After running autobuild, the Rfactors were 26/39 (autobuild removed the first 30 residues from the Nter!) but the maps look much better.
I ran a quick refinement with default settings and the Rfactors are now 31/39 and can now see the density for my peptide (absent in the model) coming up.
I have a few questions-
1) When is a good time to start building the peptide into the density (should I wait until Rfactors improve significantly)?
2) If so, should I be masking the peptide density somehow so that further refinement doesn't flatten out that density?
3) What is a general good strategy for lowering Rfactors? (Esp if the gap between Rwork and Rfree is high..like 28/40 or so)?
Thanks a lot,
S
-----Original Message-----
From: Sneha Rangarajan
Sent: Wednesday, October 01, 2014 12:54 PM
To: 'Paul Adams'
Cc: [email protected]
Subject: RE:
I think my problem in MR has been one of the chains. Anyway I tried the ideas you suggested and seems like they worked!
I used ensembler to create a merged pdb of the problematic chain and used phaser giving both chains as multiple ensembles. It gave me a solution with LLG=474 (highest I have got so far) and TFZ=18.8.
I also tried MRage and got a solution with LLG=294.
In both these maps, the density for chain1 ("bad chain") is not as good as the other chain but is nonetheless far better than what I have got before.
I am currently running autobuild on the solution hoping my Rfactors would be reasonable this time.
Thanks a lot for your inputs. They really helped!!
S
-----Original Message-----
From: Paul Adams [mailto:[email protected]]
Sent: Tuesday, September 30, 2014 7:51 PM
To: Sneha Rangarajan
Subject: Re:
This likes normal orthorhombic data. In this case I suggest that the most likely issue is the search model (I assume your molecule is fairly small given the unit cell dimensions). I would look at ways to create the best search model using using tools like sculptor and ensembler. You can get Phaser to search for the two domains in the same run but using multiple ensembles. You might also want to try MRage in Phenix, where you can just provide the data file and the sequence and it will try to make the best model and solve the MR problem.
On Sep 30, 2014, at 3:32 PM, Sneha Rangarajan
Oh I see. I tried to repeat xtriage with the scala.mtz file and am attaching the log file.
________________________________________ From: Sneha Rangarajan Sent: Tuesday, September 30, 2014 5:58 PM To: Paul Adams Cc: [email protected] Subject: RE:
Even i thought so but after i run mosflm and process the data in p21 or p1 and run quicksymm/quickscale it always suggests that the chosen space group is not correct and that it should be p212121.
I will try looking into Zanuda. Thanks.
S ________________________________________ From: Paul Adams [[email protected]] Sent: Tuesday, September 30, 2014 5:36 PM To: Sneha Rangarajan Cc: [email protected] Subject: Re:
It looks like your R-merge etc in P222 is very high, what leads you to think this is the correct point group? Can you send the xtriage output for the unmerged P2 data?
On Sep 30, 2014, at 2:29 PM, Sneha Rangarajan
wrote: Hi Nat,
I am attaching the Xtriage log file from p222.mtz. Would you need anything else (mtz,pdb)?
Thanks, Sneha
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On Thu, Oct 2, 2014 at 7:34 AM, Sneha Rangarajan
1) When is a good time to start building the peptide into the density (should I wait until Rfactors improve significantly)?
I would advise waiting until the rest of the model is as good as possible. That way you can use the difference map as a paper figure without needing to do any extra refinement to remove model bias later. 2) If so, should I be masking the peptide density somehow so that further
refinement doesn't flatten out that density?
Further refinement is probably going to make the density clearer, if it's at full (or near-full) occupancy.
3) What is a general good strategy for lowering Rfactors? (Esp if the gap between Rwork and Rfree is high..like 28/40 or so)?
Several things to try: - much longer refinement, say 10 macro-cycles instead of 3 (and even more may be helpful) - simulated annealing - although this sometimes has a tendency to overfit, but right now that's not as big a problem - weight optimization will reduce the gap between R-free and R-work, although it will also slow down convergence But you should also try to make the model as complete as possible - AutoBuild usually leaves out some residues, and rebuilding them should reduce your R-factors by quite a bit. You may be able to simply copy over appropriate pieces of the original model if they fit the map well (or can be adjusted easily). -Nat
Hi,
1) When is a good time to start building the peptide into the density (should I wait until Rfactors improve significantly)?
I would advise waiting until the rest of the model is as good as possible. That way you can use the difference map as a paper figure without needing to do any extra refinement to remove model bias later.
It's good to keep in mind that in this case map will be biased by the non-atomic model (bulk-solvent), as well as by the atomic model as shown here: Acta Cryst. (2002). A58, 270-282. Also note, more (correct) model you build - better map you get - so even more model you can build.
3) What is a general good strategy for lowering Rfactors? (Esp if the gap between Rwork and Rfree is high..like 28/40 or so)?
28/40 sounds worrying. In majority of scenarios I've seen so far such a big difference between Rfree and Rwork indicates a problem that is typically out of scope of refinement. Pavel
Thanks for your suggestions. I did another round of refinement with default settings (XYZ,realsp, IndB and occ) with and without weight optimization. Without weight opt, the Rfactors are 23/36 with RMSbonds-0.0108 and RMSangles-1.750 With weight optimization (Xray stereo and Xray ADP) the Rfactors are 32/39 with RMSbonds-0.0052 and RMSangles-1.390. I am now going to try running simulated annealing along with weight optimization and see if that makes a difference. S From: Pavel Afonine [mailto:[email protected]] Sent: Friday, October 03, 2014 2:30 AM To: Nathaniel Echols; Sneha Rangarajan Cc: [email protected] Subject: Re: [phenixbb] (no subject) Hi, 1) When is a good time to start building the peptide into the density (should I wait until Rfactors improve significantly)? I would advise waiting until the rest of the model is as good as possible. That way you can use the difference map as a paper figure without needing to do any extra refinement to remove model bias later. It's good to keep in mind that in this case map will be biased by the non-atomic model (bulk-solvent), as well as by the atomic model as shown here: Acta Cryst. (2002). A58, 270-282. Also note, more (correct) model you build - better map you get - so even more model you can build. 3) What is a general good strategy for lowering Rfactors? (Esp if the gap between Rwork and Rfree is high..like 28/40 or so)? 28/40 sounds worrying. In majority of scenarios I've seen so far such a big difference between Rfree and Rwork indicates a problem that is typically out of scope of refinement. Pavel
On Fri, Oct 3, 2014 at 11:58 AM, Sneha Rangarajan
I did another round of refinement with default settings (XYZ,realsp, IndB and occ) with and without weight optimization.
Without weight opt, the Rfactors are 23/36 with RMSbonds-0.0108 and RMSangles-1.750
One idea would be to run AutoBuild again. I've seen cases before where it didn't converge using the default settings, and feeding a previous result back into the program for a second run produced significantly better models. It might help get rid of the overfitting. -Nat
This was a great idea. My Rfactors after a second round of autobuild are now 25/32. I think it might be getting there afterall ☺
S
From: Nathaniel Echols [mailto:[email protected]]
Sent: Friday, October 03, 2014 3:08 PM
To: Sneha Rangarajan
Cc: Pavel Afonine; [email protected]
Subject: Re: [phenixbb] (no subject)
On Fri, Oct 3, 2014 at 11:58 AM, Sneha Rangarajan
participants (3)
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Nathaniel Echols
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Pavel Afonine
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Sneha Rangarajan