DeepMind AlphaFold: The Nobel Prize Winner! 🧬

📝 The paper "Highly accurate protein structure prediction with #AlphaFold" is available here:

Protein database:

More on this:

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Chapters:
00:00 What is protein folding?
01:00 Is it so hard!
04:08 CASP
05:15 AlphaFold's results
06:41 Let's look inside!
07:41 Iterative refinement
08:41 Convolutional neural networks
08:51 Transformers
09:55 Everything matters!
10:58 Adding physics knowledge
13:00 What is this good for?
13:33 A gift to humanity!
14:05 Future works
14:56 AlphaFold's weaknesses
15:16 An important message

Károly Zsolnai-Fehér's links:

[lexscarlet]

The real gift to humanity is an 18 minute two minute papers video

[KristianWant]

I'm a PhD student investigating Fe-S cluster biosynthesis, and AlphaFold has been an absolute treat for my work. I think people haven't truly understood how hugely important (and absolutely essential) this is for the Biochemistry field. It can also predict protein complexes, and it is much more accurate than any previous docking software I have used. Thanks for the video, it's great to see you getting everyone interested!

[ronnybergmann]

As a Biophysicist I can assure that this blue bar is indeed jaw-dropping. Accurate protein folding prediction is basically the holy grail of molecular biology. It is insanely powerful!

[Draxis]

For those wondering. This is truly history in the making! As a molecular biologist myself currently working with aptamers, I shiver of the possibilities this will open not only for my field of research, but for medicine, in better understanding disease, and in the nucleus structures we currently know so little.
This is as ground breaking as the 2013 Nobel Prize work, won by Michael Levitt and others, which helped develop better computational models. Hold on to your papers and hats folks!

[DanielVCOliveira]

This is really big news, and a really big step, but, as you said, it is just one of a thousand step journey. Here's what's next:

Protein folding gets exponentially more complex with each additional aminoacid, meaning large proteins are more difficult to solve. Plus, the problem as it is is mostly based on Wan Der Vaals interactions, but in reality we also have covalent cross bonding between specific aminoacids, ionic interactions with metal atoms, and non-natural folding driven by exterior forces, mainly auxiliar proteins called chaperones. Moreover, the really useful part of this is protein-protein interactions and protein-drug interactions, which are out of the scope of the current algorithm. And last but not least, the solution varies depending on temperature and pH. So all in all, we still have a way to go, but still, this is an *unbelievably* big step which I cannot understate. Amazing video as always!

[parlmc]

Dr. Zsolnai-Fehér, as a complete stranger to the subject I cannot overstate how much these videos lift the weight of ingnorance from my shoulders while adding knowledge to my brain.
I'm a whitness through your tales and, for that, i can't thank you enough

[joelgraff]

A few comments are asking about what you can do with knowledge about a protein structure. The answer is "a lot"...and that is why protein biochemists sometimes work multiple years to try to figure out the structure of a single protein.

OK, here's a better explanation of what you can do if you can predict a protein's structure from the sequence of amino acids it is made of:

1) You could understand how a protein works and where the most important sites are.

2) You could screen the structures of small molecules to identify the ones that could interact with the protein in a therapeutic way (and, even better small molecules could be identified if the current best small molecule has some limitations).

3) You could identify small molecules that could interfere with two proteins from interacting with each other to disrupt a cellular process.

4) You could study two different proteins to understand how they might interact with each other.

5) Proteins are often modified (decorated) with small molecule groups and Alphafold could understand the impact of the modifications on how they could change the protein's unmodified structure.

6) You could test ideas about whether changing the amino acid sequence at specific sites in the protein could alter the protein's function in the way your wish it to be changed.

7) You could create proteins that do not occur naturally (designed/bespoke proteins) with the properties you are seeking and check that your design would be correct by having Alphafold analyze the structure of the protein you dreamed up.

[paulmuriithi]

here in Nairobi Kenya, i shall use Alphafold to predict protein complexes that interfere with tau tangle mentor synthesis. we already have strong indication that specific proteins can derail the protein complex involved in tau tangle establishment in dementia progression. Alphafold is a mighty blessing for the dementia research community and a hope for patients-a valid real hope at last

[chrisoffersen]

It’s so nice to have something so positive to put into my “Moments in History” playlist. Thank you for sharing this :)

[howardkong]

As a computer architecture researcher, I'm now on the task of making this run fast and cheap. Hope myself good luck!

[BernhardKohli]

Whenever the daily news gets too depressing, revert to this: one of the most amazing things ever! I spent 1 year during my diploma thesis purifying proteins for structure elucidation... now this can be done from a sequence in minutes. It allowed anyone with a PC to visualize how similar or different the spike protein is between omicron an delta, for example, helping to make an educated guess on whether vaccines were bound to continue to have a reasonable effect or not. Indeed, what a time to...! 👍👏

[nulled]

What a time to be alive :D
Would love to see some more videos on multidisciplinary topics, even if u cannot explain everything properly, it always gets me excited about the future ^^

[jfk_the_second]

"Yes, this is the place on the internet where we get unreasonably excited by a large blue bar. Welcome to Two Minute Papers!"

Well said, Ka'role! 😂❤️

[Emerald_King]

Thanks for whispering the whole time. Great video.

[popquizzz]

This will go down in the annals of humanity's greatest accomplishments, e.g., Fire, the Wheel, the Motor, Antibiotics, the human genome project, Quantum Computing, cand now DeepMind Alpha Go.

[cn-ml]

The incredible effort that was AlphaFold is already astonishing, but reaching such a high level of accuracy in only two years is absolutely mindblowing. I personally do not own any paper that I could've held on strong enough.

[_adityaketkar]

Károly you have always been a source of inspiration for everyone, especially people like me from outside research community! You explain these breakthroughs in such simple illustrations, it really is making a dent in the universe, for better :)

[badgerff]

I am studying protein folding/unfolding simulations for an undergraduate degree; this video is exceptional. Very well done!

[CYIERPUNK]

WHAT A TIME TO BE ALIVE ; thank you john & karoly and everyone involved =]

[shuanlive]

I'm so impressed by you actually insist making this video correct by asking the best person knowing this work!!! Thank you so much!!