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…Right? We've made this widely available, and scientists are using it like crazy. It's absolutely amazing. You have released a database of all of these proteins and the map lit up. So now scientists from all around the world, they can access these protein structures for many downstream tasks. But to bring this to life, you know, we have proteins doing things in the body and we can use these structures, and we could do things like drug discovery and and and whatnot. But what what's the gap? So so what can people do now that they have these structures? I think the right way to think about this is it's a starting point for biological research. If you think about what what people do, what are some beautiful studies that people have done, you know, we we see it all the way. 1 that just came out was scientists trying to understand how cholesterol is moved about in the body. Right? What what actually is the thing that takes cholesterol and moves it from 1 place to another? How might mutations in that affect high cholesterol, heart disease, etcetera? There's this beautiful weird protein that kind of wraps around it in a shape that we really didn't know until a few months ago when this paper came out. And what they were able to do actually is a it's 1 of the ways in which scientists, I think, really commonly use alpha fold is they use both experimental techniques and AlphaFold. So they used an experimental technique, cryo electron microscopy, to take an incredibly blobby picture. You know, they used to call cryo EM blobology. It's gotten much better, but it's an incredibly kind of rough picture. And they don't really know the atomic details. And then they also run AlphaFold, and they see, well, actually, AlphaFold has this shape that almost exactly fits within this kind of blob. And so you get both confirmation and more detail, and suddenly you have this beautiful atomic model where you can start to then go and say, now how where are the changes in this protein? What might it affect? How might it affect how it takes cholesterol from 1 place to another? Then you have to go figure out. Now how do I make drugs for this? Do I I bind to this protein? I think when you see it in drug development, there's actually kind of 2 or 3 ways in which it's used. I mean, the 1st I will say is that the hardest part of drug development is that we do not know how biology works very well, right? That it's not, you know the thing preventing us from curing, say, I guess, autism, right, is not that we know exactly 1 protein. If we just had its structure, then autism would be cured. It's a huge disease that involves the whole body. And so we kind of are trying to unwrap and unravel biology well enough to figure out which proteins. How do these proteins interact? How does that ultimately contribute out to these phenotypes? And so people do biology across all these length scales. And the contribution of AlphaFold is to say, this protein, for example, that you didn't even know was important. Like, there was oh, 1 study from a few years ago was on a pro was you know, there's all sorts of recycling mechanisms in the body that take proteins it doesn't need anymore and gets rid of them or doesn't want anymore. There were hundreds of genes, in fact, that people found were turned off at a certain phase in cell development, they didn't exactly know what protein was involved. They did some genetics, and they found this protein that had essentially never been studied before, a human protein called mydalin. ell development, they didn't exactly know what protein was involved. They did some genetics, and they found this protein that had essentially never been studied before, a human protein called mydalin. If you knocked it down, then these proteins didn't get recycled. And that's kind of more or less what they knew. And they knew it didn't work in the standard way. And they ran AlphaFold, and they looked at it. And they saw some pieces that were suggestive. And then they ran AlphaFold together with, you know, I think it was almost all 500 proteins that were not that were kind of responsive to knocking this protein down. Right? So change. So this is kind of how biologists develop evidence. And they found in about 40 percent of these when they ran AlphaFold this very, very specific pattern where 1 part of that protein was trapped between 2 parts of mydnalin kind of grabbing it like clamps. And they could find and then they would go and they would do experiments. Right? Because and then they would say, well, what happens if I take this bit of protein and I remove the place where AlphaFold says it's clamped by middaline? And suddenly that protein doesn't drop down in the cell. Right? So and they found this on maybe the 10 examples. 9 of them worked exactly this way. 1 of them only partially was reduced in how much it's knocked down. But then they looked at the AlphaFold predictions and found that AlphaFold actually put it 2 places. And so if they take out that 2nd place as well, then the degradation is completely abolished. So now they have this mechanistic understanding of this new protein they had never thought about before, and now they know exactly how it recognizes what's developed in this really important stage of cell division. So the so and now the question becomes, okay. Now how do you take that knowledge and do drug development? And that's where so AlphaFold 2 was what came out now 5 years ago. What we've done more recently about a year ago is AlphaFold 3, which says, well, let's let's not just do proteins. Let's do the protein cinematic universe. And so, you know, I said proteins bind cholesterol. Right? So this is a non protein kind of fatty molecule. More well, not more importantly, but very importantly, they also bind drugs. Drugs are small molecules, maybe, you know, 20, 50 atoms that stick to proteins and change how they behave. And you couldn't even ask this question to AlphaFold 2. You couldn't say, how does this drug stick? It'd say, well, you better give me a protein. Only if your drug is a protein, which some are. But AlphaFold 3, we expanded it to kind of do the whole universe of things that appear in the PDB, the whole universe of cells. And now we can say, well, this is exactly where that drug sticks. And then people around the world are using these ideas, building others. For example, isomorphic labs inside Alphabet, kinda developed, inspired from the AlphaFold breakthrough are trying to say, okay. Let's really use this to start to do drug design. Let's start to take these technologies that finally work, that are finally predictive…

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