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Improving molecular replacement with morphing

Improving molecular replacement with morphing. NECAT Workshop on Advances in Moderate to Low Resolution Phasing and Refinement Sept. 19, 2011, Rockefeller University. Tom Terwilliger (Los Alamos National Laboratory) Randy Read (Cambridge University)

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Improving molecular replacement with morphing

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  1. Improving molecular replacement with morphing NECAT Workshop on Advances in Moderate to Low Resolution Phasing and Refinement Sept. 19, 2011, Rockefeller University Tom Terwilliger (Los Alamos National Laboratory) Randy Read (Cambridge University) Paul Adams (Lawrence Berkeley National Laboratory) Axel Brunger (Stanford University)

  2. The challenge: Crystal structure determination from a distant homology model A key problem: Correctly-placed model is too different from target to yield useful electron density maps

  3. The challenge: Crystal structure determination from a distant homology model A solution: Morphing (distortion) of the template using a density map to make it more like the target structure

  4. Related structures often have high local similarity ag9603; approximate NMR model as template in pink

  5. Related structures often have high local similarity XMRV PR, 30% identity template (2hs1) in blue

  6. Related structures often have high local similarity cab55348 32% identical template (Cip2) in blue

  7. Taking advantage of local similarities of homologous structures • Rigid-body refinement of segments • Fragment searches (FFFEAR, ESSENS) • DEN or jelly-body refinement • Rosetta modeling • Morphing

  8. Morphing • Local structures may superimpose very closely • The position of a large group of atoms can be identified accurately with a poor map • Relationship between structures may be a simple distortion

  9. A challenging morphing problem: How can we use this map to identify the shifts needed? cab55342: final model green3PIC (32% identity) in blue

  10. Standard refinement does not move the structure very much.. cab55342: 3PIC (32% identity) in blueRefined template in orange

  11. Steps in morphing • A. Identify local translation to apply to one Ca atom and nearby atoms • B. Smooth the local translations in window of 10 residues • C. Apply the smoothed translation to all atoms in the residue

  12. Identify local translation to apply to one Ca atom and nearby atoms cab55342: final model (green)3PIC (32% identity, blue)prime-and-switch map (blue)

  13. Identify local translation to apply to one Ca atom and nearby atomsModel density in red cab55342:3PIC (32% identity, blue) R181Ca

  14. Identify local translation to apply to one Ca atom and nearby atomsModel density in red cab55342:3PIC (32% identity, blue)

  15. Identify local translation to apply to one Ca atom and nearby atoms Model density offset to match map cab55342:3PIC (32% identity, blue)

  16. Identify local translation to apply to one Ca atom and nearby atoms Model density offset to match map cab55342:3PIC (32% identity, blue)

  17. Smooth offset over nearby residues and apply to all atoms in the residue cab55342:3PIC (32% identity, blue)Morphed model (yellow) R181Ca Geometry within each residue is maintained

  18. Refine morphed model 3PIC (32% identity) in blueMorphed model (yellow)Refined morphed model (orange) R181Ca

  19. Get new map Repeat morphing 6 times... 3PIC (32% identity) blue Refined morphed model (yellow)prime-and-switch map (purple)

  20. Autobuilding after morphing

  21. Autobuilding starting with morphed model cab55342Autobuild modelDensity-modified map

  22. Autobuilding starting with morphed model cab55342Morphed model (yellow)Autobuild model (green)

  23. Autobuilding cab55342 starting with morphed model 3PIC (32% identity, blue) Morphed model (yellow)Autobuild model (green)

  24. What is the best map for morphing?Test structures from DiMaio et al. (2011). Improving molecular replacement by density and energy guided protein structure optimization. Nature 473, 540-543.(Structures that could be solved by AutoBuild excluded)

  25. Comparison of maps for morphing

  26. Comparing morphing and refinement

  27. What to use as a baseline?Major improvements in phenix.refine since 2010

  28. Extensive refinement can be effective

  29. Morphing compared to refinement

  30. Morphing compared to refinement

  31. Tests of morphing with a series of templates with varying similarity to target structure

  32. Morphing on a series of templates

  33. Tests of Autobuilding after morphingComparison with phenix.mr_rosetta

  34. Morphing combined with autobuilding

  35. Morphing combined with autobuilding

  36. Morphing combined with autobuilding

  37. Morphing combined with autobuilding

  38. Applications for morphingMolecular replacement templates that close but distortedBuilding models into experimental electron density maps when a distant related structure is available

  39. Thanks for data to... • Alex Wlodawer, NCI (XMRV PR) • Herb Axelrod, Debanu Das, JCSG (hp3342) • Gustav Oberdorfer, Ulrike Wagner, Univ. of Graz • Eugene Valkov, Univ. of Cambridge • Assaf Alon, Deborah Fass, Weizmann Institute of Science • Sergey M. Vorobiev, NESG • Hideo Iwai, Univ. of Helsinki • P. Raj Pokkuluri, Argonne National Laboratory

  40. Scripts and documentation for phenix.morph_model are available at... • http://www.phenix-online.org

  41. The PHENIX Project Lawrence Berkeley Laboratory Paul Adams, Ralf Grosse-Kunstleve, Pavel Afonine, Nat Echols, Nigel Moriarty, Jeff Headd, Nicholas Sauter, Peter Zwart Los Alamos National Laboratory Tom Terwilliger, Li-Wei Hung Duke University Randy Read, Airlie McCoy, Gabor Bunkoczi, Rob Oeffner Jane & David Richardson, Vincent Chen, Chris Williams, Bryan Arendall, Swati Jain, Bradley Hintze Cambridge University An NIH/NIGMS funded Program Project

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