Data Management and Structure Determination at SDC/JCSG

Qingping XuSSRL/JCSG

Refinement

SDC activityYear

Crystals screened

Targets screened

Datasets collected

Targets collected

Targets in PDB

2000 33 15 0 0 0

2001 552 93 42 29 2

2002 2762 149 73 42 24

2003 6118 179 216 94 31

2004 4735 246 140 94 98

2005 6929 282 162 102 93

2006 19152 387 262 167 126

2007 29397 721 346 256 203

Total 69678 2072 1241 784 577

600 crystals / week 7 datasets / week 4 structures / week

26

67

180162 165

223

347

0

50

100

150

200

250

300

350

400

2001 2002 2003 2004 2005 2006 2007

Year

Dat

a co

llect

ed

1740

87 91106

139

252

0

50

100

150

200

250

300

2001 2002 2003 2004 2005 2006 2007

Year

Targ

ets

colle

cted

4/2007-4/2008

29,327 crystals screened from 721 targets335 datasets collected from 242 targets216 targets solved206 targets deposited

SDC Workflow1. Each crystal has a unique ID2. Essential information is captured in a central DB3. All data are online locally, also archived off-site4. Fixed data (directory) structures for all crystallographic data

Target info,crystal info

and storage ofanalysis data

for PDB

Diffraction images Data collection info

Crystal ScreeningBLU-ICE automatic screening interface

1. Co-developed by JCSG in 2000/2001

2. Robust and reliable crystal screening, 10 lost crystals in >150,000

3. Adopted by 85% of users; 75% of users collect data remotely

4. Implemented at other SR sources

Analysis of screening images

Crystal Screening Is Essential for Efficiency Use of Beamtime

1. Each crystal scored (0 -10) based on diffraction properties (resolution, spot quality)

2. Crystals with quality 6-10 are saved for possible data collectionSuccess rates for SDC stages

based on best quality crystal of each target

0.0%

10.0%20.0%

30.0%

40.0%

50.0%60.0%

70.0%

80.0%90.0%

100.0%

4 5 6 7 8 9 10

Quality score

Succ

ess

rate

Collection (%)Solution (%)Deposition (%)Cumulative (%)

All targets 2006 2002-5Collection 42% 40%Solution 85% 79%Deposition 92% 92%Cumulative 33% 30%

Structure Determination at SDC

• SDC structure determination strategy– Quick structure solution at the beamline by hand or

autoXDSp– Automated structure solution to systematically explore

application space, data space, and parameter space with Xsolve

– Human evaluation of automatic processing results– Manual inspection and resolution of unsolved/difficult

cases – Timely upload of inspected data to JCSG STSS

database

Development of Xsolve• Large scale operations call for integrated platforms

– No suitable third party platform from raw diffraction images to initial model for SDC needs

– SDC off-the-shelf PC Linux cluster– Many 3rd party crystallographic components to assemble the system

• Don’t always talk nice to each other, non-uniform data exchange• Different styles• Different capabilities

• Goal: To solve large number of MAD structures consistently and optimally with minimal human input– Automatically perform all processing steps without human intervention.– Provide reliable, high quality data processing for majority of datasets. – Provide best phases, optimal trace and processed data for refinement. – Exploit low cost modern computing for time-consuming data analysis.– Enforce uniform standards and provide data organization.

Structure Determination Process as Decision Trees

Full Tree Pruned Tree

Xsolve Implementation• Xsolve is developed as a distributed platform for wrapping third party

software• Xsolve adopts the “nearly” full tree approach by systematically

exploring parameters that are critical to structure solutions.• Methods: MAD/SAD and MR• Programs

– Data processing programs/strategies (MOSFLM, XDS & HKL ) – Phasing programs (SHELX, SOLVE, AUTOSHARP)– Density modification (DM, RESOLVE, SOLOMON)– Tracing programs (wARP, RESOVLE, RESOLVE_BUILD) – MR programs (MOLREP, PHASERS & EPMR)

• Combination of data/models• Space groups• Resolution• ASU content

Implementation of Xsolve (MAD)

MOSFLMXDSHKL

SCALAXSCALE

SCALEPACKTRUNCATE SHELX

SOLVESOLVE

AUTOSHARP

RESOLVEDM

SOLOMON

RESOLVEwARP

RESOLVE_BUILD

Index and integration

Scaling Truncation Search HA sites

Phasing

Density modification

Tracing

Consensus ModelPoint group Space group

ASU contentResolutionLaue group

Data combination

XSOLVE job distribution and control in JAVA

Crystallographic modules in XML

3rd party JMS message queue serverXsolve web server

Separated crystallographic modules allow new programs to be easily incorporated.

Data collection

Structure Determination

Start XsolveEvaluation of results

JCSG STSS DB

Xsolve Summary• 941 data processing entries in SDC

database since 4/2004 for 454 unique targets, 901 (96%) could be processed by Xsolve or manually.

• Xsolve successfully processed 801 (85%) of all 941 collected data, 89% of 901 all processible data.

• 86% of collected MAD targets were solved, Xsolve solves ~92% of solvable MAD structures.

• Data processing software usage: MOSFLM 440 (48%), XDS 401 (45%) HKL 60 (7%)

• Xsolve usually generates multiple solutions from different solving strategies, these solutions can be combined to give an improved model (Henry van den Bedem)

• Capability and reliability of Xsolve have significantly improved

• Solutions from Xsolve are essential for minimizing refinement time

4/2007-4/2008

Xsolve: PH10216A

• 315aa/8 Met, P21, 2.7Å, decamer in ASU

• Data processed in MOSFM/SCALA

• SHELXD found 58/60 sites

• Heavy atom refinement and phasing were carried out using SOLVE and AUTOSHARP

• RESOLVE_BUILD (iterative RESOLVE with refinement by REFMAC) generated very good initial trace despite of the poor resolution

Xsolve: Ugly Diffraction ImagesPE01933E, 331aa, 8 Met, C2221, 2.0 Å

Xsolve traced 315 out of 331, MOSFLM

Consensus Model

• Mix and match multiple incomplete models to increase completeness• Error reduction: Compare input models to identify and correct errors• Obtain a ‘globally optimal’ model: DP algorithm

Target/CrystalID rsds res SG mol models best trace Consensus

PC07317D/22317 253

203

310

160

PC04261E/24045 311 2.56 P43212 1 6 31%1

2.3

84%

1 2 78% 86%

PC02663D/22977 2.0

C2

C2

I4

2 8 88% 93%

TM0771/20687 2.0 1 3 69% 79%

TM1622/13219 1.9 1 37 84% 84%P3221

Quick MAD Structure Solution

XDSProcessing

in P1

XDSIntegration

XSCALEScaling

SHELXDHA search

SHELXESpace group

Handness

autoSHARPHA refinement

Phasing wARPHigh resol

Tracing

ResolveLow/med resol

Tracing

Laue group determined All data processed Space group, map, nmol

Control Script: Image parser, log parser, decision making

XDSProcessing

in P1

XDSProcessing

in P1

XDSIntegration

XDSIntegration

XSCALEScaling

XSCALEScaling

SHELXDHA search

SHELXDHA search

SHELXESpace group

Handness

SHELXESpace group

Handness

autoSHARPHA refinement

Phasing wARPHigh resol

Tracing

DM/wARPHigh resol

Tracing

ResolveLow/med resol

Tracing

Resolve_bldLow/med resol

Tracing

Laue group determined All data processed Space group, map, nmol

Control Script: Image parser, log parser, decision making

• Rapid evaluation of data quality– Automated execution of all steps from images to initial model– Can the structure be solved with the current data?

• Single script with simple command line– Location of diffraction images – Protein sequence file

• Exploits parallel data processing features built into XDS– Divide dataset into segments – Process each segment in parallel via a batch queuing system (LSF).

• Uses robust and reliable programs for structure solution– SHELX, autoSHARP, RESOLVE and wARP– Execute structure solution steps in parallel e.g. search for heavy atom sites in multiple

space-groups.• Processed data meets JCSG QC guidelines and can be directly uploaded to STSS.

autoXDSp: PC05995D

First interpretable map in less than 30 minutes (P41212, 1 monomer per asu, interpretable map). SHELXE map overall correlation to the final model is 0.73 (<φ>=51). The phases were subsequently improved in autoSHARP, CC=0.86, <φ>=36. 191 aa traced in wARP.

Step Time* (s)

Laue Group 361

Integration 906

Scale 941

MAD Scale 1063

SHELX 1519

207aa/3 Met, 3-wavelength MAD, each sweep consists of 90 MARCCD 325 images

* Measures time from start to the end of current step

%autoXDSp -data /data/jcsg/ssrl2/9_2/20060312/collection/PC05995D/23156 -seq seq.dat

FM11607A: Corrupted Sweeps

H32 3wav MAD, 36 sweeps

Applicable to small sweeps from multiple crystals

• Lots of data in short amount of time• 65 data sets, 90 frames each (MARCCD325)• Automatic processing:

– index-integrate-scale-truncate-refine– 59 out of 65 processed automatically in 2hrs

Parallel Processing of High-throughput Fragment Screening

Stout, Scripps

Manual Processing• Automatic processing allow human efforts on more difficult cases• Human intelligence to overcome program failures

– Benchmarks for automatic processing– Processing difficult cases– Interpreting Xsolve results, guiding/fine tuning Xsolve jobs toward

success– Feedbacks to programmers for future improvements

• Parallel fine sampling to solve large or difficult structures– Manually exploring large parameter space to find right combination of

parameters is time-consuming and frustrating. It could lead to prematurely abandonment a potentially solvable structure.

– Fine grid sampling (Xsolve strategy applied locally) to solve large or difficult structures

• Parallel exploration of parameter space by brute force is an effective approach to solve challenging structures efficiently and reliably

• Systematically explore parameter space• Speed up with parallel execution on cluster

Structures Solved by Fine Grid Search

Target Mol/ASU Sites/Mol Sites Space Group

Resolution

MB3864A 4 6 24 P43

H3

P21212P212121

P3121

P1C2

2.65PE000293D 6 9 54 2.15

PD06751F 6 14 84 1.90TB1547G 8 12 96 2.20PC06751C 6 20 120 2.70

FJ5490C 12 6 72 2.00FH7599A 12 17 204 2.00

TB1547G: Mislabeled Target• 409aa/13 Met, P212121, 2 tetramers per

asu• Initially labeled as something else

(TB5131A, 179aa/2 Met)• POINTLESS and XPREP to narrow

down space group choices, XPREP to generate FA values

• Treated as an unknown target, SHELXD Grid search:

– Sites 20-120 in step of 10– Resolution cutoff 3.3-4.5 in step of 0.1– E value cutoff from 1.1-1.5 in step of 0.1

• 520 parallel SHELXD jobs, each SHELXD job attempts 200 trials

• The job order was randomized to uniformly sample the search space initially

• Solutions appeared in minutes (jobs could be terminated early)

• Each SHELXD job needed ~1hrs, ~2 hrs for all jobs to finish on SDC cluster (220 CPUs)

• Interpretation of density map gave correct identification of the target

FH7599A: MR or MAD• 427 aa/17 Met, C2, 2.0Å, 4 trimers

(600kD) per asu• Estimated 10-20 monomers per asu,

100-300 heavy atom sites• No highly homologous (>20% seq id)

MR models• MAD

– Patterson seeding, 1 solution in ~6 million trials

– Random atom seeding, ~6% correct • MR

– FFAS or PSI-BLAST identified a remote sequence homolog TM0064 (14% seq id)

– TM0064 trimer poly-alanine was used as MR model, the use of the trimer as MR template significantly improved signal to noise of the MR procedure

– Density modification was critical for improving MR phases

– Improved DM phases + MAD data to locate ~200 heavy atom sites and MAD phasing

rmsd 2.42 Å for 82% Cα

FH7599A vs TM0064

2.8 Å PD07848H: Buccaneer

Very fragmented,no seq assignment

1 partial 63% dimer,Rest of trace is poor

Real space MR(ncs ops, mask)

DM with NCS94% traced, full seq

Problems with Structure Solution• 20% MAD/SAD data sets (24% collected targets) not

solved 1st time collected– Data that can not be indexed and processed (~20% data sets), or

the processed data have poor quality (~30%) – Poor resolution (~20%)– Targets with limited or no anomalous signal (1 or 2 Se-Met) (10-

15%)– Twinning (10-15%)

• Improved detection of twinning in Xsolve with PHENIX tools• All current JCSG twinned structures are solved by ignoring

twinning at solve stage (i.e. the structure was solved in the apparent space group and later refined in the correct space group)

• Sometimes there may be no correlation between twinning fraction and whether it can be solved by MAD method

• Lack effective and reliable methods to solve twinned MAD data

– Many targets (~50%) were solved later by screening/collection more crystals

Structure QC prior to PDB Deposition• Provide refiner with subjective and objective feedback on structure quality.• Automated QC check script used iteratively throughout refinement.

– Evaluates objective criteria based on best practices developed throughout JCSG, as defined in “refinement guidelines” documentation

– Checks for common errors and enforces standards• Develop additional scripts which turn some subjective decisions into objective evaluation

e.g. NCS mis-matches, side chains truncation, solvent structure.• Manual QC focused on subjective issues relating to functional interpretation and unresolved

crystallographic problems.

Quality of protein crystal structuresBrown and Ramaswamy, 2007

Dissemination

http://www.topsan.org

• Complete and accurate PDB deposition– Experimental

details– Unmerged data– Experimental

phases – Coordinates

• Community based structure annotation TOPSAN

• Provide developers or educators with well documented datasets

Conclusions and Future Directions• Xsolve and other tools

– Automatically perform all processing steps without human intervention– Provide reliable, high quality data processing for majority of datasets– Exploit the strength of different program packages– Provide optimal trace and processed data ready for refinement– Trade-off between low cost modern computing and time-consuming data

analysis– Enforce uniformity in data organization and standards

• Future developments– Better tools for analysis of results– Make it available through a web server to SSRL users and make version

that can be installed at other large facilities/institutions– Incorporating new programs/features– Become more intelligent, more feedbacks, handle more difficult cases– Improve flexibility and consistency– Better usage of resources– Developing a fully distributable version

AcknowledgementsAshley Deacon

Günter Wolf Henry van den Bedem

UCSD & BurnhamBioinformatics Core

John WooleyAdam Godzik

Lukasz JaroszewskiSlawomir Grzechnik

Sri Krishna SubramanianAndrew Morse

Tamara AstakhovaLian Duan

Piotr KozbialDana Weekes

Natasha SefcovicPrasad Burra

Konstantina BakolitsaAndrei Istomin

Kyle EllrottJosie AlaoenCindy Cook

GNF & TSRICrystallomics Core

Scott LesleyMark KnuthHeath Klock

Dennis CarltonThomas Clayton

Marc DellerDaniel McMullan Polat Abdubek

Julie FeuerhelmJoanna C. Hale

Thamara JanaratneHope Johnson

Edward NigoghossianLinda Okach

Sebastian SudekGlen Spraggon

Bernhard GeierstangerSanjay AgarwallaAnna Grzechnik

Connie ChenDustin Ernst

Regina GorskiSachin Kale

Amanda NopakunChristina PuckettTiffany Wooten

Jessica CansecoMimmi Brown

Scientific Advisory BoardSir Tom BlundellUniv. CambridgeHomme Hellinga

Duke University Medical CenterJames Naismith

The Scottish Structural Proteomics FacilityUniv. St. AndrewsJames Paulson

Consortium for Functional Glycomics,The Scripps Research Institute

Robert StroudCenter for Structure of Membrane Proteins,

Membrane Protein Expression Center, UCSF Soichi Wakatsuki

Photon Factory, KEK, JapanJames Wells

UC San FranciscoTodd Yeates

UCLA-DOE, Inst. for Genomics and Proteomics

TSRI, NMR CoreKurt Wüthrich

Reto HorstMaggie Johnson

Amaranth ChatterjeeMichael Geralt

Wojtek AugustyniakPedro Serrano

Bill PedriniBiswaranjan Mohanty

Jin-Kyu Rhee

TSRI Administrative Core

Ian WilsonMarc ElsligerGye Won Han

David MarcianoHenry Tien

Lisa van Veen

Stanford /SSRL Structure Determination Core

Keith HodgsonAshley Deacon

Mitchell Miller Herbert Axelrod

Hsiu-Ju (Jessica) ChiuKevin Jin

Christopher RifeQingping Xu

Silvya OommachenHenry van den Bedem

Scott TalafuseRonald Reyes

Abhinav KumarChristine Trame

Debanu DasWinnie Lam

The JCSG is supported by the NIGMS Protein Structure Initiative Grant U54 GM074898

Ex officio founding members JCSG-1Raymond Stevens , TSRI

Susan Taylor, UCSDPeter Kuhn, SSRL/TSRI

Duncan McRee, TSRI/SyrrxPeter Schultz, TSRI/GNF