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Are there any molecular biologists here? I'm curious: what happens to society if/when we figure out protein folding? Hypothetically, how does the world change if we had a 100% accurate way to model quaternary structure from primary structure?


My brother worked in protein folding (although his statement about specifically AlphaFold was years after he left that field) but I showed him the AlphaFold results from like 5 years ago and his reaction was "oh ... Yeah they solved protein folding"

So at least according to him we've lived in that world for the last 5 years.

As a person working with / tangentially to people in the same field I would say that it's made things faster and more scalable, but protein structure isn't the be all end all of things. Researchers use AlphaFold a lot for filtering potential candidates, but that is only one step in a lot of steps. A SNP mutation -> protein structure change -> functional change is already difficult without then considering that the vast majority of mutations that create function change in humans are not in exons, so something like AlphaFold (in the form I'm familiar with) would be useless for those as well.

Eventually though an AI system that can go mutation->function change is entirely possible, although it is much much further in the future. In that case though I think you'll be quite close to a future where combined with things like CRISPR therapeutic treatment for all heritable disease would be possible.


AlphaFold did not solve protein folding. You can tell this is the case because it doesn’t correctly model structures with missense variants.

AlphaFold is a huge advance and people are extending it to try to tackle this (eg AlphaMissense) but to say it solved protein folding is hyperbolic.


>"AlphaFold can do in TEN MINUTES what a PhD dissertation required, fifteen years ago."

Quoting a PhD immunologist from Texas, who uses AlphaFold daily.


Agreed - and this is not in tension with my comment whatsoever.


Is that not the same as saying maths is solved thanks to spreadsheets/excel? All of science and technology is to some extent automation and increased speed of what used to be slow and laborious.


My sincerest response is that we are now post-moore's-law[1]; instead of "transistor density doubling every 18 months," I have (over the past year of Perplexity.AI) more of the belief that "global intelligence will double every 18 months."

Just my ¢¢ half-sanity.

[1] Isn't a single hydrogen diatom just 1nm wide? How much smaller can transistor gates be safely assembled? Didn't we physically stop getting physically smaller around 14nm?


I heard a lot of different opinion about AlphaFolding, how it's not revolutionary or not revolutionary, or something like that.


It is revolutionary in what it does. There's no question about it. The problem is that a lot of people think it does something different or more practical, like creating new drugs. That is one of the ultimate goals, but it's way down the road.


Counting down to dekhn appearance in 3…


Uh ok. Now I feel obliged to say that AlphaFold is the obvious outcome you'd get from having a company dedicated to winning games deciding to win at CASP.

To me, "solving" structure prediction (explicitly acknowledging there are areas where AF doesn't make accurate predictions), is a clear and satisfying win, although it still doesn't answer some of the fundamental physics questions around folding.

I am glad to see the existence proof but want to see more outcomes; in particular, I'd like to see a lab-in-the-loop that actually produces something of high value (higher than the cost of building the lab-in-the-loop).


A lot of things become simpler, but hard problems remain. In the cell, a structure of a protein is the result of its sequence and all the other environmental conditions (cofactors, ligands, binding partners, lipids,…), and furthermore, the structure is a dynamical construct, so it can change over time. So the main advance for society is when we can accurately predict how to jam or unblock a machine in a cell without influencing all the other machines in a cell. The essential pieces of this puzzle are the possible shapes of the pieces that make up the machines and AF2 gives you those. But the puzzle is huge. And very important.


Even if we had a perfect library of useful proteins and their utilities, the composition of these protiens, and the emergent behaviour within "machines" made by them, would be complex enough to be handfuls of classes of new engineering altogethor.

I think its like saying "we know how to make bricks and iron and bolts now, shouldnt it be easy to make a full scale functioning replica of the greater tokyo metropolitan area?"

Even if you came up with a spec for a complex tissue or just a fluid that functions as a standalone chemical factory, you would need to fabricate it. However many specific protiens from your library, in specific ratios, mixed and maybe even... positioned.

In short protein folding is just the first fundamental step towards this print any biological design out of proteins world that I guessed you are alluding to.


It would not have a huge practical impact in the short term. There are many steps from figuring out protein folding to figuring out new, effective and safe drugs. Here's a good Nature article discussing just that: https://archive.is/4QNKy


We could do computer-only search for enzymes that catalyze desired reactions in enzyme-friendly reaction environments. Assuming that the way that makes the above 100% accurate also yields us the tooling to simulate the candidates in operation accurate enough to let the search/optimizer learn from the simulation feedback.


The static shape of a protein doesn't automatically give you a prediction of its functional properties. There's a hell of a lot more biophysics going on that we have no predictive models for that are needed to understand catalysis, allostery, assembly, etc etc etc. We don't even have good comprehensive data for any of that (compared to sequences or structure) to model with.

Fold prediction is an incredibly useful tool for scientists and genetic engineers to help design new proteins, but it doesn't magically solve molecular or cell biology. Designing new functions and mechanisms is still going to involve a huge amount of labor and brute-force experimentation.


okay so the prevailing sentiment seems to be: a) We kind of already have b) it's a big deal but not that big of a deal because knowing the precise protein structure does not become useful until you know how that structure interacts

So my takeaway is that we just need sufficiently advanced quantum computers that can do molecule-level simulation on a large cell, THEN we'll be there.


there was a talk about this a few days ago https://media.ccc.de/v/37c3-12061-alphafold_how_machine_lear...




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