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DeepMind’s AI makes gigantic leap in solving protein structures
#1

DeepMind’s AI makes gigantic leap in solving protein structures
An artificial intelligence (AI) network developed by Google AI offshoot DeepMind has made a gargantuan leap in solving one of biology’s grandest challenges — determining a protein’s 3D shape from its amino-acid sequence.

"DeepMind’s program, called AlphaFold, outperformed around 100 other teams in a biennial protein-structure prediction challenge called CASP, short for Critical Assessment of Structure Prediction. The results were announced on 30 November, at the start of the conference — held virtually this year — that takes stock of the exercise.

“This is a big deal,” says John Moult, a computational biologist at the University of Maryland in College Park, who co-founded CASP in 1994 to improve computational methods for accurately predicting protein structures. “In some sense the problem is solved.”

“It’s a game changer,” says Andrei Lupas, an evolutionary biologist at the Max Planck Institute for Developmental Biology in Tübingen, Germany, who assessed the performance of different teams in CASP. AlphaFold has already helped him find the structure of a protein that has vexed his lab for a decade, and he expects it will alter how he works and the questions he tackles. “This will change medicine. It will change research. It will change bioengineering. It will change everything,” Lupas adds.

In some cases, AlphaFold’s structure predictions were indistinguishable from those determined using ‘gold standard’ experimental methods such as X-ray crystallography and, in recent years, cryo-electron microscopy (cryo-EM). AlphaFold might not obviate the need for these laborious and expensive methods — yet — say scientists, but the AI will make it possible to study living things in new ways."
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#2

DeepMind’s AI makes gigantic leap in solving protein structures
I wonder if it will change how abiogenesis is studied.  Scientists are getting nearer and nearer to understanding how life started on this planet. 

Hint: it wasn't a god.
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#3

DeepMind’s AI makes gigantic leap in solving protein structures
(12-01-2020, 09:10 PM)Dancefortwo Wrote: Scientists are getting nearer and nearer to understanding how life started on this planet. 

I think what makes finding that point such a challenge is that it isn't a point.  Just as there's no point where a river ends and the sea begins, the threshold between living and non-living may be wide, populated with bits of compound molecular structures that don't fit either designation.  Has science yet actually defined life without some hemming and hawing?

The evolutionary process does not begin at the threshold of life, it precedes it.  Some particular configuration of minerals gets exposed to some combination of heat, pressure, moisture, acceleration and photons that alters it, moving it across an infinitesimal threshold closer to life that also made it less vulnerable to deterioration.  At a point where something is unequivocally life a long path extends backward across increments of evolutionary change to some indeterminate clump of inert mineral, with the change from dead to living unidentifiable.  Life may not be able to be built from scratch like a box of Lego bricks - it may require ascent from an amorphous process - growing a rose from a seedling, not assembling petals into a finished flower.
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#4

DeepMind’s AI makes gigantic leap in solving protein structures
(12-01-2020, 10:26 PM)airportkid Wrote:
(12-01-2020, 09:10 PM)Dancefortwo Wrote: Scientists are getting nearer and nearer to understanding how life started on this planet. 

I think what makes finding that point such a challenge is that it isn't a point.  Just as there's no point where a river ends and the sea begins, the threshold between living and non-living may be wide, populated with bits of compound molecular structures that don't fit either designation.  Has science yet actually defined life without some hemming and hawing?

The evolutionary process does not begin at the threshold of life, it precedes it.  Some particular configuration of minerals gets exposed to some combination of heat, pressure, moisture, acceleration and photons that alters it, moving it across an infinitesimal threshold closer to life that also made it less vulnerable to deterioration.  At a point where something is unequivocally life a long path extends backward across increments of evolutionary change to some indeterminate clump of inert mineral, with the change from dead to living unidentifiable.  Life may not be able to be built from scratch like a box of Lego bricks - it may require ascent from an amorphous process - growing a rose from a seedling, not assembling petals into a finished flower.

Absolutely correct. The process of natural selection is not a purely biological process; natural selection operates in chemistry as well. Stable molecules thrive when that quality serves the environment; promiscuous (i,e, more-volatile) molecules thrive when for whatever reason the environment requires adaptability.
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#5

DeepMind’s AI makes gigantic leap in solving protein structures
I can't pretend to understand how this all works in detail, but I know for example that
membrane protein structures are involved with human malignancies—in the way cells
communicate with each other. I guess this sort of research result could help in a more
targetted treatment of cancers?
I'm a creationist;   I believe that man created God.
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#6

DeepMind’s AI makes gigantic leap in solving protein structures
(12-02-2020, 02:08 AM)SYZ Wrote: I can't pretend to understand how this all works in detail, but I know for example that
membrane protein structures are involved with human malignancies—in the way cells
communicate with each other.  I guess this sort of research result could help in a more
targetted treatment of cancers?

One interest here is prions, which may be involved with things like some forms of Alzheimer's.  Prions are misfolded proteins, which in some cases, may act as catalysts causing good proteins to misbehave.
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