Skip to main content
SpringerLink
Log in

PPM_One: a static protein structure based chemical shift predictor

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

Abstract

We mined the most recent editions of the BioMagResDataBank and the protein data bank to parametrize a new empirical knowledge-based chemical shift predictor of protein backbone atoms using either a linear or an artificial neural network model. The resulting chemical shift predictor PPM_One accepts a single static 3D structure as input and emulates the effect of local protein dynamics via interatomic steric contacts. Furthermore, the chemical shift prediction was extended to most side-chain protons and it is found that the prediction accuracy is at a level allowing an independent assessment of stereospecific assignments. For a previously established set of test proteins some overall improvement was achieved over current top-performing chemical shift prediction programs.

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

Similar content being viewed by others

References

  • Berjanskii M, Wishart DS (2006) NMR: prediction of protein flexibility. Nat Protoc 1:683–688

    Article  Google Scholar 

  • Berman HM et al (2000) The protein data bank. Nucleic Acids Res 28:235–242

    Article  ADS  Google Scholar 

  • Borowski P (2012) Conformational analysis of the chemical shifts for molecules containing diastereotopic methylene protons. J Magn Reson 214:1–9

    Article  ADS  Google Scholar 

  • Cavalli A, Salvatella X, Dobson CM, Vendruscolo M (2007) Protein structure determination from NMR chemical shifts. Proc Natl Acad Sci USA 104:9615–9620

    Article  ADS  Google Scholar 

  • Haigh CW, Mallion RB (1972) New tables of ring current shielding in proton magnetic-resonance. Org Magn Reson 4:203

    Article  Google Scholar 

  • Haigh CW, Mallion RB (1979) Ring current theories in nuclear magnetic-resonance. Prog Nucl Magn Reson Spectrosc 13:303–344

    Article  Google Scholar 

  • Han B, Liu YF, Ginzinger SW, Wishart DS (2011) SHIFTX2: significantly improved protein chemical shift prediction. J Biomol NMR 50:43–57

    Article  Google Scholar 

  • Kohlhoff KJ, Robustelli P, Cavalli A, Salvatella X, Vendruscolo M (2009) Fast and accurate predictions of protein NMR chemical shifts from interatomic distances. J Am Chem Soc 131:13894

    Article  Google Scholar 

  • Lehtivarjo J, Hassinen T, Korhonen SP, Perakyla M, Laatikainen R (2009) 4D prediction of protein H-1 chemical shifts. J Biomol NMR 45:413–426

    Article  Google Scholar 

  • Lehtivarjo J, Tuppurainen K, Hassinen T, Laatikainen R, Perakyla M (2012) Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction. J Biomol NMR 52:257–267

    Article  Google Scholar 

  • Li DW, Brüschweiler R (2010) NMR-based protein potentials. Angew Chem Int Ed 49:6778–6780

    Article  Google Scholar 

  • Li DW, Brüschweiler R (2011) Iterative optimization of molecular mechanics force fields from NMR data of full-length proteins. J Chem Theory Comput 7:1773–1782

    Article  Google Scholar 

  • Li DW, Brüschweiler R (2009) All-atom contact model for understanding protein dynamics from crystallographic B-factors. Biophys J 96:3074–3081

    Article  Google Scholar 

  • Li DW, Brüschweiler R (2012) PPM: a side-chain and backbone chemical shift predictor for the assessment of protein conformational ensembles. J Biomol NMR 54:257–265

    Article  Google Scholar 

  • Markwick PRL, Cervantes CF, Abel BL, Komives EA, Blackledge M, McCammon JA (2010) Enhanced conformational space sampling improves the prediction of chemical shifts in proteins. J Am Chem Soc 132:1220

    Article  Google Scholar 

  • McConnell HM (1957) Theory of nuclear magnetic shielding in molecules. 1. Long-range dipolar shielding of protons. J Chem Phys 27:226–229

    Article  ADS  Google Scholar 

  • Meiler J (2003) PROSHIFT: protein chemical shift prediction using artificial neural networks. J Biomol NMR 26:25–37

    Article  Google Scholar 

  • Neal S, Nip AM, Zhang HY, Wishart DS (2003) Rapid and accurate calculation of protein H-1, C-13 and N-15 chemical shifts. J Biomol NMR 26:215–240

    Article  Google Scholar 

  • Nilges M, Clore GM, Gronenborn AM (1990) 1H-NMR stereospecific assignments by conformational data-base searches. Biopolymers 29:813–822

    Article  Google Scholar 

  • Osapay K, Case DA (1991) A new analysis of proton chemical-shifts in proteins. J Am Chem Soc 113:9436–9444

    Article  Google Scholar 

  • Robustelli P, Stafford KA, Palmer AG (2012) Interpreting protein structural dynamics from NMR chemical shifts. J Am Chem Soc 134:6365–6374

    Article  Google Scholar 

  • Rosato A et al (2012) Blind testing of routine, fully automated determination of protein structures from NMR data. Structure 20:227–236

    Article  Google Scholar 

  • Sahakyan AB, Vranken WF, Cavalli A, Vendruscolo M (2011a) Structure-based prediction of methyl chemical shifts in proteins. J Biomol NMR 50:331–346

    Article  Google Scholar 

  • Sahakyan AB, Vranken WF, Cavalli A, Vendruscolo M (2011b) Using side-chain aromatic proton chemical shifts for a quantitative analysis of protein structures. Angew Chem Int Ed 50:9620–9623

    Article  Google Scholar 

  • Shen Y, Bax A (2007) Protein backbone chemical shifts predicted from searching a database for torsion angle and sequence homology. J Biomol NMR 38:289–302

    Article  Google Scholar 

  • Shen Y, Bax A (2010) SPARTA plus: a modest improvement in empirical NMR chemical shift prediction by means of an artificial neural network. J Biomol NMR 48:13–22

    Article  Google Scholar 

  • Shen Y, Bax A (2013) Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks. J Biomol NMR 56:227–241

    Article  Google Scholar 

  • Shen Y et al (2008) Consistent blind protein structure generation from NMR chemical shift data. Proc Natl Acad Sci USA 105:4685–4690

    Article  ADS  Google Scholar 

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

    Article  Google Scholar 

  • Shen Y, Vernon R, Baker D, Bax A (2009b) De novo protein structure generation from incomplete chemical shift assignments. J Biomol NMR 43:63–78

    Article  Google Scholar 

  • Ulrich EL et al (2008) BioMagResBank. Nucleic Acids Res 36:D402–D408

    Article  Google Scholar 

  • Wang YJ, Jardetzky O (2002) Probability-based protein secondary structure identification using combined NMR chemical-shift data. Protein Sci 11:852–861

    Article  Google Scholar 

  • Williamson MP, Asakura T (1992) The application of 1H NMR chemical shift calculations to diastereotopic groups in proteins. FEBS Lett 302:185–188

    Article  Google Scholar 

  • Wishart DS, Case DA (2001) Use of chemical shifts in macromolecular structure determination. Method Enzymol 338:3–34

    Article  Google Scholar 

  • Wishart DS, Sykes BD (1994) The C-13 chemical-shift index—a simple method for the identification of protein secondary structure using C-13 chemical-shift data. J Biomol NMR 4:171–180

    Google Scholar 

  • Wishart DS, Watson MS, Boyko RF, Sykes BD (1997) Automated H-1 and C-13 chemical shift prediction using the BioMagResBank. J Biomol NMR 10:329–336

    Article  Google Scholar 

  • Wishart DS, Arndt D, Berjanskii M, Tang P, Zhou J, Lin G (2008) CS23D: a web server for rapid protein structure generation using NMR chemical shifts and sequence data. Nucleic Acids Res 36:W496–W502

    Article  Google Scholar 

  • Xu XP, Case DA (2001) Automated prediction of 15 N, 13Calpha, 13Cbeta and 13C′ chemical shifts in proteins using a density functional database. J Biomol NMR 21:321–333

    Article  Google Scholar 

  • Xu XP, Case DA (2002) Probing multiple effects on 15 N, 13C alpha, 13C beta, and 13C′ chemical shifts in peptides using density functional theory. Biopolymers 65:408–423

    Article  Google Scholar 

  • Xue Y, Ward JM, Yuwen TR, Podkorytov IS, Skrynnikov NR (2012) Microsecond time-scale conformational exchange in proteins: using Long molecular dynamics trajectory to simulate NMR relaxation dispersion data. J Am Chem Soc 134:2555–2562

    Article  Google Scholar 

  • Zhang F, Brüschweiler R (2002) Contact model for the prediction of NMR N–H order parameters in globular proteins. J Am Chem Soc 124:12654–12655

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the NSF (Grant MCB 1360966). R.B. is an Ohio Research Scholar.

Author information

Authors and Affiliations

  1. Campus Chemical Instrument Center, The Ohio State University, Columbus, OH, 43210, USA

    Dawei Li & Rafael Brüschweiler

  2. Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, 43210, USA

    Rafael Brüschweiler

Authors
  1. Dawei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rafael Brüschweiler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rafael Brüschweiler.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 186 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, D., Brüschweiler, R. PPM_One: a static protein structure based chemical shift predictor. J Biomol NMR 62, 403–409 (2015). https://doi.org/10.1007/s10858-015-9958-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10858-015-9958-z

Keyword

Search

Navigation