AI tool cracks code to imagine proteins in 3D

An artificial intelligence network solved a scientific problem that has stumped researchers for half a century, successfully predicting the way proteins fold into three-dimensional shapes, a process that has typically taken expensive and painstaking lab work that could go on for decades.

The way proteins, one of the building blocks of life, fold drives their functionality and behaviour. For instance, SARSCOV-2 has a protein that folds as a spike. This shape, therefore, is relevant for biologists

NEW DELHI:

(including for its ability to find cures for illnesses). It isn’t easy to predict the shape of a protein, though, based on the way amino acids come together to form a protein. That’s because there are countless ways in which a protein can fold into a three-dimensional structure.

Deepmind, owned by Google, created a computer programme called Alphafold, which predicted to surprising accuracy the 3D shapes of proteins after being fed their constituent parts – data depicting strings of amino acids.

“This computational work represents a stunning advance on the protein-folding problem, a 50-year-old grand challenge in biology. It has occurred decades before many people in the field would have predicted. It will be exciting to see the many ways in which it will fundamentally change biological research,” said professor Venki

Ramakrishnan, Nobel laureate and president of the Royal Society, according to a blog post by Deepmind.

“It’s a breakthrough of the first order, certainly one of the most significant scientific results of my lifetime,” a report in Nature quoted Mohammed Al Quraishi, a computational biologist at Columbia University in New York City, as saying. “I think it’s fair to say this will be very disruptive to the protein-structure-prediction field. I suspect many will leave the field as the core problem has arguably been solved,” he added.

ALPHAFOLD LEARNS, THEN PREDICTS HOW PROTEINS FOLD, A PROCESS THAT IS KEY TO HOW THE MACHINERY OF LIFE WORKS