Andre, some suggestions:
1. First be sure that shape reconstructions as an approach to interpreting your data is justified – the shape reconstruction approach can be quite misleading in some circumstances:
i. Does your data show any evidence of flexibility and lack of compactness from Kratky and Porod-Debye analyses? Such aspects can exaggerate molecular volumes, undermining the ability to implement shape reconstruction algorithms to arrive at stable solutions. Extra floppy bits like extended linkers his-tags and mixtures of conformations can also affect apparent volumes.
ii. Does your data agree with your understanding of molecular mass at those concentrations (e.g., Mass by Qr, Mass by I(0), Mass by empirical relationships with Porod Volume, etc.). Does Oligomer/Mixture analysis tell you that you have all tetramer, rather than say 95% tetramer/5% dimer…? Is there evidence of aggregation or concentration-dependence through multiple concentrations? As one can guess, mixtures and aggregation can undermine reliable shape reconstruction and interpretation.
iii. How does the atomic inventory of your model compare to that of the reconstruction? Commonly, x-ray crystal structures are missing sequences that might otherwise be in a full-length/native construct. If your scattered sample has a composition not entirely represented in your atomic model, automated approaches might be misled, and doing it by eye might be difficult without obvious landmarks or constraints. It could be very helpful to scatter a few different truncations and then to employ simultaneous solution approach used in MONSA. Increasing your data-to-parameters always helps!
iv. How does a CRYSOL/FOXS fit between your model and the primary data look, independent of the shape reconstruction calculations?
v. Does a symmetry-free (P1) calculation using DAMMIF or GASBOR agree with a symmetry-imposed calculation?...What is the distribution of the Normalized Spatial Discrepancies (NSDs) and Chis like for 10+ calculations? Is averaging justified by the statistics?
2. With regards to software suggestions, in addition to SUPCOMB, I might suggest looking at the SITUS/SCULPTOR package. It uses a real-space approach to reconcile atomic models with volumetric representations, and does provide a real-space correlation coefficient for fits.
Hope that helps,
Kushol
Kushol Gupta, Ph.D.
Research Associate - Van Duyne Group
Department of Biochemistry and Biophysics
Perelman School of Medicine at The University of Pennsylvania
<mailto:[log in to unmask]> [log in to unmask] / 215.573.7260 / 267.259.0082 / <http://www.stwing.upenn.edu/~kgupta> www.stwing.upenn.edu/~kgupta
From: CCP4 bulletin board [mailto:[log in to unmask]] On Behalf Of Andre Godoy
Sent: Monday, February 2, 2015 5:53 AM
To: [log in to unmask]
Subject: [ccp4bb] [off topic] Fitting unknown model in SAXS envelope
Dear users
I'm having some troubles to fit my x-ray model in my SAXS envelope..
more about:
1) I have a SAXS model with enough room for 6 monomers.
2) I have the crystallographic structure, but AU or any generate symmetry related doesn't appears to be the biological unit (I mean, crystal packing is different from SAXS packing)
Is there any piece of software that can take monomers and find the best (or least worst) RMSD between a SAXS envelope and a generated coordinate system? Or anyone have a good ideia for me to do so?
All the best,
Andre Godoy
PhD Student
IFSC - University of Sao Paulo - Brazil
