It is hard to make sensible comments without seeing your maps.
In these cases I use coot to validate.
Run the ramachandran check - click on all outliers and see if what the
electron density looks like. Sometimes you do see indicators on how to
make corrections. Sometimes you have a CIS peptide which has been
forced to be TRANS - that can cause disturbances in neighbouring
residues too.
For the clashes - I use the REFMAC listing to see where they are - again
check the density - and rebuild if possible. Some residues may simply be
invisible, then I put the occupancy to 0.00 .
Bad rotamers and angles can be caused by crystal packing but again check..
And remember that in most structures there are poorly ordered regions -
if the offending residues are there you probably cant refine them..
2.74A is not high resolution, so you will have problems correcting
everything
Eleanor
On 11/22/2011 01:41 PM, Rajesh kumar wrote:
>
> Dear Prof Dodson,
> I agree with you. Instead of further refining mutant structure, right now I am looking in to Apo structure. Which is at 2.74A and has R/freeR 22.7/27.9. But I have a molprobity profile like this
> Clashscore, all atoms: 33.73 50th percentile* (N=185, 2.740Å ± 0.25Å)Geometry Poor rotamers 8.11% Goal:<1%Ramachandran outliers 0.52% Goal:<0.2%Ramachandran favored 95.19% Goal:>98%Cβ deviations>0.25Å 2 Goal: 0MolProbity score^ 3.04 53rd percentile* (N=5278, 2.740Å ± 0.25Å)Residues with bad bonds: 0.00% Goal: 0%Residues with bad angles: 0.34% Goal:<0.1%
> If i fix the all the possible outliers and refine the structure it wouldn't improve the molprobity scores. I am not happy about the above scores at all. I am wondering if this is an indication of any wrong in the structure or is this common for an enzyme. I have reprocessed the data to make sure space group is same C2221.Any help would help me understand this and learn more.
> ThanksRaj
>> Date: Mon, 21 Nov 2011 12:27:04 +0000
>> From: [log in to unmask]
>> To: [log in to unmask]
>> CC: [log in to unmask]
>> Subject: Re: [ccp4bb] help with the structures
>>
>> I think you are proving yet again that refinement at 3.3A is not easy.
>> Indeed there are probably multiple conformations for parts of the
>> structure and that may well be why your data is at low resolution and
>> anisotropic. Maybe this is the best you can do..
>>
>> I think I would make sure the apo structure is as good as it can be,
>> then fit that to the 3.3A data set, and only use that 3.3A data to
>> deduce whatever features differ from the APO structure.
>>
>> Eleanor
>> On 11/19/2011 12:09 PM, Rajesh kumar wrote:
>>>
>>> Dear All,
>>>
>>>
>>>
>>> We have an anisotropic dataset of 3.3 A and it was solved (not by me) with P6522 with R/freeR
>>> 29.1/37.3.
>>>
>>>
>>>
>>> I got the corrected
>>> mtz file by plugging in the .HKL (P6122) file to anisotropy diffraction server at
>>> 2.04 A. I reindexed this p6122 to p6522 and extended the resolution and refined
>>> (refmac) the structure to R/freeR
>>> 36.40/38.50. With aotoncs option, fixing all Ramachnadran and rotamer
>>> outliers I got it 30/32. When I added waters and it went down to 27.5/31.2. At
>>> this point I recognized that my new .mtz file from anisotropy server has
>>> different R flag than the earlier one (3.3A) so I copied the R flag and did refinemnt to get R/Rfree 0.2682/0.3247. When I looked at
>>> the refined structure I found more outliers
>>> than I fixed in earlier round. I did fix all the outliers and without NCS and
>>> waters it gives R/Rfree 0.2906/0.3325. At all the stages I look at outliers at
>>> molprobity server which suggested structure is 10th percentile and after
>>> refinement more outliers comes back. At stage-1 map looked far better so was
>>> happy that anisotropy correction has worked for me (this was my first time
>>> handling this type of dataset) but further refinement didn’t make it look any
>>> better.I use both refmac and autoBuster for refinement. http://www.flickr.com/photos/rajesh_ccp4/sets/72157628048657095/
>>> This protein is an human enzyme and a bacterial homologue
>>> which has 38% identity has been used to solve the Apo structure (2.7 A, pC2221, R/freeR
>>> 23.03/27.96, molprobity is around 50th percentile). I looked in to this I try to fix all the outliers and try to improve
>>> molprobity score but it just refused to improve as after refinement I get more
>>> outliers. This Apo structure was used to solve the mutant structure at
>>> 3.3 A. I believe that both structure could
>>> have better R/freeR and excellent molprobity scores than what they have now. I am not able to recognise
>>> if there is any problem in Apo structure and if errors have come to mutant so
>>> both of them refuse to improve.
>>>
>>>
>>> I wondered if there is any model bias (I don’t know if it’s
>>> the case but nothing was coming to my mind) so thought using ARP/wARP classic
>>> to build model from existing model but it complained that "The wilson plot
>>> is very bad and ARp/wARP is very unlikely to run in a sensible way. Please
>>> check your data" . http://www.flickr.com/photos/rajesh_ccp4/sets/72157628048687955/
>>>
>>>
>>>
>>> At this point I dont know how to systematically dissect this problem. I know there could be wrong in several places but with my only '2-3 structure experience' I am not able to identify the regions to look for
>>> error but I think something is not right. I really appreciate if you give me
>>> some suggestions/ideas/directions/tips so that I could recognize problem and
>>> improve structure and learn some more.
>>> I appreciate your valuable time.
>>> Regards,Rajesh
>>
>
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