current position:Home>AI's prediction of protein structure has reached the annual technological breakthrough of science and nature, and AI for science has infinite potential

AI's prediction of protein structure has reached the annual technological breakthrough of science and nature, and AI for science has infinite potential

2022-02-02 20:13:55 Heart of machine

If you want to give AI In the field of 2021 The most breakthrough Award , Who will you choose ?《science》 and 《nature》 The answers are 「 Protein structure prediction 」.

This year, 7 month , Protein structure Two big AI Prediction algorithms have been developed one after another , One is DeepMind Of AphaFold2, The other is developed by institutions such as the University of Washington RoseTTAFold. Now these two algorithms are 《science》 named 2021 The annual breakthrough .

as everyone knows , Long chain amino acids in proteins are distorted 、 Fold and interweave into a complex three-dimensional structure , These structures can be difficult to , It's not even possible to decipher . For decades, scientists have been hoping to simply predict the structure and shape of proteins through gene sequences , To open a new world with insight into the mechanism of life , But progress has been slow .

until DeepMind announce , For the first time, people have found a way to predict protein structure by calculation . Even without knowing the similar structure ,AI It can also accurately predict the structure of proteins at the atomic level .
DeepMind Express AlphaFold Protein structure can be predicted periodically with atomic accuracy , Technically, multi sequence alignment and deep learning algorithm are used to design , Combined with the physical and biological knowledge of protein structure, the prediction effect is improved .AlphaFold Our breakthrough research results will help researchers explore the mechanisms that cause some diseases , And design drugs for 、 The crops have increased , And biodegradable plastics 「 super enzyme 」 R & D paves the way .
AlphaFold In the paper 7 Published in June 《nature》 The journal , Address of thesis :https://www.nature.com/articles/s41586-021-03819-2

In recent days, Alphafold One of the founders of John Jumper It was also named 《nature》2021 Top ten scientific figures of the year .
John Jumper

from 2018 Early generation AlphaFold In the international protein structure prediction competition (CASP) Cut a striking figure , To 2021 year AlphaFold2 Official open source ,John Jumper led DeepMind Our research team overcame many difficulties , Just let AlphaFold2 Realized 2/3 Outstanding achievements in protein structure prediction .

It is also the subject of protein structure prediction RoseTTAFold Also be 《science》 The selection of 2021 The annual breakthrough .

RoseTTAFold By the Institute of protein design, University of Washington School of Medicine (Institute for Protein Design) United with Harvard University 、 University of Texas Southwest Medical Center 、 University of Cambridge 、 A protein prediction tool based on deep learning developed by Lawrence Berkeley National Laboratory and other institutions .RoseTTAFold Achieved comparable results AlphaFold2 High accuracy of , And faster 、 The computer processing power required is also lower .

RoseTTAFold Published in 《science》 The journal , Address of thesis :https://www.science.org/doi/abs/10.1126/science.abj8754

Structurally ,RoseTTAFold It's a three track (three-track) neural network , It means that it can take into account the pattern of protein sequence 、 How amino acids interact and the possible three-dimensional structure of proteins . In this structure , A one-dimensional 、 A two-dimensional 、 Three dimensional information flows back and forth , So that the neural network can centrally infer the chemical part of protein and its folding structure .

As people marvel at it , More than a decade ago, some scientists thought that the problem of protein structure prediction could never be solved , But today this has become a reality . The biggest breakthrough brought about by artificial intelligence is to 「 impossible 」 Turned into 「 Probably 」.

Expand on , It's not just a change in protein structure prediction ,AI There is still a lot of potential to be tapped in the whole scientific research field , This is also AI for Science The reason why this topic has attracted much attention this year , Such as AI + mathematics 、AI + chemical 、AI + medicine .

Maybe , There will be more in the next two years AI + Breakthroughs in scientific research , You can focus on .

Reference link :
https://www.science.org/doi/10.1126/science.abn5795
https://www.nature.com/immersive/d41586-021-03621-0/index.html#section-7cgEBpkV9L

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