A recent paper in my favourite journal :-) suggests there is no correlation in 
crystallisation conditions even for similar proteins:
http://scripts.iucr.org/cgi-bin/paper?S2053230X19000141 
<http://scripts.iucr.org/cgi-bin/paper?S2053230X19000141>
As you write, surface loops are likely to be different even for similar 
proteins and those are likely to be important for crystal contacts.



> On 23 Jul 2019, at 10:35, [email protected] 
> <[email protected]> wrote:
> 
> I don't think AI will do our job in future as it heavily relies on the 
> crystal structures for training. However, as a community we should embrace 
> this technology/method to help us solve our structures. And why not start 
> with crystallisation? And again the PDB is in a good position here to enforce 
> standards which will pave the way to make use of all the information in the 
> database to train AI. All chemicals must be IUPAC conform an then the PDB can 
> decide about trivial names based on a set of rules for humans (AI doesn't 
> care how you name it as long as it is consistent). No longer those 20 odd 
> names for ammonium sulphate as Janet pointed out years ago.
> 
> 
> And regarding a magic bullet (as in one size fits all), why should a kinase 
> crystallise in the same condition as a polymerase? They do different jobs in 
> a different micro-environment within the cell so their chemical properties 
> will be different. Perhaps there could be some common ground for evolutionary 
> related molecules but a conserved active site doesn't mean a similar surface 
> for crystal contacts which is the key bit in crystallisation, right?
> 
> 


> But as Kay pointed out, crystallisation is a whole field on its own and will 
> go beyond the GRC and the question asked by James.
> 
> 
> M
> 
> ________________________________
> From: CCP4 bulletin board <[email protected]> on behalf of Kay Diederichs 
> <[email protected]>
> Sent: 23 July 2019 08:59:10
> To: ccp4bb
> Subject: Re: [ccp4bb] challenges in structural biology
> 
> If you look at the nice figure at the top of the online article, do you 
> believe that this (or rather, the correct) arrangement of domains/ molecules 
> can be predicted from a couple of correlated mutations, and energy 
> minimization? I think AI is a long way from that.  Finding the correct fold 
> of a compact domain, yes I think it's getting there.
> 
> best,
> Kay
> 
> 
> On Tue, 23 Jul 2019 08:28:42 +0530, Nishant Varshney <[email protected]> wrote:
> 
>> What about AI doing our job in the future?
>> 
>> https://www.nature.com/articles/d41586-019-01357-6?utm_source=Nature+Briefing&utm_campaign=4c1d57fdf3-briefing-dy-20190722&utm_medium=email&utm_term=0_c9dfd39373-4c1d57fdf3-44201949
>> 
>> Best Regards
>> Nishant
>> 
>> On Mon, 22 Jul 2019 at 11:30 PM, Sarah Bowman <[email protected]>
>> wrote:
>> 
>>> I'd like to point out that the MAchine Recognition of Crystallization
>>> Outcomes (MARCO) makes a start to 'deep learning applied to crystallization
>>> outcomes', at least in terms of being able to classify drop images
>>> efficiently.
>>> 
>>> 
>>> 
>>> There is obviously more work to be done to correlate these data with
>>> crystallization cocktail components (which Janet and Tom point out the
>>> difficulties with) and positive outcomes.  It seems the first step really
>>> needs to be consistent descriptions and vocabulary - I fully agree with
>>> Janet here!
>>> 
>>> 
>>> 
>>> Reference on MARCO for those interested: Bruno AE, Charbonneau P, Newman
>>> J, Snell EH, So DR, Vanhoucke V, et al. (2018) Classification of
>>> crystallization outcomes using deep convolutional neural networks. PLoS ONE
>>> 13(6): e0198883. https://doi.org/10.1371/journal.pone.0198883
>>> 
>>> 
>>> 
>>> Cheers,
>>> 
>>> Sarah
>>> 
>>> 
>>> 
>>> *Sarah EJ Bowman, PhD*
>>> 
>>> 
>>> 
>>> Associate Research Scientist, Hauptman-Woodward Medical Research Institute
>>> 
>>> Director, High-Throughput Crystallization Screening Center
>>> 
>>> Research Associate Professor, Department of Biochemistry, University at
>>> Buffalo
>>> 
>>> 
>>> 
>>> Research Webpage <https://hwi.buffalo.edu/scientist-directory/sbowman/>
>>> 
>>> www.getacrystal.org<http://www.getacrystal.org>
>>> 
>>> 
>>> 
>>> [email protected]
>>> 716-898-8623
>>> 
>>> 
>>> 
>>> 
>>> 
>>> *From: *CCP4 bulletin board <[email protected]> on behalf of Bernhard
>>> Rupp <[email protected]>
>>> *Organization: *k.k. Hofkristallamt
>>> *Reply-To: *"[email protected]" <[email protected]>
>>> *Date: *Monday, July 22, 2019 at 1:42 PM
>>> *To: *"[email protected]" <[email protected]>
>>> *Subject: *Re: challenges in structural biology
>>> 
>>> 
>>> 
>>> What about 'deep learning' applied to crystallization outcomes? Can it
>>> guide individual trials better than intuition? Can it find previously
>>> unknown promising combinations on a larger scale?
>>> 
>>> 
>>> 
>>> I think several people were well aware of this need for some sort of sound
>>> machine learning already 15 years ago but we had no cloud based AI
>>> 
>>> services then....maybe it is time to pick this up - particularly if face
>>> recognition can classify the fine detail in faces maybe we finally could do
>>> this with drop images as well...
>>> 
>>> 
>>> 
>>> A summary of the state of affairs then is here:
>>> 
>>> 
>>> http://www.ruppweb.org/cvs/br/rupp_2004_methods_predictive_models_crystallization.pdf
>>> 
>>> 
>>> 
>>> LG BR
>>> 
>>> 
>>> 
>>> 
>>> 
>>> Am 21.07.19 um 23:04 schrieb Artem Evdokimov:
>>> 
>>> Dear Kay
>>> 
>>> 
>>> 
>>> I disagree that 'magic bullet' is impossible. I think the definition is
>>> wrong here - magic bullet to me is a rational set of methods that (when
>>> executed with precision and care) enable crystallization to the maximum
>>> possible benefit. This includes everything - constructs, crystallization
>>> design, etc. Part of the magic bullet is also a precise knowledge when
>>> crystallization is unlikely (i.e. an actual proven predictor that
>>> consistently discriminates between "you're going to succeed if you work
>>> hard" and "it's doomed to fail, don't bother" scenarios in crystallization.
>>> 
>>> The above is not sexy. It does not present itself as a lovely subject on
>>> which to have international cocktail parties with politicians delivering
>>> fancy speeches. But that is what is needed, and no one is funding that to
>>> the best of my knowledge.
>>> 
>>> What needs to be done is a significant amount of testing, standardization,
>>> and methods development from the perspective of holistic outcome (i.e.
>>> crystals that work) - and none of the previously advertised 'magic bullets'
>>> work the way I just described.
>>> 
>>> Having written this, I think you're right - this is a bit of a distraction
>>> from James' original point. However it's a valid opportunity for a lively
>>> discussion on its own :)
>>> 
>>> Artem
>>> 
>>> - Cosmic Cats approve of this message
>>> 
>>> On Sun, Jul 21, 2019 at 4:52 PM Kay Diederichs <
>>> [email protected] <mailto:[email protected]>
>>> <[email protected]%3e>> wrote:
>>> 
>>>     Dear Artem,
>>> 
>>>     black or white is not my way of thinking, which is why I don't
>>> believe in Hannibal's approach when it comes to crystallization.
>>> 
>>>     None of the magic bullets that were advertised over the past decades
>>> have proven generally applicable.  I believe more in incremental
>>> improvement which in this case includes a few biophysical characterization
>>> methods, possibly improved microfluidics or other apparatus, and expanded
>>> screens. And a lot of hard work, perseverance, intuition, frustration
>>> 
>>>      tolerance. Nothing that really needs huge funding - of course it
>>> does need money, but just a  share of what is anyway needed for the usual
>>> lab work including expression, purification, functional characterization,
>>> binding studies and the like.
>>> 
>>>     One area where a huge amount of money was burnt is crystallization in
>>> space, on board of e.g. the spacelab and ISS. This is for me an example of
>>> a mis-led approach to throw money at a difficult problem, with the
>>> expectation of a solution. Science does not work like that, and money in
>>> this case seems more to be the problem than the solution.
>>> 
>>>     This example may illustrate a certain failure of us scientists to
>>> resist the temptation to promise unrealistic outcomes when confronted with
>>> money provided for political reasons, which ultimately undermines our
>>> credibility. But this takes us away from James' points.
>>> 
>>>     best,
>>> 
>>>     Kay
>>> 
>>>     On Sun, 21 Jul 2019 16:06:48 -0400, Artem Evdokimov <
>>> [email protected] <mailto:[email protected]>
>>> <[email protected]%3e>> wrote:
>>> 
>>>> Dear Kay,
>>> 
>>>> 
>>> 
>>>> Even the small, badly diffracting and 'messed up' crystals are still
>>> 
>>>> crystals. There is literally a phase transition (pun very much
>>> intended)
>>> 
>>>> between growing *usable crystals* versus *having no crystals* (or
>>> having
>>> 
>>>> crystals that do not qualify as 'diffraction quality' even under the
>>> most
>>> 
>>>> favorable light). Points 2-9 fall into the 'I have crystals' bucket
>>> and
>>> 
>>>> everything else is in the 'I have no crystals' bucket.
>>> 
>>>> 
>>> 
>>>> I am being deliberately black and white of course.
>>> 
>>>> 
>>> 
>>>> As to whether huge funding would help to bridge the 'phase gap' - to
>>> me
>>> 
>>>> this is a purely theoretical question since to the best of my
>>> knowledge
>>> 
>>>> there never was a 'huge funding' for this particular problem :) And
>>> if it
>>> 
>>>> is true that the general belief in the art is that crystallization
>>> is not
>>> 
>>>> worth investing into because there's no hope in it then of course it
>>> is a
>>> 
>>>> self-fulfilling prophesy.
>>> 
>>>> 
>>> 
>>>> There is an unresolved dichotomy buried in the sentiment above: it
>>> seems
>>> 
>>>> that we (the community of structural biologists) more or less
>>> believe that
>>> 
>>>> crystallization research is not fundamentally fruitful (hence the
>>> 
>>>> no-funding situation). However, anyone who undertakes significant
>>> efforts
>>> 
>>>> to determine an actual structure using crystallography inevitably
>>> *has to*
>>> 
>>>> crystallize their target of interest - and therefore by definition
>>> has hope
>>> 
>>>> that their particular target will work out, against the overall
>>> gloomy
>>> 
>>>> outlook on the crystallization science as a whole. So we either are a
>>> 
>>>> collective of self-induced schizophrenics, or the general sentiment
>>> is
>>> 
>>>> wrong and systematic crystallization research is meaningful and
>>> 
>>>> fruitful - *just
>>> 
>>>> very very hard*.
>>> 
>>>> 
>>> 
>>>> In ~200 BC Hannibal reportedly said "I will find a way or make one".
>>> I
>>> 
>>>> think that if we approach problem #1 with this attitude (and an
>>> equivalent
>>> 
>>>> of a very large army's worth in funding) then it can be solved.
>>> 
>>>> 
>>> 
>>>> Artem
>>> 
>>>> 
>>> 
>>>> - Cosmic Cats approve of this message
>>> 
>>>> 
>>> 
>>>> 
>>> 
>>>> On Sun, Jul 21, 2019 at 1:55 PM Kay Diederichs <
>>> 
>>>> [email protected] <
>>> mailto:[email protected]> <[email protected]%3e>>
>>> wrote:
>>> 
>>>> 
>>> 
>>>>> Hi Artem,
>>> 
>>>>> 
>>> 
>>>>> you are certainly correct in that James' points 2-9 would be moot
>>> if his
>>> 
>>>>> point 1 were solved. But as long as this is not the case, we
>>> resort to work
>>> 
>>>>> with few and/or small and/or badly diffracting and/or
>>> non-isomorphous
>>> 
>>>>> crystals, which makes points 2-9 very relevant.
>>> 
>>>>> 
>>> 
>>>>> Maybe the reason why crystallization research is not well funded
>>> is that
>>> 
>>>>> it is not expected to yield significant improvements. Personally,
>>> I think
>>> 
>>>>> that even huge funding would not result in methods that succeed in
>>> 
>>>>> crystallizing all molecules.
>>> 
>>>>> 
>>> 
>>>>> best,
>>> 
>>>>> Kay
>>> 
>>>>> 
>>> 
>>>>> On Sun, 21 Jul 2019 11:28:14 -0400, Artem Evdokimov <
>>> 
>>>>> [email protected] <mailto:[email protected]>
>>> <[email protected]%3e>> wrote:
>>> 
>>>>> 
>>> 
>>>>>> Excellent question :)
>>> 
>>>>>> 
>>> 
>>>>>> First of all, thank you for putting this out to the community!
>>> 
>>>>>> 
>>> 
>>>>>> Secondly, I agree with several of us who've written that a single
>>> 
>>>>>> conference is not enough to discuss all the possible topics.
>>> 
>>>>>> 
>>> 
>>>>>> Thirdly, in my opinion all the other problems are secondary to
>>> the main
>>> 
>>>>>> (and only remaining!) problem in crystallography: getting
>>> 
>>>>>> diffraction-quality protein crystals reproducibly and quickly
>>> 
>>>>>> 
>>> 
>>>>>> The amount of funding for serious crystallization research seems
>>> to be
>>> 
>>>>>> close to non-existent. In general methodology funding is hard to
>>> get, but
>>> 
>>>>>> crystallization seems to me like the absolute underdog of the
>>> method pool
>>> 
>>>>> -
>>> 
>>>>>> the true 'red headed stepchild' of the methods development
>>> funders.
>>> 
>>>>>> 
>>> 
>>>>>> At risk of repeating myself - the other problems (worthy,
>>> significant, and
>>> 
>>>>>> urgent as they are!) are subservient to the main issue at hand -
>>> namely
>>> 
>>>>>> that crystallization remains an unpredictable and artful
>>> phenomenon while
>>> 
>>>>>> literally all other aspects of structure determination process
>>> (the gene
>>> 
>>>>> to
>>> 
>>>>>> structure pipeline, whatever you might call it)have made
>>> astronomic leaps
>>> 
>>>>>> forward.
>>> 
>>>>>> 
>>> 
>>>>>> Artem
>>> 
>>>>>> - Cosmic Cats approve of this message
>>> 
>>>>>> 
>>> 
>>>>>> 
>>> 
>>>>>> On Mon, Jul 15, 2019 at 3:44 PM Holton, James M <
>>> 
>>>>>> [email protected] <
>>> mailto:[email protected]>
>>> <[email protected]%3e>> wrote:
>>> 
>>>>>> 
>>> 
>>>>>>> Hello folks,
>>> 
>>>>>>> 
>>> 
>>>>>>> I have the distinct honor of chairing the next Gordon Research
>>> 
>>>>>>> Conference on Diffraction Methods in Structural Biology (July
>>> 26-31
>>> 
>>>>>>> 2020).  This meeting will focus on the biggest challenges
>>> currently
>>> 
>>>>>>> faced by structural biologists, and I mean actual real-world
>>> 
>>>>>>> challenges.  As much as possible, these challenges will take
>>> the form of
>>> 
>>>>>>> friendly competitions with defined parameters, data, a scoring
>>> system,
>>> 
>>>>>>> and "winners", to be established along with other unpublished
>>> results
>>> 
>>>>>>> only at the meeting, as is tradition at GRCs.
>>> 
>>>>>>> 
>>> 
>>>>>>> But what are the principle challenges in biological structure
>>> 
>>>>>>> determination today?  I of course have my own ideas, but I feel
>>> like I'm
>>> 
>>>>>>> forgetting something.  Obvious choices are:
>>> 
>>>>>>> 1) getting crystals to diffract better
>>> 
>>>>>>> 2) building models into low-resolution maps (after failing at
>>> #1)
>>> 
>>>>>>> 3) telling if a ligand is really there or not
>>> 
>>>>>>> 4) the phase problem (dealing with weak signal, twinning and
>>> 
>>>>>>> pseudotranslation)
>>> 
>>>>>>> 5) what does "resolution" really mean?
>>> 
>>>>>>> 6) why are macromolecular R factors so much higher than
>>> small-molecule
>>> 
>>>>>>> ones?
>>> 
>>>>>>> 7) what is the best way to process serial crystallography data?
>>> 
>>>>>>> 8) how should one deal with non-isomorphism in multi-crystal
>>> methods?
>>> 
>>>>>>> 9) what is the "structure" of something that won't sit still?
>>> 
>>>>>>> 
>>> 
>>>>>>> What am I missing?  Is industry facing different problems than
>>> 
>>>>>>> academics?  Are there specific challenges facing electron-based
>>> 
>>>>>>> techniques?  If so, could the combined strength of all the
>>> world's
>>> 
>>>>>>> methods developers solve them?  I'm interested in hearing the
>>> voice of
>>> 
>>>>>>> this community.  On or off-list is fine.
>>> 
>>>>>>> 
>>> 
>>>>>>> -James Holton
>>> 
>>>>>>> MAD Scientist
>>> 
>>>>>>> 
>>> 
>>>>>>> 
>>> 
>>>>>>> 
>>> ########################################################################
>>> 
>>>>>>> 
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>>>>>> 
>>> 
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