Protein Folding

Creator
Creator
Seonglae Cho
Created
Created
2023 Jul 12 17:23
Editor
Edited
Edited
2025 Apr 27 9:58

Protein Folding Prediction

The process by which a linear chain of amino acids (protein) forms a uniquely folded structure specific to each protein or reaches a stabilized conformation
Native folding refers to reaching optimization while maintaining minimal energy loss
Protein Folding Competitions
 
 
 
 
 
How AI Cracked the Protein Folding Code and Won a Nobel Prize
This is the inside story of how David Baker, Demis Hassabis and John Jumper won the 2024 Nobel Prize in Chemistry for advances in computer-assisted protein design and structure prediction. Proteins are biological nano-machines that perform a vast array of vital functions inside of every living organism. For more than half a century, scientists have looked to solve the central mystery of protein science: How does a one-dimensional string of molecules fold innately and near-instantaneously into a complex three-dimensional shape? In 2020, Google DeepMind entered a deep-learning algorithm called AlphaFold2 into the Olympics of protein folding — and to everyone’s shock and surprise, ended up solving a key part of the puzzle. This breakthrough kick-started an AI revolution in biology research, clearing the path to revolutionary new techniques in protein design, which is the process of creating new and novel proteins that could solve some of the world's biggest problems. Read the related article at: https://www.quantamagazine.org/how-ai-revolutionized-protein-science-but-didnt-end-it-20240626/ Related Papers: - "Highly accurate protein structure prediction with AlphaFold" https://www.nature.com/articles/s41586-021-03819-2 - "De novo design of protein structure and function with RFdiffusion" https://www.nature.com/articles/s41586-023-06415-8 - "Generalized biomolecular modeling and design with RoseTTAFold All-Atom" https://www.science.org/doi/10.1126/science.adl2528 - "Accurate structure prediction of biomolecular interactions with AlphaFold 3" https://www.nature.com/articles/s41586-024-07487-w CORRECTION: The protein shown at 01:07 labeled SEROTONIN is mislabeled, it is in fact "Crystal structure of serotonin 2A receptor in complex with serotonin" https://www.rcsb.org/structure/7WC4 --------- Chapters: 00:00 - Introduction 01:03 - What is a protein? 02:31 - Levinthal Paradox 02:53 - The Protein Folding Problem - how proteins fold to function 03:48 - John Kendrew / using X-ray crystallography to determine structure 05:02 - The Protein Data Bank (PDB) 05:45 - Christian Anfinsen's Nobel winning research 06:28 - Chemical structure of amino acids 07:17 - Secondary and tertiary folding structures 07:59 - Quaternary folding structure 08:16 - The beginnings of computational biology 09:09 - Critical Assessment of protein Structure Prediction (CASP) challenge 10:26 - Baker lab develops RoseTTA 11:31 - Google DeepMind introduces deep learning with AlphaGo 12:00 - DeepMind develops AlphaFold 1 to enter CASP 13 13:32 - AlphaFold 2 explained 15:28 - DeepMind wins CASP 14 and solves the protein folding problem 17:10 - An AI revolution in biological research 17:45 - How the Baker lab designs new proteins 19:53 - New AI tools predict cellular interactions, AlphaFold 3 and RoseTTAFold All-Atom 21:23 - David Baker, John Jumper, and Demis Hassabis win the Nobel Prize --------- VISIT our website: https://www.quantamagazine.org LIKE us on Facebook: / quantanews FOLLOW us Twitter: / quantamagazine Quanta Magazine is an editorially independent publication supported by the Simons Foundation: https://www.simonsfoundation.org
How AI Cracked the Protein Folding Code and Won a Nobel Prize
 

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