Explained| AlphaFold: A tour de force in science

Source: The post is based on the article “Explained| AlphaFold: A tour de force in science” published in The Hindu on 2nd August 2022.

What is the News?

DeepMind, a company based in London and owned by Google announced that it had predicted the three-dimensional structures of more than 200 million proteins using AlphaFold.

What is AlphaFold?

AlphaFold is an AI-based protein structure prediction tool. It is based on a computer system called deep neural network. 

How does AlphaFold work?

It uses processes based on “training, learning, retraining and relearning”. By using this method, AlphaFold has now predicted the structures of the entire 214 million unique protein sequences deposited in the Universal Protein Resource(UniProt) database.

What are the implications of this development?

Proteins are the business ends of biology, meaning proteins carry out all the functions inside a living cell. Therefore, knowing protein structure and function is essential to understanding human diseases. 

Scientists predict protein structures using x-ray crystallography, nuclear magnetic resonance spectroscopy, or cryogenic electron microscopy. 

These techniques are not just time-consuming, they often take years and are based mainly on trial-and-error methods.

Therefore, the development of AlphaFold changes all of that. It is a watershed movement in science and structural biology in particular.

Is AlphaFold the only tool for predicting protein structures?

AlphaFold is neither flawless nor the only AI-based protein structure prediction tool.

RoseTTaFold, developed at the University of Washington in Seattle, U.S., is another tool. Although less accurate than AlphaFold, it can predict the structure of protein complexes.