Re: [DIYbio] Protein Categorization

I may have worded this poorly, I'm currently just looking for the core dimensions and their scale+span.  The NP-hard folding problem still remains, even the NP-hard chunking problem (or clustering) for actual simulation in silica still remains - the issue I'm trying to resolve at the moment is purely based around addressing.  I.e. a unique identifier consisting of a structure similar to: { sequence, chunk, pH, salinity, etc } which is able to comprise all or at least nearly all we've observed in as few bits as possible.  I know the dimensions involved are based on the structure (sequence and chunking, though chunking is largely covered via the use of MSM Builder,) but the possible conformations of importance beyond that are finite but definitely spread across multiple dimensions (e.g. any temperature over 1,000 C might as well be considered the same and 0.0000001C of difference between the conditions while folding a protein is almost certainly not going to yield anything different from 0.000001C of difference) but how finite those dimensional spans and scales can be is the crux of this problem.  I get what you and Skyler are saying about microfluidics for testing, but I'm trying to derive this from known data (way too many ongoing projects to try to engineer a microfluidic chip then spending decades and millions if not billions of dollars running enough proteins through it to get an exact value,) which is why I'm aiming for knowledge pulled from people who have more experience with this than myself.  If it hits 99.9% of protein conformations for a given protein within a bioengineering application it will pass the good enough test in my opinion.

On Friday, December 8, 2017 at 10:12:16 AM UTC-5, John Griessen wrote:

On 12/08/2017 08:41 AM, Cory J. Geesaman wrote:
> I don't get why companies designing recombinant proteins specifically would want it,) any idea of the pH scale required to get
> good coverage?

Because once you knew such data points for a range of proteins you would shorten the trial and error of designing
proteins with similar conditions.  You'd start to be able to treat proteins like a key to a lock, and know which detent position
on the key you were working with.  That would be input to synthesis.

Getting the data on folding needs some kind of observation of folding states though.  Visual observing of it probably is not very
easy, so not very useful.   Some kind of test, which is why Skyler Gordon was saying get knowledge on microfluidic physics for
corralling molecules, would be a help for categorizing.  I can only see it being done by automaton that moves protein molecules
through microscopic chambers of conditions that fold and unfold and also with some detector of folded state.  The you could relate
the basic conditions to how the folding happens in presence of other molecules -- the normal way catalyze reactions, but since you
will get observations 2 ways you'll have a rosetta stone to decode more...