comment by Spiracular ·
2020-12-01T19:11:19.949Z · LW(p) · GW(p)
That is the dream. The reality is harder, and the combinatorics are not friendly.
In practice, trying to "catch 2 proteins hanging out together" has usually been easier.
The main way we actually check to see if 2 proteins are interacting is... well, this metaphor is fun.
We try to work out which proteins are a couple, by trying to catch the proteins holding hands at the school dance. Either by freezing them, or sticking glue on their hands.
Sometimes even dragging one of them out of the school dance, and then checking to see if the other one tagged along.
Or if you already have a pretty good guess, try just grounding one of them and see if the other one starts acting weird.
I guess this turns the simulation method into "computer-modeling which people are likely to end up in a relationship together" which... seems to capture some of the right intuitions for how hard it is, and how much knowing "they were present in the same place at the same time" matters (whether they had an opportunity to meet in a cell type & cell compartment; something protein-shape doesn't tell you). Watching for hand-holding has typically been easier.
Un-metaphoring: there's multiple variants of this broad class of technique, and there's even a variant of it for DNA-DNA, DNA-protein, or RNA-protein interactions.
Here's some slightly-de-metaphored executions:
- Glue: A chimeric-protein with a sticky-end (and then isolating one of the proteins in a binding column, and checking what else tagged along).
- Freeze: Chemicals that halt cellular processes and cause semi-random-binding (ideally reversible) of things that happen to be next to each other whenever you took the freeze-frame.
- Grounding: Here that means either altering, removing, or silencing one protein, to see how it affects the behavior of another.
And of course, whenever you do this, you still have to do: isolating, sequencing, and identifying the batch of proteins you've nabbed.
comment by Vanessa Kosoy (vanessa-kosoy) ·
2020-12-01T21:14:52.427Z · LW(p) · GW(p)
Yes, I do know the physics involved on some level, and some about the computational methods.
I think that, if deep learning can predict protein folding then it should eventually be able to predict protein binding as well, since most of the physics is the same: it's just amino acids on two different peptide chains interacting, instead of amino acids on the same chain.
On the other hand, predicting which reaction an enzyme catalyzes involves more physics, so it could be much harder: but then again, maybe it isn't. Or maybe we can at least predict with which biomolecules a given protein is likely to react and do experimental work to find out the details.