#Breakthrough: DeepMind’s AI Solves 50 Year Old Science Prob
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Google’s Deepmind claims to have created an artificially intelligent program called AlphaFold to predict the structure of proteins potentially decoding a problem that has been described as akin to mapping a genome. It was presented at Critical Assessment of Structure Prediction Competition.

Why protein structure prediction matters?

The ability to predict protein structures accurately enables a better understanding of what they do and how they work. Many of the greatest challenges facing society, like developing treatments for diseases or finding enzymes that break down industrial waste, are fundamentally tied to proteins and the role they play.

DeepMind’s approach to the protein folding problem:

In the experiment, DeepMind used a new deep learning architecture for AlphaFold that was able to interpret and compute the spatial graph of 3D proteins, predicting the molecular structure underpinning their folded configuration.

CASP scientists analyzed the shape of amino acid sequences for a set of about 100 proteins and AlphaFold's assessment lined up almost perfectly with two-thirds of proteins. These algorithms are becoming strong and powerful to be applicable to scientific problems.

A better understanding of protein structures and the ability to predict them using a computer means a better understanding of life, evolution and human health and disease said Janet Thornton, director emeritus of European Bioinfomatics Institute.

1. https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology
2. https://www.nature.com/articles/d41586-020-03348-4
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