How AlphaFold solves protein folding
Vložit
- čas přidán 25. 04. 2024
- AlphaFold paper: www.nature.com/articles/s4158...
The original paper about transformers (the technology behind GPT), Attention Is All You Need: arxiv.org/abs/1706.03762
Helpful videos and blogposts about attention and AlphaFold
3blue1brown's video on transformers: • Attention in transform...
Nazim Bouatta's talk on AlphaFold: • Nazim Bouatta | Machin...
Simon Kohl's talk on AlphaFold, (he is one of the coauthor's of the algorithm): • Highly Accurate Protei...
A very thorough blogpost about the algorithm from UV-Bio: www.uvio.bio/alphafold-archit...
The Openfold github + paper: github.com/aqlaboratory/openfold + www.biorxiv.org/content/10.11... - Věda a technologie
The media would have you believe that researchers merely asked AI to solve the folding problem, and it magically did. This video is an excellent illustration that the problem needed to be really well understood by the researchers, and a method had to be found in which to frame the problem in such a way that it was suitable for machine learning to solve. This is not unlike traditional software development. For now, there's still a lot of human intelligence required in getting AI to do useful things.
I was very surprised at how involved this algorithm is! As you say, there was a lot of knowledge about the problem that was needed to solve it
Well, now you can "merely aks the AI" to solve the folding problem of a protein. That work is just made once, and not always, more and more of the capabilites of AI are "emergent", not crafted.
And, are you equaling AlphaFold to the bleeding edge of public AI right now?!
For now
The triangle inequality is the kind of mathematical construct that, when learning about, seems kind of useless or obvious but then shows up everywhere.
Right? I remember thinking, “why are we bothering to learn this?” When it first came up.
I know this is a bit different from my usual videos! I've been very interested in how AI in science recently, and AlphaFold is a great case study.
I was shocked when I heard that protein folding, one of the most notorious and important questions in computational biology, had suddenly been solved by AI. In this video I explain what the AlphaFold algorithm actually does. Next week I want to see if I can replicate it.
Thanks for this video and looking forward to the follow -up. I can understand how AI can make predictions about folding and structure based on the actual sequence. But I guess another important aspect is of course the function that a protein can perform or how active it is. Is this something that AI can also predict?
I would also be interested in the followup of replicating it. even a simplified version would be great
Any video is already a nice surprise! The connection to quantum computing makes it totally on-brand because I'm seeing so much excitement about how transformers and attention models will replace other AI... maybe quantum computing will fulfill the hype too!
But AlphaFold is very ancient by today's standard.
Please more AI videos, AI is a pivot point for Humanity!
In undergrad, I used to work in a structural biochemistry lab. I worked a lot with predicting protein structures using homology modeling to comparing two proteins with similar primary structures and other characteristics and using that to predict the tertiary structure of our protein of interest. I graduated before alphafold came out but I remember the excitement of those working in my former lab when it came out. Back then with our ab initio protein modeling techniques, I think the best we could do was proteins with like 100-200 residues with limited accuracy but I think alphafold can due over a thousand with decent accuracy. I no longer do any of that stuff but it is pretty amazing to see such a massive breakthrough in my former field of study.
Oh that's so interesting! If you still keep in contact with your former lab, do you know how their research has changed now?
Gosh, I remember at the beginning of my undergrad talking to my friend about protein folding and how hard is it. Five years later, we were talking about how AlphaFold just solved the problem. It's crazy!
Would love to see more diverse stuff from you!
Yeah, I remember how certain people were that it was an intractable problem classically. AlphaFold really came out of the blue!
I certainly would not say that its 'solved'. Under rigid conditions of determining singular structures based on the protein data bank, alphafold performs amazingly. That's only a small subset of our proteome. alphafold cannot generate ensembles of structures, which is an exceptional challenge.
@@yousufo.ramahi126 Yeah, but AlphaFold is already old.
We missed you!!
Sorry!!
Insanely well presented content.
Top tier content right here
Very clear explanation. Thanks!
thanks! there have been a few explanations of alphafold in various videos, but now I can say that finally there is a good explanation video on youtube
Aww, thank you so much!
I remember playing Fold-it years ago to help scientists figure out proteine folding as computers couldn't do it. Glad to see that computers *can* do it now 😊
I remember that!! Crazy isn’t it that computers are now good at this problem?
Awesome animations. Really nicely done :)
The triangle inequality went a long way towards understanding for me, thanks
And Go. We thought Go was impossible for a computer. We learned that AI can see patterns that we overlook
Yes, very true.
Come for the animation. Stay for the content. ❤
Thanks! It was fun to watch.😀
Thanks, that was very good!
Look at AlphaGo go, how AlphaFold folds, and Alphabet... Bets?
Attention is truly all you need
It's interesting to see some AI topics on your channel. I find quantum physics interesting, but a lot of it goes over my head admittedly. AI/ML is more in my wheelhouse, so I'm excited for the follow up video on this. I think a lot of the more interesting AI algorithms are those like AlphaFold which combine some expert/domain knowledge to provide structure to more numerical machine learning algorithms. If you're starting to explore more AI literature, do you think you would try to create a video combining your own domain knowledge of physics plus AI to solve something new?
Thank you! I’m very interested in the intersection of quantum physics/ chemistry and AI. I’d love to make more videos about it!
very interesting
This is statistic analyze, and preparing data to do statistic analyze is main in quality of final result of statistic approximation.
Just sort your data and build statistic of data connections - and predict outcome of new data base on statistic.
Chess was solved same way in the late 1980s.
Now "statistical approximation" called as AI.
As mentioned in other comment - "media present AI as magic that invent rules of universe" - when it hand made data analyze made exact for this task.
Holy moly!!
Neat!
Does it just predict how known proteins fold, or can it predict how a completely novel protein would fold? Like if I just invented an amino acid sequence that doesn't actually exist in nature, could it predict how that protein would fold if it were actually made?
That’s a great question! It claims to work for “biological relevant” proteins. There are definitely pathological ones it can’t do well. But I wonder how well it does for “random” proteins
I don't know much biology, but isn't it the case that not all amino acid sequences are capable of folding into a stable shape? I wonder what AlphaFold would say about those. Would it say, "I mean, like, we can fold parts of it, but we can't get the whole thing to fold into a stable shape"?
That’s so interesting! I might give it a go. My guess is that it just takes a stab at it and gets it wrong
MAM How u done quantum mechanics as i was browsing through ur old videos i saw u done quantum mech degree so where and how u done it mam can a 12th grader do it?
maybe its just my headphones but your audio sounds vaguely like Robert Kennedy, like, but as though its an electronic effect.
Given a one long string of amino acids, is there only one unique way that can fold?
Great question! It seems like, given a particular environment (eg, ph levels and other molecules around) the protein will fold a certain way. But changing the environment can “denature” a protein (it will fold differently)
@@LookingGlassUniverse Don't forget the effects of electromagnetic radiation, there is the resonance effects beyond the normally considered ones.
With videos like this I learn a lot. As someone that never studied science in school but out of school have an interest in science, I enjoy this. Clear explanation. Your animation is a lot better in this video as well.
Thank you for your kind words!
ChatGPT on steroids except it speaks in angles and distance instead of English 🥴
Nah. More like "Homology Modeling" merged with Attension. If you wander, what Homology Modeling is - Its roughly what the first half of the video talk about. Alphafold just uses attention to extract better inference from the homology data.
I hope you can catch up with the bleeding edge in public AI very soon, at least with its capabilities. Thanks for your videos.
Given that the algorithm seem to require input from genetically related species,
what kind of data does AlphaFold need to predict protein folding?
does it need information on the full 3D shape of a protein of related species?
No, just other amino acid strings!
There is a philosophical dilemma here - would you give credit for "solving" a protein-folding to alphafold itself or the architects who baked-in the various sequences, loops, inequality-checks, pairwise modifiers, etc. into the basic design of alphafold? A "vanilla" model would have been inadequate to solve the problem, right? Alphafold "just" does the number-crunching.
AI is great for solving specific types of problems. Too bad it's being sold as technomagic for everything, and an incredible amount of resources have been dumped into the technomagic bubble that's starting to pop.
It's mainly machine learning. May be we should stop calling it AI. May be we should stop calling it machine learning either, since that's mostly statistical inference recursively applied gazzilions of times.
To be fair, ordinary digital computing was sold in the same way, with the same fears / mania expressed by the media, and the same business opportunities, some legit, many exploitative.
@@WanJae42 kind of. It was sold as instant access to infinite knowledge, which is kinda true, along with some technomagical problem solving. It wasn't being sold as this is the solution to all problems and will make you insanely rich.
@@aniksamiurrahman6365 AI, and deep or machine learning are definitely misnomers.
@adampope5107 You may be younger than me. It was going to take over the world. Robots were going to run everything and take our jobs. Computers in movies could do everything except perform the actual car chase ... well until KITT came along. People thought that ordinary digital computers were already a kind of sentience, and didn't really know the difference. Not unlike how too many people today think that the current take on AI is sentient / thinking. The media played along. Hollywood played along. Tron depicted a massive intelligence going on inside an early 80s arcade cabinet. I give Terminator credit for at least explaining that the AI depicted required a leap in CPU technology unlike what existed at the time. (For the record, I love Tron.)
Yay you upload! Never knew you were into AI. Good for me i guess...
Edit: Obligatory "first" message
So, basically, homology modeling on steriods, ummm, I mean attension.
God's geometry of creation is waiting for you, your Esoteric studies will be realized in Time. ❤
Please take this nonsense elsewhere. Smug theists always show their whole ass when they can't understand something. Go read a book. Try and learn.
Once again brilliant explination. It's a shame your too educated to be a high school teacher. Because with the way you're able to break complex things down and make them interesting, you could get a lot of bored high schoolers interested in physics.