Headline, August 04 2021/ ''' '' A.I. -ALPHAFOLD- APP '' '''

''' '' A.I. -ALPHAFOLD-

 APP '' '''

SHAPING THE WORLD AT THE MOLECULAR LEVEL : This is the same technology that identifies the commands you bark into your smartphone, recognize faces in the photos you post to Facebook and translates one language into another on Google Translate and other services.

But many experts believe AlphaFold is one of the technology's most powerful applications. ''It shows that A.I. can do useful things amid the complexity of the real world,'' said Jack Clark, one of the authors of A.I. Index, an effort to track the progress of Artificial Intelligence across the globe. 

For some years John McGeehan, a biologist and a director of the Center for Enzyme Innovation in Portsmouth, England has been searching for a molecule that could break down the 150 million tons of soda bottles and other plastic waste strewn across the globe.

Working with researchers on both sides of the Atlantic, he has found a few good options. But his task is that of the most demanding locksmith : to pinpoint the most chemical compounds that on their own will twist and fold into the microscopic shape that can fit perfectly into the molecules of a plastic bottle and split them apart, like a key opening a door.

Determining the exact chemical contents of any given enzyme is a fairly simple challenge these days. But identifying its three-dimensional shape can involve years of biochemical experimentation. So last fall, after reading that an artificial intelligence lab in London called DeepMind had built a system that automatically predicts the shape of enzymes and other proteins, Dr. McGeehan asked the lab if it could help with his project.

Toward the end of one workweek, he sent DeepMind a list of seven enzymes. The following Monday, the lab returned shapes for all seven. ''This moved us to a year ahead of where we were, if not two,'' Dr. McGeehan said.

Now, any biochemist can speed up work in much the same way. Last week, DeepMind released the predicted shapes of more than 350,000 proteins - the microscopic mechanisms that drive the behavior of bacteria, viruses, the human body and all other living things.

This new database includes the three-dimensional structure for all proteins expressed by the human genome, as well as those for proteins that appear in 20 other organisms, including the mouse, the fruit fly and the E-coli bacterium.

This vast and detailed biological map - which includes roughly 250,000 shapes and were previously unknown - may accelerate the ability to understand diseases, develop new medicines and repurpose existing drugs.

It may also lead to new kinds of biological tools, like an enzyme that efficiently breaks down plastic bottles and converts them into materials that are easily reused and recycled.

'' This can take you ahead in time - influence the way you are thinking about problems and help solve them faster,'' said Gira Bhabha, an assistant professor in the department of cell biology at New York University. ''Whether you study neuroscience or immunology - whatever your field of biology - this can be useful.''

This new knowledge is its own sort of key : If scientists can determine the shape of protein, they can determine how other molecules will bind to it.

This might reveal, say, how bacteria resist antibiotics - and how to counter that resistance. Bacteria resist antibiotics by expressing certain proteins; if scientists were able to identify the shapes of these proteins, they could develop new antibiotics or new medicines that suppress them.

In the past, pinpointing the shape of a protein required months, years or even decades of trial-and-error experiments involving X-rays, microscopes, and other tools on the lab bench. But DeepMind can significantly shrink the timeline with its A.I. technology, known as AlphaFold.

When Dr. McGeehan sent DeepMind his list of seven enzymes, he told the lab that he had already identified shapes for two of them, but he did not say which two. This was a way of testing how well the system worked; AlphaFold passed the test, correctly predicting both shapes.

It was even more remarkable, Dr. McGeehan said, that the predictions arrived within days. He later learned that AlphaFold had in fact completed the task in just a few hours.

AlphaFold predicts protein structures using what is called a neural network, a mathematical system that can learn tasks by analyzing vast amounts of data - in this case, thousands of known proteins and their physical shapes - and extrapolating into the unknown.

The Honor and Serving of the latest Global Operational Research on Artificial Intelligence and Medical Sciences for Mankind, continues. The World Students Society thanks author Cade Metz.

With respectful dedication to Research Scientists, Innovators, and then Students, Professors and Teachers of the World.  See Ya all  prepare and register for  Great Global Elections on The World Students Society : wssciw.blogspot.com and Twitter - !E-WOW! - The Ecosystem 2011 :

Good Night and God Bless

SAM Daily Times - the Voice of the Voiceless