCRAFT: a tool for simultaneous characterization of protein backbone structure and motion from RDC data. JMR 191:322–334

    Google Scholar 

  • Chaudhury S, Lyskov S, Gray JJ (2010) PyRosetta: a script-based interface for implementing molecular modeling algorithm using Rosetta. Bioinformatics 26:689–691

    Article  Google Scholar 

  • Chellapa GD, Rose GD (2015) On interpretation of protein X-ray structures: planarity of the peptide unit. Proteins 83:1687–1692

    Article  Google Scholar 

  • Cornilescu G, Bax A (2000) Measurement of proton, nitrogen, and carbonyl chemical shielding anisotropies in a protein dissolved in a dilute liquid crystalline phase. J Am Chem Soc 122:10143–10154

    Article  Google Scholar 

  • Cornilescu G, Delaglio F, Bax A (1999) Protein backbone angle restraints from searching a database for chemical shift and sequence homology. J Biomol NMR 13:211–222

    Article  Google Scholar 

  • Dvinskikh S, Yamamoto K, Ramamoorthy A (2006) Heteronuclear isotropic mixing separated local field NMR spectroscopy. J. Chem. Phys. 125:034507

    Article  ADS  Google Scholar 

  • Gayen A, Banigan JR, Traaseth NJ (2013) Ligand-Induced Conformational changes of the multidrug resistance transporter EmrE probed by oriented solid-state NMR spectroscopy. Angew Chem Int Ed 52:10321–10324

    Article  Google Scholar 

  • Gleason NJ, Vostrikov VV, Greathouse DV, Koeppe RE (2013) Buried lysine, but not arginine, titrates and alters transmembrane helix tilt. Proc Natl Acad Sci 110:1692–1695

    Article  ADS  Google Scholar 

  • Gronenborn AM, Filpula DR, Essig NZ, Achari A, Whitlow M, Wingfield PT, Clore GM (1991) A novel highly stable fold of the immunoglobin binding domain of streptococcal protein G. Science 253:657–661

    Article  ADS  Google Scholar 

  • Herrmann T, Guntert P (2002) Protein NMR structure determination and automated NOE assignment using the new software CANDID and the torsion angle dynamics alogrithm DYANA. JMB 319:209–227

    Article  Google Scholar 

  • Kabsch W (1976) A solution for the best rotation to relate two sets of vectors. Acta Crystallogr A A32:922–923

    Article  ADS  Google Scholar 

  • Kuhlman B, Baker D (2000) Native protein sequences are close to optimal for their structures. Proc Natl Acad Sci USA 97(19):10383–10388

    Article  ADS  Google Scholar 

  • Kuhlman B, Dantas G, Ireton GC, Varani G, Stoddard BL, Baker D (2003) Design of a novel globular protein fold with atomic-level accuracy. Science 302(5649):1364–1368

    Article  ADS  Google Scholar 

  • Leaver-Fay A, O’Meara MJ, Tyka M, Jacak R, Song Y, Kellogg EH, Thompson J, Davis IW, Pache RA, Lyskov S, Gray JJ, Kortemme T, Richardson JS, Havranek JJ, Snoeyink J, Baker D, Kuhlman B (2013) Scientific benchmarks for guiding macromolecular energy function improvement. Methods Enzymol 523:109

    Article  Google Scholar 

  • Lee DK, Wittebort RJ, Ramamoorthy A (1998) Characterization of 15N chemical shift and 1H–15N dipolar coupling interactions in a peptide bond of uniaxially oriented and polycrystalline samples by one-dimensional dipolar chemical shift solid-state NMR spectroscopy. JACS 120:8868–8874

    Article  Google Scholar 

  • Leman JK, Ulmschneider MB, Gray JJ (2014) Computational modeling of membrane proteins. Proteins Struct Funct Bioinf 83:1–24

    Article  Google Scholar 

  • Linge JP, Habeck M, Rieping W, Nilges M (2003) ARIA: automated NOE assignment and NMR structure calculation. Bioinformatics 19:315–316

    Article  Google Scholar 

  • Marassi FM, Opella SJ (2003) Simultaneous assignment and structure determination of a membrane protein from NMR orientational restraints. Protein Sci 12:403–411

    Article  Google Scholar 

  • McDonnell PA, Shon K, Kim Y, Opella SJ (1993) fd Coat protein structure in membrane environments. JMR 233:447–463

    Google Scholar 

  • Nevzorov AA, Opella SJ (2007) Selective averaging for high-resolution solid-state NMR spectroscopy of aligned samples. JMR 185:59–70

    Google Scholar 

  • O’Meara MJ, Leaver-Fay A, Tyka M, Stein A, Houlihan K, DiMaio F, Bradley P, Kortemme T, Baker D, Snoeyink J (2015) A Combined Covalent-Electrostatic Model of Hydrogen Bonding Improves Structure Prediction with Rosetta. J Chem Theory Comput 11:609–622

    Article  Google Scholar 

  • Opella SJ, Marassi FM, Gesell JJ, Valente AP, Kim Y, Oblatt-Montal M, Montal M (1999) Structures of the M2 channel-lining segments from the nicotinic acetylcholine and NMDA receptors by NMR spectroscopy. Nat Struct Mol Biol 6:374

    Article  Google Scholar 

  • Rohl CA, Strauss CEM, Misura KMS, Baker D (2004) Protein structure prediction using Rosetta. Methods Enzymol 383:66–93

    Article  Google Scholar 

  • Ruan K, Briggman KB, Tolman JR (2008) De novo determination of internuclear vector orientations from residual dipolar coupling measured in three independent alignment media. J Biomol NMR 41:61–76

    Article  Google Scholar 

  • Saito H, Ando I, Ramamoorthy A (2010) Chemical shift tensor—the heart of NMR: insights into biological aspects of proteins. Prog Nucl Magn Reson Spectrosc 57:181–228

    Article  Google Scholar 

  • Schwieters CD, Kuszewski JJ, Tjandra N, Clore GM (2003) The Xplor-NIH NMR molecular structure determination package. JMR 160:65–73

    Google Scholar 

  • Sharma M, Yi M, Dong H, Qin H, Peterson E, Busath DD, Cross TA (2010) Insight into the mechanism of the influenza A proton channel from a structure ina lipid bilayer. Science 330:509–512

    Article  ADS  Google Scholar 

  • Shen Y, Delaglio F, Cornilescu G, Bax A (2009) TALOS+: a hybrid method for predicting protein backbone torsion angles from NMR chemical shifts. J Biomol NMR 44:213–223

    Article  Google Scholar 

  • Sinha N, Grant CV, Park SH, Brown JM, Opella SJ (2007) Triple resonance experiments for aligned sample solid-state NMR of 13C and 15N labeled proteins. J Magn Reson 186:51–64

    Article  ADS  Google Scholar 

  • Spera S, Bax A (1991) Empirical correlation between protein backbone conformation and Ca and Q8 13C nuclear magnetic resonance chemical shifts. J Am Chem Soc 113:5490–5492

    Article  Google Scholar 

  • Stewart PL, Valentine KG, Opella SJ (1987) Structural analysis of solid-state NMR measurements of peptides and proteins. JMR 71:45–61

    Google Scholar 

  • Stewart PL, Tycko R, Opella SJ (1988) Peptide backbone conformation by solid-state nuclear magnetic resonance spectroscopy. J Chem Soc 84:3803–3819

    Google Scholar 

  • Thiriot DS, Nevzorov AA, Opella SJ (2004) Structural basis of the temperature transition of Pf1 bacteriophage. Protein Sci 14:1064–1070

    Article  Google Scholar 

  • Tian Y, Schwieters CD, Opella SJ, Marassi FM (2014) A practical implicit solvent potential for NMR structure calculation. J Magn Reson 243:54–64

    Article  ADS  Google Scholar 

  • Tian Y, Schwieters CD, Opella SJ, Marassi FM (2017) High quality NMR structures: a new force field with implicit water and membrane solvation for Xplor-NIH. J Biomol NMR 67:35–49

    Article  Google Scholar 

  • Traaseth NJ, Buffy JJ, Zamoon J, Veglia G (2006) Structural dynamics and topology of phospholamban in oriented lipid bilayers using multidimensional solid-state NMR. Biochemistry 45:13827–13834

    Article  Google Scholar 

  • Traaseth NJ, Shi L, Verardi R, Mullen DG, Barany G, Veglia G (2009) Structure and topology of monomeric phospholamban in lipid membranes determined by a hybrid solution and solid-state NMR approach. Proc Natl Acad Sci 106:10165–10170

    Article  ADS  Google Scholar 

  • Valafar H, Prestegard JH (2004) REDCAT: a residual dipolar coupling analysis tool. JMR 167:228–241

    Google Scholar 

  • Verardi R, Shi L, Traaseth NJ, Walsh N, Veglia G (2011) Structural topology of phospholamban pentamer in lipid bilayers by a hybrid solution and solid-state NMR method. Proc Natl Acad Sci 108:9101–9106

    Article  ADS  Google Scholar 

  • Wang J, Kim S, Kovacs F, Cross TA (2001) Structure of the transmembrane region of the M2 protein H+ channel. Protein Sci 10:2241–2250

    Article  Google Scholar 

  • Wu CH, Ramamoorthy A, Opella SJ (1994) High-resolution heteronuclear dipolar solid-state NMR spectroscopy. JMR 109:270–272

    Google Scholar 

  • Yamamoto K, Durr UH, Xu J, Im SC, Waskell L, Ramamoorthy A (2013) Dynamic interaction between membrane-bound full-length cytochrome P450 and cytochrome b 5 observed by solid-state NMR spectroscopy. Scientific Rep 3:2538

    Article  Google Scholar 

  • Yang J, Kulkarni K, Manolaridis I, Zhang Z, Dodd RB, Mas-Droux C, Barford D (2011) Mechanism of isoprenylcysteine carboxyl methylation from the crystal structure of the integral membrane methyltransferase ICMT. Mol Cell 44:997–1004

    Article  Google Scholar 

  • Yarov-Yarovoy V, Schonbrun J, Baker D (2005) Multipass membrane protein structure prediction using Rosetta. Prot Struct Funct Bioinf 62:1010–1025

    Article  Google Scholar 

  • Yin Y, Nevzorov AA (2011) Structure determination in “shiftless” solid state NMR of oriented protein samples. JMR 212:64–73

    Google Scholar 

Download references

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. 1508400 and in part by the Army Research Office Grant W911NF1810363.

Author information

Authors and Affiliations

  1. Department of Chemistry, North Carolina State University, 2620 Yarbrough Drive, Raleigh, NC, 27695-8204, USA

    Joel Lapin & Alexander A. Nevzorov

Authors
  1. Joel Lapin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexander A. Nevzorov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alexander A. Nevzorov.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lapin, J., Nevzorov, A.A. Validation of protein backbone structures calculated from NMR angular restraints using Rosetta. J Biomol NMR 73, 229–244 (2019). https://doi.org/10.1007/s10858-019-00251-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10858-019-00251-7

Keywords

Search

Navigation