I had a discussion about this a few days ago. If the current state of DNA programming is done at the physical level, that's like writing your code by doing photolithography on silicon: not very productive. A level up, maybe the Von Neumann architecture for genetic engineering is the world of DNA and the various proteins like transcriptase. When will we come up with the equivalent Structured Programming? Or Object Orientation? Or Operating Systems?
Each represents an abstraction over the others, and increases productivity.
The level up from DNA is proteins, the molecules that actually do stuff. These are relatively structured:
Primary structure is the amino acid sequence.
Secondary is the structures that from out of the primary sequence:
Helices coil, like DNA except except only a single helix not double. Double and triple helices (see keratin and collagen respectively) are more like winding 2 or 3 single helices around themselves, and
Sheets: two or more strands that bond to each other either parallel or antiparallel.
Then it starts to get interesting. These secondary structures form domains which are the functional subunit of proteins that actually do (or are in the case of non-enzymes) stuff. These are the equivalent of structured programming. E.g. join an antibody variable domain (the bit that stick to stuff) to an enzyme, inject it into the bloodstream and you get expression on the enzyme wherever the antibody happens to bind (e.g. to a cancer cell).
(Tertiary and quaternary structure refer to the complete protein and to proteins that form a functional unit with other proteins respectively.)
The OO analogy is like the OO analogy for HDLs, the protein _is_ an object. OS is whole organism level.
My understanding is we got programmable computers in large part because: 1) a bunch of scientific/engineering advances we were in a position to make were bottlenecked by massive amounts of 'boring' calculations 2) Some of those affected areas related to the war effort in critical ways, so lots of money and resources were poured into solving the problem.
Seems like we're in a similar position with '1' above, in connection with genetic engineering, so demand exists to abstract over and automate the boring stuff. But maybe the problem is significantly harder, or maybe we're just lacking the pressure that would lead to focused/cooperative effort and lots of resources pouring in, like we had in '2'.
> lacking the pressure that would lead to focused/cooperative effort and lots of resources pouring in
Until literally a few months ago, hacking at the level of the protein abstraction was relegated to academics. Then Chimeric Antigen Receptors cured children of cancers, and were approved by the FDA. And so in August, Kite got bought by Gilead for $12B. Then in November Gilead bought another class of multi-domain protein biotherapeutics called SynNotch for $0.5B from an 18 month old startup. And Juno got purchased yesterday for $9B again for their work on CARs - multi-domain protein biotherapeutics.
We'd like to think that such cooperative effort and resources are just starting to pour in. But up until very recently, it was not obvious what the commercial value was when working at such an abstraction layer.
That's interesting to know, thanks. Regarding the 'cooperative' aspect, though—acquisitions might be falling a bit short of the ideal imo ;) But maybe it will be enough.
Each represents an abstraction over the others, and increases productivity.