Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling

Nature Methods volume 6, pages 551–552 (2009)Cite this article

To the Editor: Proteins exploit the conformational variability of loop regions to carry out diverse biological tasks including molecular recognition and signal transduction. New algorithms to engineer these functions by combining loop building and sequence design therefore have enormous practical applications but require high-resolution 'loop reconstruction': the modeling of protein loop conformations, given the amino acid sequence. Loop reconstruction in protein design may be simplified conceptually by restricting changes to the functional loop regions. However, despite progress in loop prediction methods1,2, design applications are limited by the difficulty in modeling purely local conformational moves and by the need for advances in sampling and evaluating loop conformations.

We found that KIC substantially improves model accuracy over the standard loop building method in Rosetta, which combines insertion of torsion segments from homologous proteins and a numerical closure technique6. We generated 1,000 models by the KIC method and compared its performance to the standard Rosetta method with the same number of Monte Carlo steps on twenty-five 12-residue protein loops (dataset 1; ref. 7). For each protein, we computed the root mean squared (r.m.s.) deviation of the backbone atoms of the best scoring loop model to the crystallographic loop, after superimposing the non-loop regions of the model onto the crystal structure. The KIC protocol frequently sampled regions of conformational space that were <1.0 Å from the crystallographic loop, which were not sampled by the standard Rosetta method (Fig. 1b). In the majority of cases (15/25), the best-scoring models were very close to the crystallographic loop conformation (Fig. 1b, c). Over the entire 25-loop set, KIC improved the median accuracy to 0.8 Å r.m.s. deviation from 2.0 Å r.m.s. deviation when we applied the standard Rosetta method (Supplementary Table 1). As both methods use the same scoring function, these results suggest that KIC increased accuracy by improved conformational sampling (although sampling and scoring errors cannot be considered entirely independently as scoring guides the simulation trajectories; see Supplementary Discussion, Supplementary Tables 1–8, and Supplementary Figs. 3,4 for additional analysis of method performance and error sources). The standard method required ∼280 central processing unit hours per protein, and KIC required ∼320.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Loop reconstruction with KIC.
Figure 2: Performance of the KIC loop reconstruction protocol.

References

  1. Sellers, B.D. et al. Proteins 72, 959–971 (2008).

    Article  CAS  Google Scholar 

  2. Felts, A.K. et al. J. Chem. Theory Comput. 4, 855–868 (2008).

    Article  CAS  Google Scholar 

  3. Go, N. & Scheraga, H.A. Macromolecules 3, 178–187 (1970).

    Article  CAS  Google Scholar 

  4. Coutsias, E.A. et al. Int. J. Quantum Chem. 106, 176–189 (2006).

    Article  CAS  Google Scholar 

  5. Schueler-Furman, O., Wang, C., Bradley, P., Misura, K. & Baker, D. Science 310, 638–642 (2005).

    Article  CAS  Google Scholar 

  6. Canutescu, A.A. & Dunbrack, R.L. Jr . Protein Sci. 12, 963–972 (2003).

    Article  CAS  Google Scholar 

  7. Wang, C., Bradley, P. & Baker, D. J. Mol. Biol. 373, 503–519 (2007).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank D. Baker and A. Sali for valuable comments, and B. Sellers and M. Jacobson for sharing data and for helpful discussions. This work was supported by grants from the US National Institutes of Health to T.K. (PN2-EY016525) and E.A.C (R01-GM08171), the University of California Lab Research Program (T.K.), and a PhRMA Foundation Predoctoral Fellowship (D.J.M.).

Author information

Authors and Affiliations

  1. Graduate Program in Bioinformatics and Computational Biology,

    Daniel J Mandell & Tanja Kortemme

  2. California Institute for Quantitative Biosciences, University of California San Francisco, San Francisco, California, USA

    Daniel J Mandell & Tanja Kortemme

  3. Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico, USA

    Evangelos A Coutsias

  4. Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, USA

    Tanja Kortemme

Authors
  1. Daniel J Mandell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Evangelos A Coutsias
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tanja Kortemme
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tanja Kortemme.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4, Supplementary Tables 1–8, Supplementary Methods, Supplementary Discussion (PDF 3700 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mandell, D., Coutsias, E. & Kortemme, T. Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling. Nat Methods 6, 551–552 (2009). https://doi.org/10.1038/nmeth0809-551

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth0809-551

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing