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Advanced Light Source

Beamline staff Acknowledgments George Meigs Jane Tanamachi ALS Team

Acknowledgements PRT: Jamie Cate Center for Structure of Membrane Proteins Membrane Protein Expression Center II Center for HIV Accessory and Regulatory Complexes W. M. Keck Foundation Plexxikon, Inc. M D Anderson CRC University of California Berkeley University of California San Francisco National Science Foundation University of California Campus-Laboratory Collaboration Grant 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. Ken Frankel Chris Neilson Michael Blum Joe Ferrara

Elves examine images and set-up data processing Elves run… mosflm scala solve mlphare dm arp/warp Elven Automation

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

Elven Automation Elves examine images and set-up data processing Elves run… mosflm scala solve mlphare dm arp/warp

Conversational User Interface user input ->

Conversational User Interface user input -> process the data in /data/semet

Conversational User Interface user input -> process the data in /data/semet recognition blah blah blah blah /data/semet

Conversational User Interface user input -> process the data in /data/semet recognition blah blah blah blah /data/semet simplify /data/semet

Conversational User Interface user input -> process the data in /data/semet recognition blah blah blah blah /data/semet simplify /data/semet preempt /data/semet contains image files

Conversational User Interface user input -> process the data in /data/semet report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 100 mm from the crystal using 1.54 Å x-rays.

Conversational User Interface user input -> process the data in /data/semet report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 100 mm from the crystal using 1.54 Å x-rays. confirm Everything look okay? [Yes] ->

Conversational User Interface user input -> process the data in /data/semet report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 100 mm from the crystal using 1.54 Å x-rays. confirm Everything look okay? [Yes] -> user input distance was more like 110

Conversational User Interface user input -> distance was more like 110

Conversational User Interface user input -> distance was more like 110 recognition distance blah blah blah 110

Conversational User Interface user input -> distance was more like 110 recognition distance blah blah blah 110 simplify DISTANCE 110

Conversational User Interface user input -> distance was more like 110 report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 110 mm from the crystal using 1.54 Å x-rays.

Conversational User Interface user input -> distance was more like 110 report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 110 mm from the crystal using 1.54 Å x-rays. confirm Everything look okay? [Yes] ->

Conversational User Interface user input -> distance was more like 110 report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 110 mm from the crystal using 1.54 Å x-rays. confirm Everything look okay? [Yes] user input -> wavelength is wrong

Conversational User Interface user input -> wavelength is wrong

Conversational User Interface user input -> wavelength is wrong recognition wavelength = -NOT

Conversational User Interface user input -> wavelength is wrong recognition wavelength = -NOT simplify WAVELENGTH

Conversational User Interface user input -> wavelength is wrong recognition wavelength = -NOT query What is the x-ray wavelength? [1.54Å] -> simplify WAVELENGTH

Conversational User Interface user input -> wavelength is wrong recognition wavelength = -NOT query What is the x-ray wavelength? [1.54Å] user input -> 1 simplify WAVELENGTH

Conversational User Interface user input -> wavelength is wrong query What is the x-ray wavelength? [1.54Å] user input -> 1

Conversational User Interface user input -> wavelength is wrong report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 110 mm from the crystal using 1 Å x-rays. query What is the x-ray wavelength? [1.54Å] user input -> 1

Conversational User Interface user input -> wavelength is wrong report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 110 mm from the crystal using 1 Å x-rays. query What is the x-ray wavelength? [1.54Å] user input -> 1 confirm Everything look okay? [Yes] ->

Conversational User Interface user input -> wavelength is wrong report Elves will process from /data/semet/frame001.img to /data/semet/frame100.img Data were collected from 0º to 100º in 1º steps with an ADSC Q4 detector 110 mm from the crystal using 1 Å x-rays. query What is the x-ray wavelength? [1.54Å] user input -> 1 confirm Everything look okay? [Yes] user input -> Yes

Major Phasing techniques Molecular Replacement Multiple Isomorphous Replacement Multiwavelength Anomalous Diffraction Single-wavelength Anomalous Diffraction

? Molecular Replacement correct structure and intensities ~cowtan/fourier/coeff.html

Molecular Replacement use something similar as a starting model

Model Building current model is missing something

Model Building phases from model

Model Building missing bits show up in “difference map”

Model Building missing bits show up better in F O + (F O - F C ) map

structure factor (F) spot index (h) Fitting data

structure factor (F) spot index (h) Fitting data

structure factor (F) spot index (h) Fitting data

structure factor (F) spot index (h) Fitting data

Major Phasing techniques Molecular Replacement Multiple Isomorphous Replacement Multiwavelength Anomalous Diffraction Single-wavelength Anomalous Diffraction

inverse Fourier Transform no phase

inverse Fourier Transform no phase

Major Phasing techniques Molecular Replacement Multiple Isomorphous Replacement Multiwavelength Anomalous Diffraction Single-wavelength Anomalous Diffraction

detector anomalous scattering sample x-ray beam

detector anomalous scattering sample x-ray beam

Independent tasks can be performed simultaneously Multiprocessing Strategy

SOLVE/P212121/done SOLVE/P21212/done SOLVE/P21221/done SOLVE/P22121/done SOLVE/P2221/done SOLVE/P2212/done SOLVE/P2122/busy SOLVE/P222/done Multiprocessing Strategy

epmr/P212121/model1/done epmr/P212121/model2/done epmr/P21212/model1/done epmr/P21212/model2/done epmr/P21221/model1/done epmr/P21221/model2/done epmr/P22121/model1/busy epmr/P22121/model2/done epmr/P2221/model1/ epmr/P2221/model2/ epmr/P2212/model1/ epmr/P2212/model2/ epmr/P2122/model1/ epmr/P2122/model2/ Multiprocessing Strategy

wARP/P212121/done wARP/P21212/done wARP/P21221/done wARP/P22121/done wARP/P2221/done wARP/P2212/done wARP/P2122/busy wARP/P222/done Multiprocessing Strategy

space group FOMR cryst P P P321 Multiprocessing Advantage

space group FOMR cryst P P P321 Multiprocessing Advantage

space group FOMR cryst P P P Multiprocessing Advantage

table1.com

Elven Automation How often does it really work?

Apr 6 – 24 at ALS Elven Automation 27,686images collected

Apr 6 – 24 at ALS Elven Automation 27,686images collected 148datasets (15 MAD)

Apr 6 – 24 at ALS Elven Automation 27,686images collected 148datasets (15 MAD) 31investigators

Apr 6 – 24 at ALS Elven Automation 27,686images collected 148datasets (15 MAD) 31investigators 56unique cells

Apr 6 – 24 at ALS Elven Automation 27,686images collected 148datasets (15 MAD) 31investigators 56unique cells 5 KDa – 23 MDaasymmetric unit

Apr 6 – 24 at ALS Elven Automation 27,686images collected 148datasets (15 MAD) 31investigators 56unique cells 5 KDa – 23 MDaasymmetric unit 0.94 – 32 Åresolution (3.2 Å)

Apr 6 – 24 at ALS Elven Automation 148datasets

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours 31failed

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours 31failed ~61 (0-231)hours

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours 31failed ~61 (0-231)hours 2 / 15MAD structures

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours 31failed ~61 (0-231)hours 2 / 15MAD structures

NumberDescriptionPercent Images (~7 TB)33% 2346Data sets47% 449MAD/SAD (1:2)19% 104Published4.4% in 2003 How many structures get solved?

Why do structures fail?

Overlaps Why do structures fail?

Overlaps Signal to noise Why do structures fail?

Overlaps Signal to noise Radiation Damage Why do structures fail?

Overlaps Signal to noise Radiation Damage Why do structures fail?

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours 31failed ~61 (0-231)hours 2 / 15MAD structures

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours 31 failed ~61 (0-231)hours 2 / 15MAD structures

unavoidable overlaps

detector

unavoidable overlaps phi detector

unavoidable overlaps mosaicity phi detector

unavoidable overlaps mosaicity phi detector c*

unavoidable overlaps mosaicity phi detector c* Ewald sphere

unavoidable overlaps mosaicity phi detector c* Ewald sphere

unavoidable overlaps mosaicity phi detector c* Ewald sphere

unavoidable overlaps mosaicity phi detector c* Ewald sphere

unavoidable overlaps mosaicity phi detector c* Ewald sphere

unavoidable overlaps mosaicity phi detector c* Ewald sphere

unavoidable overlaps mosaicity phi detector c* Ewald sphere

unavoidable overlaps mosaicity phi detector c* b c a

unavoidable overlaps mosaicity phi detector c* b c a

unavoidable overlaps mosaicity phi detector c* b c a

unavoidable overlaps mosaicity phi detector c* b c a

avoidable overlaps mosaicity phi detector c* b c a

avoidable overlaps mosaicity phi detector c* b c a

avoiding overlaps

c c

1000 mm

avoiding overlaps 1000 mm 2 mrad 10 seconds

avoiding overlaps 1000 mm 2 mm 2 mrad 10 seconds

avoiding overlaps 1000 mm 1 mm 1 mrad 20 seconds

avoiding overlaps 1000 mm 300 um 0.3 mrad 60 seconds

Overlaps Signal to noise Radiation Damage Why do structures fail?

Overlaps Signal to noise Radiation Damage Why do structures fail?

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours 31failed ~61 (0-231)hours 2 / 15MAD structures

Apr 6 – 24 at ALS Elven Automation 148datasets 117succeded ~3.5 (0.1-75)hours 31failed ~61 (0-231)hours 2 / 15MAD structures

Radiation Damage why not just avoid it?

Holton & Frankel (2010) Acta D

B ≈ 4 d average atomic B factor resolution (Å)

Simulated diffraction image MLFSOM simulatedreal

signal vs noise

“If you don’t have good data, then you have no data at all.” -Sung-Hou Kim

signal vs noise easy hard impossible

signal vs noise easy hard impossible threshold of “solvability”

signal vs noise “If you don’t have good data, then you must learn statistics.” -James Holton

Adding noise

= 1.4 2

Adding noise = = σ total 2 = σ σ 2 2

Adding noise = = σ total 2 = σ σ 2 2

Adding noise = = σ total 2 = σ σ 2 2

Adding noise = = =

MAD phasing simulation Anomalous signal to noise ratio Correlation coefficient to correct model mlphare results

SAD phasing simulation Anomalous signal to noise ratio Correlation coefficient to correct model mlphare results

SAD phasing experiment Anomalous signal to noise ratio Correlation coefficient to published model

MR simulation Signal to noise ratio Correlation coefficient to correct density corrupted data

MR simulation Signal to noise ratio Correlation coefficient to correct density corrupted data

MR simulation Rmsd from perfect search model ( Å ) Correlation coefficient to correct density corrupted model

MR simulation Fraction of full search model Correlation coefficient to correct density trimmed model

“photon counting” Read-out noise Shutter jitter Beam flicker spot shape radiation damage σ(N) = sqrt(N) rms 11.5 e-/pixel rms 0.57 ms 0.15 %/√Hz pixels? mosaicity? B/Gray? signal vs noise

Which error dominates? Weak spots (high-res) background MAD/SAD (small differences) detector calibration ( if not rad dam! )

Holton & Frankel (2010) Acta D

Background level sets needed photons/spot Moukhametzianov et al. (2008). Acta Cryst. D 64,

Holton & Frankel (2010) Acta D

Optimal exposure time (faint spots) σ total 2 = σ spot 2 + σ bg 2 + σ readout 2 + σ raddam 2 too long! σ total 2 = σ spot 2 + σ bg 2 + σ readout 2 + σ raddam 2

Optimal exposure time (faint spots) σ total 2 = σ spot 2 + σ bg 2 + σ readout 2 + σ raddam 2 too short!

σ total 2 = σ spot 2 + σ bg 2 + σ readout 2 + σ raddam 2 Optimal exposure time (faint spots) σ total 2 = N photons + σ readout 2 + σ raddam 2 needlessly long

N photons ≈ σ detector 2 Optimal exposure time (faint spots) “optimal”

N photons ≈ 10x σ detector 2 Optimal exposure time (faint spots) “buried”

N spot + N bg ≈ 10x m Optimal exposure time (faint spots) “buried”

0 + N bg ≈ 10x m Optimal exposure time (faint spots) “buried”

Optimal exposure time (faint spots)

t hr Optimal exposure time for data set (s) t ref exposure time of reference image (s) bg ref background level near weak spots on reference image (ADU) bg 0 ADC offset of detector (ADU) bg hr optimal background level (via t hr ) σ 0 rms read-out noise (ADU) gainADU/photon mmultiplicity of data set (including partials) Short answer: bg hr ~ 100 ADU for ADSC Q315r

What error dominates? Weak spots (high-res) background MAD/SAD (small differences) detector calibration if not rad dam!

Optimal exposure time (anomalous differences) I-I+ 3% 100 photons 10 photons 100 photons

Optimal exposure time (anomalous differences) I-I+ 3% 100 photons 14 photons 100 photons

Optimal exposure time (anomalous differences) 3% I-I photons 67 photons

Optimal exposure time (anomalous differences) 1% I-I+ 20,000 photons 200 photons

Minimum required signal (MAD/SAD)

Holton & Frankel (2010) Acta D

“photon counting” Read-out noise Shutter jitter Beam flicker spot shape radiation damage σ(N) = sqrt(N) rms 11.5 e-/pixel rms 0.57 ms 0.15 %/√Hz pixels? mosaicity? B/Gray? signal vs noise

Optimal exposure time (anomalous differences) σ total 2 = σ spot 2 + σ bg 2 + σ readout 2 + σ raddam 2

Optimal exposure time (anomalous differences) σ total 2 = σ spot 2 + σ bg 2 + σ readout 2 + σ raddam 2

Optimal exposure time (anomalous differences) no detector is perfectly calibrated! σ total 2 = N spot + σ bg 2 + σ readout 2 + σ raddam 2 + (f shutter N spot ) 2 + (f flicker N spot ) 2 + (f calib N spot ) 2 σ total 2 = N spot + σ bg 2 + σ readout 2 + σ raddam 2

Fractional error mult > ( — ) 2 R merge

Holton & Frankel (2010) Acta D

Damage model system

67 consecutive data sets

Data quality vs exposure Exposure time (min) Correlation coefficient

Data quality vs exposure Exposure time (min)  

Data quality vs exposure Exposure time (min)  

Data quality vs exposure Exposure time (min) Resolution limit

Data quality vs exposure Exposure time (min) R sym

Experimentally-phased map

Damage changes absorbance spectrum Photon energy (eV) counts

Damage changes absorbance spectrum Photon energy (eV) counts

Damage changes absorbance spectrum Photon energy (eV) counts

Damage changes absorbance spectrum Photon energy (eV) counts 1 0

fluorescence probe for damage Absorbed Dose (MGy) Fraction unconverted Wide range of decay rates seen Half-dose = 41.7 ± 4 MGy “GCN4” in crystal Half-dose = 5.5 ± 0.6 MGy 8 mM SeMet in NaOH Protection factor: 660% ± 94%

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