Protein folding thread

Xyls
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Protein folding thread

Post by Xyls »

DeepMind says it will release the structure of every protein known to science

https://www.technologyreview.com/2021/0 ... -proteome/

Back in December 2020, DeepMind took the world of biology by surprise when it solved a 50-year grand challenge with AlphaFold, an AI tool that predicts the structure of proteins. Last week the London-based company published full details of that tool and released its source code.

Now the firm has announced that it has used its AI to predict the shapes of nearly every protein in the human body, as well as the shapes of hundreds of thousands of other proteins found in 20 of the most widely studied organisms, including yeast, fruit flies, and mice. The breakthrough could allow biologists from around the world to understand diseases better and develop new drugs.
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funkervogt
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Re: Protein folding thread

Post by funkervogt »

People will have a lot of fun for years verifying the accuracy of these.
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raklian
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Re: Protein folding thread

Post by raklian »

funkervogt wrote: Fri Jul 23, 2021 12:52 pm People will have a lot of fun for years verifying the accuracy of these.
More likely they will use neural networks or even a later iteration of DeepMind to verify them. :lol:
To know is essentially the same as not knowing. The only thing that occurs is the rearrangement of atoms in your brain.
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Yuli Ban
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Re: Protein folding thread

Post by Yuli Ban »

AI protein folding breakthrough could spark medical revolution
Artificial intelligence has been used to predict the structures of almost every protein made by the human body.

The development could help supercharge the discovery of new drugs to treat disease, alongside other applications.

Proteins are essential building blocks of living organisms; every cell we have in us is packed with them.

Understanding the shapes of proteins is critical for advancing medicine, but until now, only a fraction of these have been worked out.

Researchers used a program called AlphaFold to predict the structures of 350,000 proteins belonging to humans and other organisms.

The instructions for making human proteins are contained in our genomes - the DNA contained in the nuclei of human cells.

There are around 20,000 of these proteins expressed by the human genome. Collectively, biologists refer to this full complement as the "proteome".

Commenting on the results from AlphaFold, Dr Demis Hassabis, chief executive and co-founder of artificial intelligence company Deep Mind, said: "We believe it's the most complete and accurate picture of the human proteome to date.
And remember my friend, future events such as these will affect you in the future
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funkervogt
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Re: Protein folding thread

Post by funkervogt »

Further progress:
I will not attempt to describe the details of this approach - given enough time I think that I probably could, but I'm pretty sure that I don't have enough pork rinds and Mountain Dew on hand to get me through that process, given my current level of knowledge. What I can tell you, though, is that the method uses the primary sequence of the protein, with no reference to existing structures, and it depends strongly on the torsional angles between each residue. Now, that turns into an awful problem very quickly if you just take it as a big long list of individual torsion angles, but this approach uses Frenet-Serret formulas to deal with these things as a curve in torsion space, which appears to be computationally far more tractable. After working through the sequence that way, the problem drops back into Cartesian space for a brush-up with more conventional energy minimization, with what is presumably a solid starting point based on the optimization of the primary backbone geometry.
https://www.science.org/content/blog-po ... prediction
RGN2 outperforms AlphaFold2 and RoseTTAFold (as well as trRosetta) on orphan proteins and is competitive with designed sequences, while achieving up to a 106-fold reduction in compute time. These findings demonstrate the practical and theoretical strengths of protein language models relative to MSAs in structure prediction.
https://www.biorxiv.org/content/10.1101 ... 2.454840v1
Xyls
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Re: Protein folding thread

Post by Xyls »

Apparently, some of the underlying theory needs to be reviewed:

Restructuring biology: New study shows protein hydrophobic parts do not hate water

Scientists disprove a key theory about how proteins in our cells achieve their characteristic folded structures

https://www.sciencedaily.com/releases/2 ... 104123.htm
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funkervogt
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Re: Protein folding thread

Post by funkervogt »

And yet more progress, with even more complex tasks.

https://www.science.org/content/blog-po ... ns-already
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Re: Protein folding thread

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Scientists use Summit supercomputer, deep learning to predict protein functions at genome scale

January 11, 2022

A team of scientists led by the Department of Energy's Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

Their deep learning-driven approaches infer protein structure and function from DNA sequences, accelerating new discoveries that could inform advances in biotechnology, biosecurity, bioenergy and solutions for environmental pollution and climate change.

Researchers are using the Summit supercomputer at ORNL and tools developed by Google's DeepMind and Georgia Tech to speed the accurate identification of protein structures and functions across the entire genomes of organisms. The team recently published details of the high-performance computing toolkit and its deployment on Summit.

[...]

With advances in DNA sequencing technology, data are available for about 350 million protein sequences—a number that continues to climb. Because of the need for extensive experimental work to determine three dimensional structures, scientists have only solved the structures for about 170,000 of those proteins. This is a tremendous gap.

"We're now dealing with the amount of data that astrophysicists deal with, all because of the genome sequencing revolution," said ORNL researcher Ada Sedova. "We want to be able to use high-performance computing to take that sequencing data and come up with useful inferences to narrow the field for experiments. We want to quickly answer questions such as 'what does this protein do, and how does it affect the cell? How can we harness proteins to achieve goals such as making needed chemicals, medicines and sustainable fuels, or to engineer organisms that can help mitigate the effects of climate change?'"

https://phys.org/news/2022-01-scientist ... otein.html


Image
This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy
Xyls
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Re: Protein folding thread

Post by Xyls »

Physicists identify most complex protein knots

https://physicsworld.com/a/physicists-i ... ein-knots/
Scientists in Germany and the US have predicted the most topologically complex knot ever found in a protein using AlphaFold, the artificial intelligence (AI) system developed by Google’s DeepMind. Their complete analysis of the data produced by AlphaFold also revealed the first composite knots in proteins: topological structures containing two separate knots on the same string. If the discovered protein knots can be recreated experimentally it will serve to verify the accuracy of predictions made by AlphaFold.

Proteins can fold to form complex topological structures. The most intriguing of these are protein knots – shapes that would not disentangle if the protein were pulled from both ends. Peter Virnau, a theoretical physicist at Johannes Gutenberg University Mainz, tells Physics World that there are currently around 20 to 30 known knotted proteins. These structures, Virnau explains, raise interesting questions around how they fold and why they exist.
Xyls
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Re: Protein folding thread

Post by Xyls »

DeepMind has predicted the shape of every protein known to science. How excited should we be?

The AI-based breakthrough, like the sequencing of the human genome, may not turbocharge the development of new drugs as some hope. But as a resource for basic biological research it will be valuable.

https://www.prospectmagazine.co.uk/scie ... ould-we-be
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