Mystery ‘largely solved’ by AI

Weekender

ONE of biology’s biggest mysteries has been solved using artificial intelligence, experts have announced.
Predicting how a protein folds into a unique three-dimensional shape has puzzled scientists for half a century.
London-based AI lab, DeepMind, has largely cracked the problem, say the organisers of a scientific challenge.
A better understanding of protein shapes could play a pivotal role in the development of novel drugs to treat disease.
The advance by DeepMind is expected to accelerate research into a host of illnesses, including Covid-19.
Their programme determined the shape of proteins at a level of accuracy comparable to expensive and time-consuming lab methods, they say.
Dr Andriy Kryshtafovych, from University of California (UC), Davis in the US, one of the panel of scientific adjudicators, described the achievement as “truly remarkable”.
“Being able to investigate the shape of proteins quickly and accurately has the potential to revolutionise life sciences,” he said.
What are proteins?
Proteins are present in all living things where they play a central role in the chemical processes essential for life.
Made up of strings of amino acids, they fold up in an infinite number of ways into elaborate shapes that hold the key to how they carry out their vital functions.
Many diseases are linked to the roles of proteins in catalysing chemical reactions (enzymes), fighting disease (antibodies) or acting as chemical messengers (hormones such as insulin).
“Even tiny rearrangements of these vital molecules can have catastrophic effects on our health, so one of the most efficient ways to understand disease and find new treatments is to study the proteins involved,” said Dr John Moult of the University of Maryland, US, the chair of the panel of scientific adjudicators.
“There are tens of thousands of human proteins and many billions in other species, including bacteria and viruses, but working out the shape of just one requires expensive equipment and can take years.”
How does the challenge work?
In 1972, Christian Anfinsen was awarded a Nobel Prize for his work showing that it should be possible to determine the shape of proteins based on the sequence of their amino acid building blocks.
Every two years, scores of teams from more than 20 countries blindly attempt to predict using computers the shape of a set of around 100 proteins from their amino acid sequences.
At the same time, the 3-D structures are worked out in the lab by biologists using traditional techniques like X-ray crystallography and NMR spectroscopy, which determine the location of each atom relative to each other in the protein molecule.
A team of scientists from Casp (the Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction) then compares these predictions with 3-D structures solved using experimental methods.
Casp uses a metric known as the global distance test to assess accuracy, ranging from 0-100. A score of around 90, which DeepMind’s AlphaFold program achieved, is regarded as comparable with lab techniques.
What happened this year?
In the latest round of the challenge, Casp-14, AlphaFold determined the shape of around two thirds of the proteins with accuracy comparable to laboratory experiments.
The assessors said accuracy with most of the other proteins was also high, though not quite at that level.
AlphaFold is based on a concept called deep learning. In this process, the structure of a folded protein is represented as a spatial graph.
The programme then “learns” using information on the 3-D shapes of known proteins held in the Public Database of Proteins. The AI programme was able to do in a matter of days what might take years at the laboratory bench. – BBC

One thought on “Mystery ‘largely solved’ by AI

  • That was actually the approach taken by the UPNG Structural and Molecular Chemist and the associated scientists and doctors at the UPNG. These UPNG experts were initially investigating potential proteins using computer models to identify the ones that can arrest the CONVID-19 virus. As far as we know, the next step of their research would include laboratory mixing of these identified proteins.

    There are a number of contributions made by UPNG scientist into the manufacturing industries in the past that are now enjoyed by PNG citizens as well as the region. Let’s not underestimate our very own scientists, most of whom are highly respected abroad (sadly are looked down on in PNG).

    Give our national scientists the change to prove to PNG once again and the world the potential PNG as and can offer.

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