Levinthal's Paradox, Protein Folding and AlphaFold

Around five decades ago, Cyrus Levinthal, an American molecular biologist, postulated that if a protein were to sample every possible conformation of its amino acids, it would take longer than the age of the universe to assemble into its three-dimensional shape. Although scientists had been studying proteins for decades prior, the mystery of how proteins could reliably fold into their conformations on a millisecond scale had remained unanswered. In the many years since studies of protein folding began, the question of how proteins fold has been slowly unraveling, and today, it is possible to predict proteins’ structures based on the amino acid sequences. Recently, artificial intelligence has been able to quickly and accurately determine the conformation of proteins from their amino acid sequence, which will enable tremendous advancements in microbiology and further our understanding and application of proteins for medicine.

Transcript:

Music by Emile van Krieken:

Song: Wings (Aether 2)

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[TheMeaningCode]

This is excellent, thank you! Here visiting because of the shout out of your channel from Curt at TOE.

[druidjuicer]

Great videos. Referred here by Curt at TOE and I'm glad I was. Thanks

[innate-videos]

Great presentation, full of useful detail and very interesting, thank you.

[mazinnasralla]

Excellent video. I wanted to know more about the Levinthal Paradox but the background detail is really excellent.

[jayakarjosephjohnson]

It’s a reflection of Time paradox that exists with particle scenario of universe. Thus, we claim that the fundamental matter is string like structure rather than particle and in that the atomic analogy may change from Bohr model.

[deeveevideos]

It takes intelligence to understand intelligence

[vasilesambor]

I think it's an over statement that after 50 years, AI helped us "understand how proteins fold" and does it computationally. What it actually does, it looked into classified information specified by humans, (for eg. this is how a good protein of type x looks like and this is how a protein of type y should look like) and then it can predict based on what information it has (with a machine learning system), but I don't see how is this related to the paradox or with our understanding about how the protein formed in the first place...!? Am I missing something?

[davidhoang]

Nice! Your videos should be seen by more watchers. May I repost your channel without changing anything on the clean platform named Ganjing World? Thank you!

[madmoon]

So are people still not sure how proteins fold?

[cicinindivin]

Demis's gonna win that gold Alfred

[olafstorvik]

AI can now design antimicrobial proteins almost from scratch, it's amazing stuff.

[djkostya]

They have no idea how to deal with Levinthal’s paradox, but they are completely sure that life has originated itself. Wow these claims sound over the top stupid. Richard, are you there?