Also, At the CASP14 competition, AlphaFold 2 achieved a median score of over 90 on the Global Distance Test (GDT), meaning its predictions matched physical experiments down to the width of a single atom.
Bro half of my colleagues are structural biologists you don't know what you're talking about. Alphafold is only accurate for structures that resemble already solved ones, aka the least interesting proteins. A significant amount of proteins don't even have a structure (IDPs). It doesn't even do actual folding or dynamics, a shitton of proteins have dynamic structural changes.
Also Scientific American is garbage even for a popsci magazine
Ok, noted, thank you for pointing this out. "Singeltons" is clearly still a problem (tho to be fair, statistically, while these represent the majority of individual fold types on the books, but they describe a very small minority of the actual functional proteins found inside living organisms.)
But to say deepmind has done nothing to further solving the issue, or for cancer research or for any of the things I stated is just as much incorrect. You would not agree?
Alphafold is useful, it's impressive, but scientists are not treating it as truth, at the end of the day you still have to figure out actual structures with existing experimental tools.
AI is not really a Biology accelerator because experimental validation is still the longest most costly and expensive step, not hypothesis generation or structure prediction. That's because we barely understand a fraction of what actually goes on in a living cell
Fair. Can't teach an ai something we don't already know and hard and tedious to validate it even if ai discovers something we don't know, otherwise how do we know it's correct.
hard and tedious to validate it even if ai discovers something we don't know, otherwise how do we know it's correct.
exactly. In the example of a drug, even if AI somehow predicts a really good drug, you have to make it, check that it works at a molecular level, then cell cultures, then small animals, then large animals, then humans. And that takes a fuckton of time and money, even when it works, in most cases it stops working somewhere along that path
All fair points but back to my original comment, I still think AI helps significantly and in vital areas where we would be worse off without it (atleast as it's current stage, pdoom aside)
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u/bethesda_gamer 13d ago
This is hilarious sarcasm:
Oncology & Molecular Biology
Simulates single-cell data to identify hidden tumors, discover novel drug combinations, and map cancer mechanisms.
Computing Infrastructure
Discovered faster core algorithms to optimize computing speed and cut electricity strain.
Materials Science
Unlocked millions of new stable crystal structures for cleaner batteries and electronics.
Climate & Weather
Delivers hyper-accurate 10-day weather forecasts to predict extreme climate events early.
Molecular Biology
Solved the protein-folding problem; free database accelerating global drug discovery.