Improved crystallographic structures using extensive combinatorial refinement.

Identifying errors and alternate conformers and modeling multiple main-chain conformers in poorly ordered regions are overarching problems in crystallographic structure determination that have limited automation efforts and structure quality. Here, we show that implementation of a full factorial designed set of standard refinement approaches, termed ExCoR (Extensive Combinatorial Refinement), significantly improves structural models compared to the traditional linear tree approach, in which individual algorithms are tested linearly and are only incorporated if the model improves. ExCoR markedly improved maps and models and reveals building errors and alternate conformations that were masked by traditional refinement approaches. Surprisingly, an individual algorithm that renders a model worse in isolation could still be necessary to produce the best overall model, suggesting that model distortion allows escape from local minima of optimization target function, here shown to be a hallmark limitation of the traditional approach. ExCoR thus provides a simple approach to improving structure determination.

[1]  Martin Phillips,et al.  Toward the structural genomics of complexes: crystal structure of a PE/PPE protein complex from Mycobacterium tuberculosis. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Vincent Breton,et al.  PDB_REDO: automated re-refinement of X-ray structure models in the PDB , 2009, Journal of applied crystallography.

[3]  Gerard J Kleywegt,et al.  Separating model optimization and model validation in statistical cross-validation as applied to crystallography. , 2007, Acta crystallographica. Section D, Biological crystallography.

[4]  A. Brunger Free R value: a novel statistical quantity for assessing the accuracy of crystal structures. , 1992 .

[5]  Min Zhao,et al.  Coupling of Receptor Conformation and Ligand Orientation Determine Graded Activity , 2010, Nature chemical biology.

[6]  P. Zwart,et al.  Towards automated crystallographic structure refinement with phenix.refine , 2012, Acta crystallographica. Section D, Biological crystallography.

[7]  Randy J. Read,et al.  Phenix - a comprehensive python-based system for macromolecular structure solution , 2012 .

[8]  Axel T. Brunger,et al.  Phase Improvement by Multi-Start Simulated Annealing Refinement and Structure-Factor Averaging , 1998 .

[9]  Mark A Depristo,et al.  Crystallographic refinement by knowledge-based exploration of complex energy landscapes. , 2005, Structure.

[10]  Jay Painter,et al.  Electronic Reprint Biological Crystallography Optimal Description of a Protein Structure in Terms of Multiple Groups Undergoing Tls Motion Biological Crystallography Optimal Description of a Protein Structure in Terms of Multiple Groups Undergoing Tls Motion , 2005 .

[11]  Nathaniel Echols,et al.  The Phenix software for automated determination of macromolecular structures. , 2011, Methods.

[12]  Paul D. Adams,et al.  short communications Acta Crystallographica Section D Biological , 1998 .

[13]  S. McNicholas,et al.  Presenting your structures: the CCP4mg molecular-graphics software , 2011, Acta crystallographica. Section D, Biological crystallography.

[14]  Jay Painter,et al.  TLSMD web server for the generation of multi-group TLS models , 2006 .

[15]  Ankur Dhanik,et al.  Modeling discrete heterogeneity in X-ray diffraction data by fitting multi-conformers. , 2009, Acta crystallographica. Section D, Biological crystallography.

[16]  Paul D Adams,et al.  Modelling dynamics in protein crystal structures by ensemble refinement , 2012, eLife.

[17]  Randy J. Read,et al.  Overview of the CCP4 suite and current developments , 2011, Acta crystallographica. Section D, Biological crystallography.

[18]  Randy J. Read,et al.  Interpretation of ensembles created by multiple iterative rebuilding of macromolecular models , 2007, Acta crystallographica. Section D, Biological crystallography.

[19]  H. Ng,et al.  Automated electron‐density sampling reveals widespread conformational polymorphism in proteins , 2010, Protein science : a publication of the Protein Society.

[20]  David Baker,et al.  Protein Structure Prediction Using Rosetta , 2004, Numerical Computer Methods, Part D.

[21]  Michael Levitt,et al.  Super-resolution biomolecular crystallography with low-resolution data , 2010, Nature.

[22]  Randy J. Read,et al.  Dauter Iterative model building , structure refinement and density modification with the PHENIX AutoBuild wizard , 2007 .

[23]  Eric Blanc,et al.  Automated structure solution with autoSHARP. , 2007, Methods in molecular biology.

[24]  Nicholas Furnham,et al.  Knowledge-based real-space explorations for low-resolution structure determination. , 2006, Structure.

[25]  Vincent B. Chen,et al.  Correspondence e-mail: , 2000 .

[26]  A. W. Schüttelkopf,et al.  PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. , 2004, Acta crystallographica. Section D, Biological crystallography.

[27]  Randy J. Read,et al.  A New Generation of Crystallographic Validation Tools for the Protein Data Bank , 2011, Structure.

[28]  Serge X. Cohen,et al.  Automated macromolecular model building for X-ray crystallography using ARP/wARP version 7 , 2008, Nature Protocols.

[29]  G. Kleywegt Use of non-crystallographic symmetry in protein structure refinement. , 1996, Acta crystallographica. Section D, Biological crystallography.

[30]  Kevin Cowtan,et al.  research papers Acta Crystallographica Section D Biological , 2005 .

[31]  M. DePristo,et al.  Heterogeneity and inaccuracy in protein structures solved by X-ray crystallography. , 2004, Structure.

[32]  Randy J. Read,et al.  Application of DEN refinement and automated model building to a difficult case of molecular-replacement phasing: the structure of a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum , 2012, Acta crystallographica. Section D, Biological crystallography.

[33]  Z. Otwinowski,et al.  [20] Processing of X-ray diffraction data collected in oscillation mode. , 1997, Methods in enzymology.

[34]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[35]  Gert Vriend,et al.  Re-refinement from deposited X-ray data can deliver improved models for most PDB entries , 2009, Acta crystallographica. Section D, Biological crystallography.

[36]  Randy J. Read,et al.  Improved molecular replacement by density- and energy-guided protein structure optimization , 2011, Nature.

[37]  G. Kleywegt,et al.  Checking your imagination: applications of the free R value. , 1996, Structure.