[DIYbio] Article: The Feds Are Officially Cracking Down on Basement Biohackers

https://gizmodo.com/the-feds-are-officially-cracking-down-on-basement-bioha-1820682025

Seems to instigated by DIY gene therapy, but could make for an interesting discussion.

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Re: [DIYbio] Protein Unfolding Algorithms?

People have used Rosetta both ways. For example, the "game" foldit uses rosetta + human intuition to figure out how proteins fold given the sequence. However, the bigger goal of Rosetta is to design new proteins. You start with a desired function/reaction -> define a topology or active site geometry to catalyze the reaction -> find an overall protein fold that can accommodate the active site -> optimized sequence -> make and test the new protein.

" it seems the only thing really missing (aside from likely lots of computing power to compile anything) is the ability to go from a desired structure to the DNA which codes for that structure"
It's even less than that. It's very straightforward to go from desired protein sequence -> DNA sequence, although you might need some optimization in terms of promoters and the like to optimize expression levels. So the only really hard step is going from desired docking or structure to protein sequence. That's exactly what Rosetta is for. I think it's the best there is for doing this, however, it's still not that great. It typically requires trying dozens of designs to find one protein that does the desired job even very poorly.

Here's a good paper that discusses how to use Rosetta to design new enzymes: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0019230 

On Wed, Nov 22, 2017 at 12:11 PM Cory J. Geesaman <cory@geesaman.com> wrote:
To put it another way, think of the arbitrarily stupid use case: sharks with laser beams coming from their eyes.

You would need a way to create proteins which either are covered in quantum wells, or which assist in the construction of a planar surface of quantum wells, with the required metallic traces to power the thing, in addition to cells designed to get the electricity needed to power it (forgoing the possibility of chemical or dye lasers for this example even though they might be easier.)  Then you would need new amino acids (think things like Selenocysteine which replaces a stop codon in some organisms to create an AA with a Cysteine-like structure replacing a Sulfur atom with a Selenium atom) to allow for the structure of the actual quantum wells.  At that point (assuming you've worked out the building blocks required to get the desired elements into side chains) you could seed the cell with the appropriate mRNA components and conceivably build it, but you still have the really big problem of going from "this is the structure I need" to "this is the DNA which codes for the protein which will fold into that structure, given the prerequisite materials."

I'm trying to build an IDE which lets you use abstract concepts ("replicate N times, differentiate into these cell types, take on this superstructure, etc") to compile DNA, ultimately to compile complete chromosomes and organisms.  Awhile back I was trying to tackle this from the standpoint of semantic search type methodologies against DNA as a whole, but after learning a bit more about the structure of DNA and the way it functions within an organism it seems the only thing really missing (aside from likely lots of computing power to compile anything) is the ability to go from a desired structure to the DNA which codes for that structure, everything else is either already built (e.g. DNA printers) or a relatively straightforward adaptation of computing (e.g. the abstractions involved, creating a system of compatible docking sites without overlap, etc.)


On Wednesday, November 22, 2017 at 10:22:55 AM UTC-5, Bryan Jones wrote:
Cory, I'm not sure if I completely follow your logic, but it sounds like you might be describing something like Rosetta, which can be used to design proteins from scratch based upon a given fold/topology or desired active site. It's far from perfect but keeps getting better. There are lots of people working on it, but the Rosetta project is spearheaded by David Baker at the University of Washington. I'm not sure if it is open source, but it is at least free to use for personal or non-profit uses.
You can check it out here: https://www.rosettacommons.org/software
Here's one recent paper that used Rosetta to design a new TIM barrel protein:

On Wed, Nov 22, 2017 at 3:11 AM Cory J. Geesaman <co...@geesaman.com> wrote:
So this might seem outright insane given the computational requirements of protein folding, but I had a though I'm not able to locate any existing resources on, but could be the basis for an actual biotech boom (i.e. not just copying and pasting stuff, but creating things.)

The concept would be, to start: take a desired topology, stick it in the computer, have the computer generate a matching docking profile, then run a sort of protein unfolding algorithm to generate a best fitting protein for that docking profile.  Eventually add in things like active sites, inhibition sites, any special functionality (e.g. what part of the protein should flex when something is docked in some arbitrary site, which direction should it flex, should it just change shape, or open another site for access to some thing to dock in it, or eject something from another site, etc.)

I figure starting with the topology --> docking site --> protein --> DNA piece would be a really good start and would likely be pretty useful, but then adding in the other stuff would be the basis for a code --> DNA compiler (or one of the smaller units of a really powerful biological IDE which could let you build complete systems from proteins on up through organs and transmitters and such.)

Any thoughts on this welcome (especially if some or all of this already exists in an open source manner I can hack on.)  Decided to heat my house this winter by running Folding@home but the curecoins generated are still $3/day in the hole for electricity so I might as well play with other computationally intensive genomics.

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