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Why are

This article discusses the challenges faced in solving protein structures and improving efficiency in beamline operation. Topics include data collection, overlaps, signal-to-noise ratio, radiation damage, and strategies to avoid failures. The importance of beamline operation efficiency and the correlation between data quality and phasing quality are also explored.

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Why are

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  1. Why are

  2. we not

  3. solving

  4. more

  5. struct

  6. tures?

  7. James Holton JMHolton@lbl.gov University of California San Francisco and Advanced Light Source Lawrence Berkeley National Laboratory Berkeley, CA 94720 USA This work was supported by contributions from the ALS 8.3.1 participating research team, a University of California Campus-Laboratory Collaboration Grant and grants from the National Institutes of Health: GM74929 and GM24485. Beamline 8.3.1 was funded by the National Science Foundation, the University of California, Berkeley, the University of California, San Francisco and Henry Wheeler. The Advanced Light Source is supported by the Director, Office of Science, Office of Basic Energy Sciences, Materials Sciences Division, of the US Department of Energy under contract No. DE-AC02-05CH11231 at Lawrence Berkeley National Laboratory.

  8. About 50 data sets (MAD,SAD or native) are collected for every PDB deposition Only one in 12 MAD/SAD datasets can be solved Failures are generally due to: Overlaps – run strategy! Site-specific damage - stay under ~5 MGy Insufficient signal-to-noise - need ΔFano> σ(ΔFano) Summary

  9. Beamline operation efficiency “representative” 8.3.1 user

  10. Structure Productivity ALS 8.3.1 in 2003

  11. USA Structure Productivity 28 operating US beamlines ~1011 ph/μm2 exposure limit ÷ 2x109 ph/μm2/s x 25% beamline operation efficiency ≈100,000 datasets/year ÷ 1324 str in 2003 ≈2% efficient Henderson (1990) biosync.sdsc.edu Jiang & R.M.Sweet (2004)

  12. Investigated withElvesAutomation Elves examine images and set-up data processing Elves run… mosflm scala solve mlphare dm arp/warp

  13. Investigated withElvesAutomation Apr 6 – 24 2003 at ALS 8.3.1

  14. Why do structures fail?

  15. Why do structures fail? Overlaps Signal to Noise Radiation Damage

  16. Avoiding Overlaps c c

  17. Is it real, or is it MLFSOM?Simulate diffraction experimentto test hypotheses

  18. MAD phasing simulations mlphare results Threshold of interpretability Correlation coefficient to correct model Anomalous signal to noise ratio

  19. Reduce Noise:minimize background scattering Se edge with detector at 100 mm Photons/s/pixel  7.5 3.8 2.5 1.9 1.5 1.2 1.1 Resolution (Ǻ)

  20. Increase Signal:use multiple crystals and incremental strategy incremental_strategy.com merged.mtz auto.mat

  21. e- + + e- + Interactions of x-rays with matter e- e- e- elasticscattering inelasticscattering Photoelectronemission Secondaryionization fluorescence

  22. Radiation Damage Lattice Damage Site-specific Damage

  23. Where do photons go? Protein 1A x-rays elastic scattering (6%) Transmitted (98%) beamstop inelastic scattering (7%) Photoelectric (87%) Re-emitted (99%) Absorbed (~0%) Re-emitted (~0%) Absorbed (99%) useful/absorbed energy: 7.3%

  24. x-rays cause sample expansion Protein crystalin oil after before 20% glycerol

  25. Data quality vs phasing quality Correlation coefficient 0 12 24 36 48 60 dose (MGy)

  26. Individual atoms decay at different rates Correlation coefficient to observed data 0 12 24 36 48 60 dose (MGy)

  27. peak 1.0 valley fraction unconverted 0.0

  28. 660%

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