Dear James,
Well, 100,000 genes used to be the estimate of the size of the human genome.
(eg see 
https://physicsworld.com/a/protein-crystallography-the-human-genome-in-3-d/ )
It seems it has got easier, albeit still gargantuan, at ~30,000 genes to be 
expressed into proteins.

Meanwhile funding agencies also look out for Big Ideas:-
https://epsrc.ukri.org/research/ourportfolio/epsrcbigideas/?utm_source=Twitter&utm_medium=social&utm_campaign=SocialSignIn
and even helpfully spell out the difference between a Big Idea and a Grand 
Challenge!
Maybe an “Open Door for funding” for us all?

Today also the repertoire of methods capable of resolving in 3D protein 
structures has expanded further with the splendid development of cryoEM. 

To define challenges in terms of projects, as Max Perutz taught us 
(“Haemoglobin the Molecular Lung”) avoids methods looking for problems.

Also a final thought, how we organise ourselves in different areas of the World 
varies according to our cultural traditions. So the Big Project is neutral to 
politics and can accommodate all contributions however so arrived at.

“What shall we do with it?”
As Darwin taught us, first make your Collection......

Greetings!
John 


Emeritus Professor John R Helliwell DSc
https://www.crcpress.com/The-Whats-of-a-Scientific-Life/Helliwell/p/book/9780367233020



> On 18 Sep 2019, at 22:15, James Holton <jmhol...@lbl.gov> wrote:
> 
> Thank you John, an excellent choice as always.  Here is your trillion 
> dollars!  Now, what are you going to do with it?
> 
> Do you think simply scaling up current technology could reach this goal?  
> More screens, more combinations, more compute cycles?  Remember, if you want 
> the "genome/proteome" you need all of it, including all those super-cool 
> human membrane proteins we gave up on because they were too hard.  
> 
> I think we all have at least one of those projects in our past.  What was the 
> show-stopper in the end?  Did they just not grow crystals? Poor diffraction? 
> Weird diffraction? Twinned? Won't phase? Won't refine to a decent R factor? 
> Annoying reviewer? Did you try cryoEM? NMR? and did they not work either?
> 
> I think a key question for all of us is: what new capability would make you 
> decide to go back and pick up your old favorite project again?  Without your 
> structure, the genome is incomplete.
> 
> -James Holton
> MAD Scientist
> 
>> On 9/16/2019 12:24 AM, John R Helliwell wrote:
>> Dear James,
>> Here you go, a “grand challenge” suggestion to consider for funding from the 
>> “James Holton Foundation for structural biology research”:-
>> “The human genome/proteome in 3-D”
>> Greetings,
>> John 
>> Emeritus Professor John R Helliwell DSc
>> 
>> 
>> 
>> 
>> On 14 Sep 2019, at 02:39, James Holton <jmhol...@lbl.gov> wrote:
>> 
>>> 
>>> I would like to thank everyone who took the time to respond to my question 
>>> that started this thread.  It is really good for me to get a sense of the 
>>> community perspective.  Some debates were predictable, others not.  Many 
>>> ideas I agree with, some not so much.  All were thought-provoking. I think 
>>> this is going to be a really good GRC!
>>> 
>>> Something I did not expect to distill from all the responses is that the 
>>> dominant challenge in structural biology is financial. The most common 
>>> strategy suggested for addressing this challenge was torpedoing other 
>>> scientists in similar fields, perhaps expecting to benefit from the 
>>> flotsam.  Historically, this strategy is often counterproductive and at 
>>> best inefficient. The good news is there is a lot of room for improvement. 
>>> In reality, we are all on the same ship, and the people in our funding 
>>> agencies fighting to get us what we need can be much more effective when 
>>> armed with positive ideas and clear plans.  That is a better strategy for 
>>> overcoming this challenge.
>>> 
>>> To this end, my first GRC session title is going to be:
>>> 
>>> "If I had a trillion dollars for structural biology"
>>> 
>>> I think we can all agree that science in general is vastly under-funded 
>>> relative to the impact it has on the human condition.  For example, I 
>>> estimate the value of a general cure for cancer to be at least a trillion 
>>> dollars.  This is based on the lives claimed every year, multiplied by how 
>>> much one person would gladly pay after being diagnosed (amortized over the 
>>> rest of their much longer life). This is only ~1% of the Gross World 
>>> Product, a real bargain if we can come up with a plan that will actually 
>>> work. 
>>> 
>>> Now, obviously not all cancer research is structural biology, but not all 
>>> structural biology is cancer research either. Let us suppose for a moment 
>>> that you (yes, I'm talking to YOU), were given a trillion-dollar budget to 
>>> do your science.  After buying all the tools and hiring all the people you 
>>> wanted: would that solve all of your problems?  I expect not. The 
>>> intellectual and technical challenges that remain are what I believe 
>>> science is really all about, and the 2020 Diffraction Methods GRC will 
>>> focus on the ones facing structural biology.  
>>> 
>>> My goals here are twofold: 
>>> 1) I believe it would be healthy for this field if we all spent a little 
>>> time "thinking big"
>>> 2) I want to remove financial anxiety from the discussion, both here and at 
>>> the GRC.
>>> 
>>> I ask for one restraint: please confine the discussion to structural 
>>> biology.  I understand it is difficult to think about the trillion-dollar 
>>> level without involving politics, but the CCP4 Bulletin Board is not a 
>>> political discussion forum, and neither is the GRC. Assume all the other 
>>> worthy causes in the world are given their own ample budgets. This trillion 
>>> is yours, and you have to spend it on structural biology.  If you can't 
>>> think of anything, think harder.
>>> 
>>> To get you started, a few things that could be done for under a trillion 
>>> dollars:
>>> 1) re-do all the protein crystallization in the PDB, 500 times (saving all 
>>> information)
>>> 2) buy Google and Facebook, get their AI teams to do machine learning and 
>>> structure prediction for us
>>> 3) hire every "biological scientist" in the world, and give each $1M to 
>>> work on your projects
>>> 4) re-do the NASA Apollo program three times
>>> 5) build 1000 XFELs and 100,000 Titan microscopes (yes, that's "and")
>>> 6) solve the phase problem by brute force.  (zettaflops-scale computing at 
>>> $0.03/gflop)
>>> 7) build half a dozen terapixel detectors (ask Colin Nave what those can do)
>>> 8) fund every NIH grant submitted in the last 5 years. Not just the awarded 
>>> ones, all of them.
>>> 9) X-prize style competitions for landmark achievements, such as predicting 
>>> crystallization outcomes, or finding a universal way to stop protein from 
>>> denaturing on the air-water interface.
>>> 
>>> This is not a to-do list, but rather an attempt to convey the scale of what 
>>> can be done.  Oh, and you have a month or so to think about it. The meeting 
>>> is July 26-31 2020, but my speaker list is due Oct 15.
>>> 
>>> Now, of course, at the GRC I will not actually have billion-dollar prizes 
>>> to pass around, but I do want to set our sights on those lofty goals, and 
>>> then work on the bridge we will need to get there.
>>> 
>>> So, when I say "challenge" I mean more than something we all agree is hard. 
>>>  Those would make for very short talks.  I am after something more like a 
>>> benchmark.  Useful challenges should have certain properties.  They should 
>>> be:
>>> a) possible, because something that doesn't work no matter what you do is 
>>> no fun.
>>> b) hard, because something that is too easy is also not very interesting
>>> c) realistic, as in relevant to a real-world problem we all agree is 
>>> important
>>> d) accessible, as in reasonable download sizes and/or affordable reagents
>>> e) fast, because it if takes forever to try it nobody will have time to 
>>> participate
>>> f) measurable, as in having a clear and broadly acceptable "score" 
>>> g) adjustable, as in the level of "difficulty" can be selected continuously 
>>> between "easy" and "impossible".  
>>> 
>>> This last one is important because it is at the transition point between 
>>> success and failure that teaches us the most about what can be improved. 
>>> 
>>> Some challenges that already exist are:
>>> anomalous phasing from weak signals
>>>     https://bl831.als.lbl.gov/~jamesh/challenge/anom/
>>> anomalous phasing from twinned data
>>>     https://bl831.als.lbl.gov/~jamesh/challenge/twin/
>>> merging highly incomplete data with an indexing ambiguity
>>>     https://bl831.als.lbl.gov/~jamesh/challenge/microfocus/
>>> extracting motions from diffuse scatter data
>>>     https://bl831.als.lbl.gov/~jamesh/challenge/diffuse/
>>> Coming soon:
>>> dial-a-resolution model building challenge
>>> XFEL data processing reference set
>>> 
>>> -James Holton
>>> MAD Scientist
>>> 
>>>> On 7/25/2019 10:07 AM, Keller, Jacob wrote:
>>>> >>It would seem to me that an important issue is also: do get all 
>>>> >>information out of our diffraction data? By integrating the Bragg peaks 
>>>> >>we usually neglect the diffuse scattering that could potentially contain 
>>>> >>additional (dynamic) structural information. This can be cloudy diffuse 
>>>> >>scattering hidden in the background but also diffuse streaks that 
>>>> >>contain information on packing disorder and reveals intrinsic 
>>>> >>interactions in the crystal.
>>>> 
>>>> Along these lines, and taking a page from you also, how about 
>>>> “crystallographic model refinement as image-faking?” Metrics of the 
>>>> goodness of a particular refinement could simply be some measure of the 
>>>> correlation between predicted vs. measured images. I have seen some of 
>>>> this done with diffuse scattering, but why not with the whole thing, 
>>>> including intensity and shape of Bragg peaks, solvent rings, etc? Maybe 
>>>> instead of doing the multiple steps of (indexing, integration, scaling, 
>>>> solving…) all of this could be refined as one? Processing parameters like 
>>>> moscaicity [sic] etc would now be part of the final model…?
>>>>  
>>>> JPK
>>>>  
>>>>  
>>>>  
>>>> 
>>>> Loes Kroon-Batenburg
>>>> 
>>>> On 07/15/19 21:44, Holton, James M 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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>>>> 
>>>> 
>>>> 
>>>> -- 
>>>>  
>>>> __________________________________________
>>>>  
>>>> Dr. Loes Kroon-Batenburg
>>>> Dept. of Crystal and Structural Chemistry
>>>> Bijvoet Center for Biomolecular Research
>>>> Utrecht University
>>>> Padualaan 8, 3584 CH Utrecht
>>>> The Netherlands
>>>>  
>>>> E-mail : l.m.j.kroon-batenb...@uu.nl
>>>> phone  : +31-30-2532865
>>>> fax    : +31-30-2533940
>>>> __________________________________________ 
>>>>  
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>>>> 
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>>> 
>>> 
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