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Automated protein model building combined with iterative structure refinement

Abstract

In protein crystallography, much time and effort are often required to trace an initial model from an interpretable electron density map and to refine it until it best agrees with the crystallographic data. Here, we present a method to build and refine a protein model automatically and without user intervention, starting from diffraction data extending to resolution higher than 2.3 Å and reasonable estimates of crystallographic phases. The method is based on an iterative procedure that describes the electron density map as a set of unconnected atoms and then searches for protein-like patterns. Automatic pattern recognition (model building) combined with refinement, allows a structural model to be obtained reliably within a few CPU hours. We demonstrate the power of the method with examples of a few recently solved structures.

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Figure 1
Figure 2: A gallery of some of the structures automatically built and refined with warpNtrace.
Figure 3: Automatic building of Leishmanolysin.
Figure 4: Number of traced residues and the crystallographic R-factor as a function of warpNtrace cycles on the example of leishmanolysin.

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Acknowledgements

The authors are extremely grateful to K. Wilson and Z. Dauter for many useful comments and discussions. We also acknowledge the numerous test users for their efforts in using (and tuning) the ARP/wARP software and for making available brief results (presented in Table 1). Many thanks to our colleagues for critical reading of the manuscript. 'warpNtrace' is a part of the ARP/wARP suite, http://www.embl-hamburg.de/ARP (thanks to C. Blessing and T. Eriksson for the www setup and useful suggestions). The authors and the European Molecular Biology Laboratory copyright the software, which is available to the community.

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Correspondence to Anastassis Perrakis.

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Perrakis, A., Morris, R. & Lamzin, V. Automated protein model building combined with iterative structure refinement . Nat Struct Mol Biol 6, 458–463 (1999). https://doi.org/10.1038/8263

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