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Improved molecular replacement by density- and energy-guided protein structure optimization


Molecular replacement1,2,3,4 procedures, which search for placements of a starting model within the crystallographic unit cell that best account for the measured diffraction amplitudes, followed by automatic chain tracing methods5,6,7,8, have allowed the rapid solution of large numbers of protein crystal structures. Despite extensive work9,10,11,12,13,14, molecular replacement or the subsequent rebuilding usually fail with more divergent starting models based on remote homologues with less than 30% sequence identity. Here we show that this limitation can be substantially reduced by combining algorithms for protein structure modelling with those developed for crystallographic structure determination. An approach integrating Rosetta structure modelling with Autobuild chain tracing yielded high-resolution structures for 8 of 13 X-ray diffraction data sets that could not be solved in the laboratories of expert crystallographers and that remained unsolved after application of an extensive array of alternative approaches. We estimate that the new method should allow rapid structure determination without experimental phase information for over half the cases where current methods fail, given diffraction data sets of better than 3.2 Å resolution, four or fewer copies in the asymmetric unit, and the availability of structures of homologous proteins with >20% sequence identity.

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Figure 1: Examples of improvement in electron density and model quality.
Figure 2: Method comparison.
Figure 3: Comparison of the effectiveness of model diversification using Rosetta and simulated annealing.

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  1. Rossmann, M. G. The Molecular Replacement Method (Gordon & Breach, 1972)

    Google Scholar 

  2. McCoy, A. J. et al. Phaser crystallographic software. J. Appl. Cryst. 40, 658–674 (2007)

    Article  CAS  Google Scholar 

  3. Brünger, A. T. et al. Crystallography & NMR system: a new software system for macromolecular structure determination. Acta Crystallogr. D 54, 905–921 (1998)

    Article  Google Scholar 

  4. Vagin, A. & Teplyakov, A. MOLREP: an automated program for molecular replacement. J. Appl. Cryst. 30, 1022–1025 (1997)

    Article  CAS  Google Scholar 

  5. Langer, G., Cohen, S. X., Lamzin, V. S. & Perrakis, A. Automated macromolecular model building for X-ray crystallography using ARP/wARP version 7. Nature Protocols 3, 1171–1179 (2008)

    Article  CAS  Google Scholar 

  6. Terwilliger, T. C. et al. Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard. Acta Crystallogr. D 64, 61–69 (2008)

    Article  CAS  Google Scholar 

  7. DePristo, M. A., de Bakker, P. I. W., Johnson, R. J. K. & Blundell, T. L. Crystallographic refinement by knowledge-based exploration of complex energy landscapes. Structure 13, 1311–1319 (2005)

    Article  CAS  Google Scholar 

  8. Cowtan, K. The Buccaneer software for automated model building. Acta Crystallogr. D 62, 1002–1011 (2006)

    Article  Google Scholar 

  9. Schwarzenbacher, R., Godzik, A., Grzechnik, S. K. & Jaroszewski, L. The importance of alignment accuracy for molecular replacement. Acta Crystallogr. D 60, 1229–1236 (2004)

    Article  Google Scholar 

  10. Rodríguez, D. D. et al. Crystallographic ab initio protein structure solution below atomic resolution. Nature Methods 6, 651–653 (2009)

    Article  Google Scholar 

  11. Suhre, K. & Sanejouand, Y. H. On the potential of normal-mode analysis for solving difficult molecular-replacement problems. Acta Crystallogr. D 60, 796–799 (2004)

    Article  Google Scholar 

  12. Qian, B. et al. High-resolution structure prediction and the crystallographic phase problem. Nature 450, 259–264 (2007)

    Article  ADS  CAS  Google Scholar 

  13. Schröder, G., Levitt, M. & Brünger, A. T. Super-resolution biomolecular crystallography with low-resolution data. Nature 464, 1218–1222 (2010)

    Article  ADS  Google Scholar 

  14. Brünger, A. T., Kuriyan, J. & Karplus, M. Crystallographic R factor refinement by molecular dynamics. Science 235, 458–460 (1987)

    Article  ADS  Google Scholar 

  15. Raman, S. et al. NMR structure determination for larger proteins using backbone-only data. Science 327, 1014–1018 (2010)

    Article  ADS  CAS  Google Scholar 

  16. Das, R. & Baker, D. Macromolecular modeling with Rosetta. Annu. Rev. Biochem. 77, 363–382 (2008)

    Article  CAS  Google Scholar 

  17. Brünger, A. T. Free R value: a novel statistical quantity for assessing the accuracy of crystal structures. Nature 355, 472–475 (1992)

    Article  ADS  Google Scholar 

  18. Söding, J. Protein homology detection by HMM–HMM comparison. Bioinformatics 21, 951–960 (2005)

    Article  Google Scholar 

  19. Schröder, G. F., Brunger, A. T. & Levitt, M. Combining efficient conformational sampling with a deformable elastic network model facilitates structure refinement at low resolution. Structure 15, 1630–1641 (2007)

    Article  Google Scholar 

  20. Brünger, A. T. Extension of molecular replacement: a new search strategy based on Patterson correlation refinement. Acta Crystallogr. A 46, 46–57 (1990)

    Article  Google Scholar 

  21. Brünger, A. T., Karplus, M. & Petsko, G. A. Crystallographic refinement by simulated annealing: application to crambin. Acta Crystallogr. A 45, 50–61 (1989)

    Article  Google Scholar 

  22. Read, R. J. Improved Fourier coefficients for maps using phases from partial structures with errors. Acta Crystallogr. A 42, 140–149 (1986)

    Article  Google Scholar 

  23. Vitkup, D., Melamud, E., Moult, J. & Sander, C. Completeness in structural genomics. Nature Struct. Biol. 8, 559–566 (2001)

    Article  CAS  Google Scholar 

  24. Canutescu, A. & Dunbrack, R. Cyclic coordinate descent: a new algorithm for loop closure in protein modeling. Protein Sci. 12, 963–972 (2003)

    Article  CAS  Google Scholar 

  25. DiMaio, F., Tyka, M. D., Baker, M. L., Chiu, W. & Baker, D. Refinement of protein structures into low-resolution density maps using Rosetta. J. Mol. Biol. 392, 181–190 (2009)

    Article  CAS  Google Scholar 

  26. André, I., Bradley, P., Wang, C. & Baker, D. Prediction of the structure of symmetrical protein assemblies. Proc. Natl Acad. Sci. USA 104, 17656–17661 (2007)

    Article  ADS  Google Scholar 

  27. Weis, W. I., Brünger, A. T., Skehel, J. J. & Wiley, D. D. Refinement of the influenza virus hemagglutinin by simulated annealing. J. Mol. Biol. 212, 737–761 (1990)

    Article  CAS  Google Scholar 

  28. Abe, H., Braun, W., Noguti, T. & Go¯, N. Rapid calculation of first and second derivatives of conformational energy with respect to dihedral angles for proteins general recurrent equations. Comput. Chem. 8, 239–247 (1984)

    Article  CAS  Google Scholar 

  29. Eswar, N. et al. Comparative protein structure modeling with MODELLER. Curr. Protoc. Bioinform. (Suppl.) 15, 5.6 10.1002/0471250953.bi0506s15. (2006)

    Article  Google Scholar 

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R.J.R., T.C.T. and D.B. thank the NIH (5R01GM092802), the Wellcome Trust (R.J.R.), and HHMI (D.B.) for funding this research. F.D. acknowledges the NIH (P41RR002250) and HHMI. D.F. and A.A. acknowledge support from the Israel Science Foundation. G.O. thanks DK Molecular Enzymology (FWF-project W901) and the Austrian Science Fund (FWF-project P19858). The work of A.W. was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. H.I. acknowledges support from the academy of Finland (1131413). S.M.V. was supported by a grant from the Protein Structure Initiative of National Institute of General Medical Sciences (U54 GM074958). The work of P.R.P. at Argonne National Laboratory was supported by the US Department of Energy’s Office of Science, Biological and Environmental Research GTL programme under contract DE-AC02-06CH11357. We thank all members of the JCSG for their general contributions to the protein production and structural work. The JCSG is supported by the NIH, National Institutes of General Medical Sciences, Protein Structure Initiative (U54 GM094586 and GM074898).

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Authors and Affiliations



F.D., T.C.T., R.J.R. and D.B. developed the methods described in the manuscript; F.D., T.C.T., R.J.R., A.W. and D.B wrote the paper. A.W., G.O., U.W., E.V., A.A., D.F., H.L.A., D.D., S.M.V., H.I. and P.R.P. provided the data and refined one or more structures to completion.

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Correspondence to Thomas C. Terwilliger or David Baker.

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The authors declare no competing financial interests.

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DiMaio, F., Terwilliger, T., Read, R. et al. Improved molecular replacement by density- and energy-guided protein structure optimization. Nature 473, 540–543 (2011).

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