I also should have added that if you use a predicted structure and you run MR 
with it and then modify it to fit the data of your novel structure then, for 
sure, MolProbity applies or other tools as you will find in the various 
packages and on the PDB site.

The most current predicted structures usually do have an energy minimisation 
step at the end but nevertheless you can always add it yourself as Xavier 
pointed out.

In general, your prediction is a very good, educated guess on what your protein 
might look like. However,  the algorithm has no clue about your crystallisation 
condition or even the true biological environment in the cell and hence cannot 
take this chemical information into account when arranging the atoms. The 
algorithm also doesn't know that you have a membrane protein or different 
domains that need to be arranged relative to each other. The artefacts 
mentioned by Xavier are most likely a result for this lack of knowledge by the 
algorithm. Or just poor performance after all, even the best predictor can't do 
magic...

Look at the pLDDT score for your prediction, a local measure for the confidence 
with which each residue was placed into 3D space. A low score (<50) means high 
uncertainty and these residues should be removed anyway.

So, open your model in Coot, look at it and remove the rubbish...

M
________________________________
From: CCP4 bulletin board <[email protected]> on behalf of F.Xavier 
Gomis-Rüth <[email protected]>
Sent: 21 December 2021 10:04
To: [email protected] <[email protected]>
Subject: [ccp4bb] Fwd: [ccp4bb] Validation of structure prediction

Dear all,
this is by far not the general case in our hands. Depending on which AlphaFold 
protocol is used, the resulting models have locally disfavourable
geometries–including clashes–, impossible chain crossovers, etc. I would 
definitively recommend everybody to go through the model in detail and perform
a final geometry minimization with Coot and/or Phenix/Refmac. And in these 
cases, general geometry validation as provided by MolProbity
provides a final proof of the computational model.
Best,
Xavier


-------- Forwarded Message --------
Subject:        Re: [ccp4bb] Validation of structure prediction
Date:   Tue, 21 Dec 2021 09:43:37 +0000
From:   Vollmar, Melanie (DLSLtd,RAL,LSCI) 
<[email protected]><mailto:[email protected]>
Reply-To:       Vollmar, Melanie (DLSLtd,RAL,LSCI) 
<[email protected]><mailto:[email protected]>
To:     [email protected]<mailto:[email protected]>


Tristan is spot on. All the predicted structures have near perfect geometry, so 
commonly used validation tools like MolProbity can no longer be applied.

What you need to consider is biological relevance of the predicted model. Does 
the model correctly reflect residue arrangement in the active site? Are domains 
in correct relative orientation to allow for interactions and movements, 
perhaps found by some other assay? Is there appropriate room to fit a 
ligand/cofactor? Are transmembrane helices, if there are any, correctly found?

You need to map the knowledge you have of your protein to the structure and see 
if the atom positions and what you know support each other.

Cheers

M
________________________________
From: CCP4 bulletin board <[email protected]><mailto:[email protected]> 
on behalf of Tristan Croll <[email protected]><mailto:[email protected]>
Sent: 21 December 2021 08:28
To: [email protected]<mailto:[email protected]> 
<[email protected]><mailto:[email protected]>
Subject: Re: [ccp4bb] Validation of structure prediction

I agree with Dale. Tools like MolProbity are not the right approach to 
validating a structure prediction. To understand why, just consider that all 
you need to do to get a perfect MolProbity score is predict every structure as 
a single long alpha helix with ideal rotamers, with a kink at each proline.

To validate a predicted structure will require a completely different toolset - 
one that I’m not sure fully exists yet.

— Tristan

> On 20 Dec 2021, at 18:47, Dale Tronrud 
> <[email protected]><mailto:[email protected]> wrote:
>
>   I don't see any reason to believe that software designed to validate 
> crystallographic or NMR models would have any utility validating AlphaFold 
> predicted models.  Doesn't the prediction software already ensure that all 
> the indicators used by Molprobity are obeyed?  I'm afraid that the tools to 
> validate any new technique must be designed specifically for that technique. 
> (And when they become available they will be useless for validating 
> crystallographic models!)
>
> Dale E. Tronrud
>
>> On 12/20/2021 10:28 AM, Nicholas Clark wrote:
>> The Molprobity server can be run online and only requires the coordinates in 
>> PDB format: http://molprobity.biochem.duke.edu/ 
>> <http://molprobity.biochem.duke.edu/>.
>> Best,
>> Nick Clark
>> On Mon, Dec 20, 2021 at 11:10 AM Reza Khayat 
>> <[email protected]<mailto:[email protected]> 
>> <mailto:[email protected]>> wrote:
>>    ​Hi,
>>    Can anyone suggest how to validate a predicted structure? Something
>>    similar to wwPDB validation without the need for refinement
>>    statistics. I realize this is a strange question given that the
>>    geometry of the model is anticipated to be fine if the structure was
>>    predicted by a server that minimizes the geometry to improve its
>>    statistics. Nonetheless, the journal has asked me for such a report.
>>    Thanks.
>>    Best wishes,
>>    Reza
>>    Reza Khayat, PhD
>>    Associate Professor
>>    City College of New York
>>    Department of Chemistry and Biochemistry
>>    New York, NY 10031
>>    ------------------------------------------------------------------------
>>    To unsubscribe from the CCP4BB list, click the following link:
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>> --
>> Nicholas D. Clark
>> PhD Candidate
>> Malkowski Lab
>> University at Buffalo
>> Department of Structural Biology
>> Jacob's School of Medicine & Biomedical Sciences
>> 955 Main Street, RM 5130
>> Buffalo, NY 14203
>> Cell: 716-830-1908
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