BEST a program for optimal planning of X-ray data collection from protein crystals - PowerPoint Presentation

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BESTa program for optimal planning of X-ray data collection from protein crystals

Alexander Popov

ESRF, MX group

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Geometry

Optimal starting spindle angle and scan range

Maximum rotation angle without spot overlap

Optimal Multiplicity

Space group, Cell parameters, Orientation,

Mosaicity

I(h,k,l), Ibackground

Statistics calculationReconstruction of average intensity vs. resolutionStatistics modeling based on Wilson distributionRadiation damage modeling

MOSFLM XDS

Optimal plan(s) of data collection

Initial Images

BEST

Ω

= 90

°

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Optimal

starting

spindle angle

and scan range

GEOMETRY

Maximum

rotation angle without spot

overlap

Space group, Cell parameters, Orientation,

Mosaicity, Spot Size

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Main uncertainties of the observed intensities are determined

by counting statistics

DATA STATISTICS

I

b

I

p

I

p

I

b

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Statistics

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Wilson plot

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Intensity decay:

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10/12/2014

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Global radiation damage

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Basic ideas of BEST

σ

2

І

(

J)=ko

+k1J+k2J2

Semi-empirical model for diffraction intensity vs reciprocal space coordinateSemi-empirical model of variance vs integrated intensity

Integration over the scanned reciprocal space using Wilson distributionRadiation-damage model

Resolution-dependent intensity decay:

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<I

D

>/ <I

o

>

<

/I>

R

1IDose [Gy] , d=2.5 Å

Expected Intensity Variation

SAD

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Intensity vs. crystal position

Intensity Anisotropy

φ

=0º

φ

=90º

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Optimal Oscillation Range

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User choices

MOSFLM

XDS

Optimal plan(s) of data collection

Statistics

B-factor

Beamline Flux

Crystal contents

RADDOSE

Absorbed dose rate

Initial Images

BEST

4.1

Data collection strategy accounting radiation damage

Detector parameters

Beamline

parameters and limitations

Optimize data collection

Optimize SAD data collection

Find optimal crystal orientation

Low-resolution optimal

Rad. Damage sensitivity

Multi-positional data

collection

Helical data collection

Estimate data statistics

Dose (Time) limit

Geometry limits

Aimed statistics

Aimed completeness

Aimed redundancy

Aimed resolution

Crystal shape and size

Beam profile and size

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Olof Svensson, NorStruct 20130910

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EDNA characterisation v1.3

A workflow written in Python

MOSLFM

indexing

LABELIT

DISTL

Indexing

Evaluation

MOSFLM

integration

[RADDOSE]

BEST

MOSFLM

Predictions

LABELIT

indexing

Indexing

Evaluation

Failure

Ok

Ok

Failure

+ Xtal info

+ beam flux

+ diffraction plan

Data collection plan

XDS backg.

estimation

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EDNA

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cyan fluorescent protein

............... Routine data collection.......

-q minimize total time, default minimize the absorbed dose

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BEST prediction

XDS

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---------------------------------------------

Resolution

RFriedel

(%) I/Sigma Redundancy

--------------------------------------------- 10.12 0.8 74.1 23.7 6.90 0.8 43.6 23.7 5.34 1.1 48.4 23.0 4.51 1.2 47.5 23.5 3.98 1.6 34.5 20.6 3.60 2.5 22.4 13.9 3.31 4.0 14.0 11.9 3.08 6.6 8.3 7.0

2.89 10.5 5.2 6.1 2.73 15.6 3.7 2.5 2.60 23.0 2.4 3.8----------------------------------------------------------------------SAD optimization

Minimum of RFriedel = <|<E2+/w>-<E2-/w>|> is a targetnoise only, no anomalous scattering itself:decay, non-isomorphismexact pair-vice dose differences for Bijvoet mates

http://skuld.bmsc.washington.edu/cgi-bin/MAD_power.pl

.............. SAD data collection............

-

asad, strategy for SAD data collection, resolution selected automatically,rot.interval=360 dg.-SAD {

no|yes|graph}, strategy for SAD data collection if "yes", "graph" - estimation of resolution for SAD

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SAD optimization

Minimum of

R

Friedel

=

<|<E2+> - <E2->|> is a target

site-specific damage processes the radiation damage may start affecting anomalous signal

Dose>2 MGy

Garman limitDose>30 MGy

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Olof Svensson, NorStruct 20130910

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Kappa goniostat re-orientation

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Kappa goniostat re-orientation

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User

MOSFLM

XDS

Plan

of data

collection

Beamline

Flux

Crystal contentsCrystal sizes

RADDOSE

Absorbed dose rate

Initial Images

Rad

. Damage

sensitivity

BEST

Induced Burn Strategy

11 cycles for testing

10 cycles for burning

Minimal RD inside the testing cycles

Must induce significant changes in Intensity

The intensity measurements remain statistically significant up to the last cycle of data collection

Measurements

XDS auto

RDFIT

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Example results from ”burning strategy”

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Multi-positional

or

helical

data collection

FAE crystals

ID23-1

E=12.75Kev, I=35 mA

, Aperture=0.03 mmFlux=1.5x1011 Photon/secFAE2 – 5 positions

The 70 kDa membrane protein FtsH from Aquifex

aeolicus I222, a = 137.9, b = 162.1, c = 170

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Diffraction resolution vs. absorbed

dose

for

different crystal size

B-factor=16 Á2

completeness =100%Rot.range=26°150 µm100 µm30 µm

10 µm5 µm

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Macrhodopsin

ID23-1,

Aperture 20

Flux =4.7e+11 [photons/s]Dose rate =0.5 Mgy

/s

Resolution vs.

Total exposure

BEST estimations, No radiation damage

Or 25000 crystals

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Two-dimension DC

Space group, Cell parameters, Orientation

MOSFLM XDS

Already collected data

X-ray

Test image(s)

Data Collection Strategy

Data Collection

Auto Processing

Number of crystals

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Beam profile effects

time (s)

ID23-2, 7e10 ph/s, trypsin, thin resolution shell [1.2 Å]

Log(I(t))

f

ast decay in the

b

eam center

slow decay at the tails

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1

st

order model convolved with the beam profile

measured with a 5 µm pinhole

1 fit parameter per data set, in all resolution shells :

β = 0.88 Å

2/MGy1st order rate equation, no intermediatesLog(I(h,t))

d= 1.8 Åd= 1.2 Åd= 2.4 Åd= 3.6 Å

t (sec)

ID23-2, 7e10 ph/s,

trypsin

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Background vs. Crystal position

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Diffraction sample Modeling

Voxel

Volumetric Picture Element

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Ω

Flux

σ

x

σ

y

aperture

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Ω

min

Ω

max

Vertical max

Crystal horizontal

Vertical min

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First step - scaling

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First step - scaling

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Acknowledgements

Gleb Bourenkov

ESRF MX Group

Olof Svensson & EDNA developers team