sastbx ALS UM - cci.lbl.govcci.lbl.gov/~phzwart/Talks/sastbx_ALS_UM.pdf · Real space...
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Accelerated shape discovery fromSAXS data with the Small AngleScattering ToolBox (SASTBX)
Peter Zwart
The SASTBX
• Open source software for analyses of SAXS data— http://sastbx.als.lbl.gov—Extends the CCTBX—Hybrid C++/phython environment
• Tools—Kratky analyses—I0 / Rg estimates—P(r) estimates—Model data calculation—Model refinement—Shape discovery
Model refinement
• How to modify a crystals structure so that it fits SAXS data?— Iterative normal mode perturbations to model—Use she (spherical harmonic expansion) for model data
calculation
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Zernike Polynomials
Zernike Moments
Orthonormal in unit sphere
Polynomial weights
Weighted Sum of basis functions
Real space representation of 3DZP
Model Representation
Cnlm
{(x,y,z)} 1000x {Cnlm} 100x
•Fnl•Fnn’l•Hnn’
Intensity Calculation
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Build Shape Database
{Cnlm}
{Cnlm}
{Cnlm}
{Cnlm}
ShapeDatabase
ModelDatabasePDB,PISA,PIQSI
Somethingyou build
1.Read SAXS data2.rmax guesses3.Shape hypothesisranking4.(sequence alignment)
!
Hnn '
{ } !
cnlm
{ }
!
Fnn ' l
{ }
!
Sequence
Coefficients for reconstruction
High information contentshape vectorProtein sequence
Shape vector related to SAXS curves
10k structural assemblies
Experimental SAXS data
Input
Output: proposed low resolution shapes
Rough shape classification from SAXS data
Model Comparison
cc = 0.93
Alignment
sastbx.shapeup target=iofq.dat pdb=2p6n.pdb
Run time: 80 seconds
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Bioisis data Features
• Fast and Automated—Providing preliminary results in 2 minutes—real time feedback to experiments
• Flexible approach—Customized shape database can enable even
faster shape reconstruction and enhance morerelevant results
—Not limited to biomolecules
Refinement Expansion
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CarvingLocal Refinement
Challenging Questions
• Number of Zernike polynomes—Speed vs Accuracy (and q_range)
• q_range—q_start; q_stop
• Model Quality—Compare to available model—Check consistency of the top models
Model Quality Measure
• Model Quality is positively correlated to the consistency
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Diverse models Diverse models
Diverse models Summary
• Zernike Moments can represent biomoleculemodels
• SAXS intensity can be calculated from zernikemoments in an efficient manner
• Model can be efficiently recovered fromDatabases
• The process is fast and automated• The model quality can be gauged by comparing
to existing models or from model consistency
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Outlook
• Increasing information content in SAXS data canbe achieved by taking ultra-fast snapshots,before molecules reorient themselves
• Fluctuation X-ray Scattering (fXS)Ensemble ofparticles
Beyond Small Angle Scattering: Exploitingangular correlations
Saldin et al, (2010) Phys Rev B, 81, 174105.
Ensemblescattering patterns
Angular auto-correlation
Scattering pattern
‘Fast’ X-ray pulse Data reductionof large numberof images
‘Phasing’ ‘Phasing’
Outlook
Normal Mode Perturbations
• The fXS experiment results in an estimateof the auto correlation function of thescattering pattern of a single particle.
• fXS data has orders of magnitudes higherinformation content as compared to SAXSdata.
• fXS can in principle be used for ab-initioshape reconstruction as well— The 2D case has recently shown to be
feasible— The 3D case is feasible as well, but await
implementation
• All that can be done with SAXS/WAXS canbe done with fXS data.
Acknowledgements
Haiguang LiuRalf Grosse-KunstlevePaul AdamsAlex HexemerEric SchaibleRobert Rambo
Dilano SaldinJohn Spence
$$$ LBNL
Question/Suggestion, send to [email protected]