ACA meeting July 2009 Highlights. Small Angle Scattering (X-rays, Neutrons) Don’t need.

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Presentation transcript:

ACA meeting July 2009 Highlights

Small Angle Scattering (X-rays, Neutrons) Don’t need crystals Can study small proteins or HUGE complexes –Maximum size –Radius of gyration –BUT, more is possible: With medium resolution scattering curves, can generate models of possible SHAPES and then on using restraints such as compactness and -ab initio Also can generate models of complexes when you have the component structures from X-ray or NMR, compare calculated & real scattering curves hamburg.de/ExternalInfo/Research/Sax/atsas-online/ hamburg.de/ExternalInfo/Research/Sax/atsas-online/ Two good refs: Svergun, J. Appl. Cryst. 2006, 40, s10 - s17 Hura et al., Nature Methods 2009, 6, 606 -,612

Some examples of SAS SARS polyproteins Whole virus 400 kD protein studied by combination of –SAXS, AUC, DLS Making SDS into a non-denaturing detergent by adding cosolvents - like MPD; studied a  -barrel membrane protein MPD SDS OH

Powder Diffraction from sub-micron crystals of PSI using a micro-jet Mark Hunter (grad. Student) with others at ALS Filter microcrystals to size of 500 nM (<1000 unit cells) Shoot through an aperture serially, collect scattering using long wavelength so can get e.g. 28 Angstrom curves Working on developing this method to higher resolution at ALS Ref: Shapiro DA, Chapman HN, Deponte D, Doak RB, Fromme P, Hembree G, Hunter M, Marchesini S, Schmidt K, Spence J, Starodub D, Weierstall U. Powder diffraction from a continuous microjet of submicrometer protein crystals. J Synchrotron Radiat Nov;15(Pt 6): Epub 2008 Oct 3.

Irimpan Mathews - SSRL Grow crystals directly in loops Nextal plates

Instrumentation Session Pilates Detector - Swiss Light Source –Single photon counter, solid state, not a multiwire –No “dark current” or read noise –Less point spread –4 ms dead time Can collect continuously; no shutter, reduces noise Fine phi slicing - also better for noise Commercialization of detector Dectris

Data Collection Diagnostics James Holton: –Discovering the Rules of Successful Protein Structure Determination with Simulated Diffraction Images Only 2% data collected at beamlines become good structural models - why? “MLSFOM” - tool to simulate diffraction while varying parameters such as: –Spot shape –Mosaic spread –Beam divergence –Spectral dispersion –Point spread function –Radiation damage –Crystal size –Detector & goniometer properties Calculates a Correlation Coefficient with the actual data & if get >0.5, then (e.g. MAD) probably solvable ~jamesh/powerpoint/ACA_2009.ppthttp://bl831.als.lbl.gov/ ~jamesh/powerpoint/ACA_2009.ppt

dataset exposure1.0s0.1s1.0s frames x R merge R anom I/sd I/sd (2.0 Ǻ) redundancy PADFPH FOM FOMDM CC(1H87) same total dose with high and low redundancy

dataset exposure1.0s0.1s1.0s frames x R merge 5.6%11.2%4.7% R anom 4.8%4.7% I/sd I/sd (2.0 Ǻ) redundancy PADFPH FOM FOMDM CC(1H87) same total dose with high and low redundancy

dataset exposure1.0s0.1s1.0s frames x R merge 5.6% 11.2% 4.7% R anom 4.8%4.7% I/sd I/sd (2.0 Ǻ) redundancy PADFPH FOM FOMDM CC(1H87) same total dose with high and low redundancy

dataset exposure1.0s0.1s1.0s frames x R merge 5.6% 11.2% 4.7% R anom 4.8%4.7% I/sd I/sd (2.0 Ǻ) redundancy PADFPH FOM FOMDM CC(1H87) same total dose with high and low redundancy