July Science Chat Date Set

The Date: 21 July 2015 (Tuesday) Add your questions to this post!
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(Wed, 06/24/2015 - 21:26  |  13 comments)
Joined: 04/28/2015
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Good afternoon. Thank you for

Good afternoon. Thank you for your attention to my questions.
1) Why can not we do the most frequent genetic algorithms are combinations of protein? To find the best solutions.
2) If the protein has a common model model - why not make a neural network that will seek solutions based on the total of the best players in action?
3) If I'm in something wrong, or the application of these technologies is impossible to tell why.

Thank you very much.

brow42's picture
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small peptide bidges

Why do small peptides like 2 or 3 bridges? Doesn't 1 bridge already reduce the available conformations (entropy) enormously? Don't 2 bridges have a 50% chance of mis-folding, and 3 bridges 66%-84%?

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A kind of "support" for MS

A kind of "support" for MS HoloLens, to really work in 3D with proteins

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No promises but

...we're actually looking into that. :)

Susume's picture
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Mutate and glycine

Could the mutate function be adjusted to put fewer glycines in? Once a glycine has been in for a while is very hard to get rid of it, and if another amino acid were put in that spot early on the scripts we run would have a chance to adjust things around it and make it fit.

Susume's picture
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Marburg binders

Are you running simulations on our Marburg binders? Will you tell us the results (good or bad)?

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Not really a science issue,

Not really a science issue, but I certainly agree with Aotearoa, Susume, and others that more feedback is necessary. Some of the recent blog posts have been really useful here and it would be great to have a post mortem after each puzzle.

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Feedback

We consider increased feedback on a regular basis an ongoing process, and do want to try to make sure that it stays at a steady level without overtaxing the busy workload of our scientists (who naturally, are the best and most qualified people to write these). :) Thanks for the feedback!

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results or process?

The post a while back about Tony Origami reaching Thermodynamic Lawbreaker status was interesting. First, what constitutes a "move" for record-keeping purposes?

More generally, does the science team look only at the final results, or at the process used to reach the result? There's a list of most-used recipes in CASP 10, so we know statistics can be gathered at the recipe level. What additional information is collected? I can't imagine that foldit central gets a clickstream containing every little change to the protein....

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revisting "revisiting"

As others have requested, it would be interesting to see how the "revisiting" results compare to the originals.

Even more interesting would be to factor in the effect of faster computers and more complex recipes.

Given that foldit has some level of move-tracking (see my previous post), it seems like it might be possible to approximate how much "work" went into a given solution. I'd be curious to know whether the paleo-folders with their primitive stone tools were actually better than today's high-tech script kiddies. (Economists seem to be unable to detect productivity gains from the tech boom, but maybe that's because...they're economists....)

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margins of victory

Many puzzles are decided by only a few points. A difference of 1% in the score can be the difference between 1st and 11th place.

Another It Would Be Interesting: how much do the top-scoring solutions differ from each other, and how far are they from the "native"? Design puzzles may have radically different solutions, but for "revisiting" puzzles and others with a known "native" solution, it seems like this information might actually be useful.

Along these lines, some "revisiting" puzzles have many published solutions with the exact same sequence. How much do these solutions vary? Is there any way to build a consensus model, or are the variations between solutions quite small?

(Of course, we might be straying close to the territory of Interpreting CASP Results...not a place where you find quick, clear-cut answers....)

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core requirements

In the actual universe of known proteins do the cores constitute 33% of the residues, as seems to be required in our design puzzles? Or is there a range going down as low as 20%?

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Proline and H-bonds:

I would like to ask sboyken:

How does proline's backbone nitrogen behave in H-bonding?
Does it lose its H to form a peptide bond, leaving the
exposed N as a hydrogen bond acceptor like one of the N's on
histidine?

See below for more:
http://fold.it/portal/node/2000666#comment-30377
http://fold.it/portal/node/2000666#comment-30572

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