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dungone t1_ja3p4db wrote

Nothing much. People were already doing this for 50 years. Using computers and using machine learning, too. Generating millions of random protein formulas is the easy part. The hard part is manufacturing them and testing them because that's still like looking for a needle in a haystack. But by improving the machine learning approach, it gave the researchers a smaller haystack.

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reconrose t1_ja3sm32 wrote

Yeah the other comments here talking about how this is revolutionary / terrifying make me roll my eyes because they act like we haven't been doing similar research for a long time. These tools just might make the process more efficient.

It's very exciting seeing ML put to tasks that open up new possibilities vs making current tasks simpler.

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MysteryInc152 t1_ja3udcd wrote

It's novel because this is Large Language Model and not a NN designed to formulate proteins. The fact that it can is extremely interesting and telling. You can't exactly talk to AlphaFold.

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dokushin t1_ja5qazz wrote

Hah; no. What we've been doing is a form of incremental improvement, taking existing proteins and modeling a single fold in an attempt to evolve a new one, gradually forcing the protein towards some desired property. We've been largely unable to design proteins from the ground up and have them actually work.

This thing just up and spat out thousands of functional proteins from scratch, which is unheard of. There are proteins solving the same problem with completely different structures. Just one of those novel, functioning proteins is the end goal of everything we've been trying to do for decades. This is pretty incredible.

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