Bissan Al-Lazikani

The solving of a biological mystery

A representation of a myoglobin protein, found in the muscle tissue of most mammals

DNA is the blueprint that encodes the instructions to make proteins. Proteins are the building blocks and the machines that power life. And proteins make up the tissue that in turn comprise the organs and muscles that make up us. Considering how crucial proteins are to life itself, there is still so much we do not know about them. But Google’s AI firm Deepmind may just have helped us make a giant leap forward.

When a protein is first made inside a living cell, it is merely a chain of connected amino acids — like beads on a string. Yet, it instantaneously folds into unique three-dimensional, beautiful shapes, which enable them to carry out their function. When proteins go wrong — because of mutations or mistakes in folding — serious human diseases emerge, such as cancer and dementia.

Knowing the 3D structures of proteins has a transformative impact on the discovery of new drugs

Knowing the 3D structures of proteins has a transformative impact on the discovery of new drugs. When we design potential drugs, we need to know that they’re the right shape to fit, like a lock and key, into the protein that we want it to interact with. Otherwise, it might not work well enough — or it might not work at all.

Fundamental rules of physics govern this folding of proteins, which determines their biological function. Yet, many generations of scientists around the world have tried, with limited success, to use these rules to predict the way proteins fold. Of the 11,362,682 amino acids that make up the human proteome — all of the proteins found in the human body — we have modelled the experimental structures of just 17 per cent of them.

Computational prediction methods have historically come to the rescue of more traditional technologies that we use in the lab, such as electron microscopy.

Already a subscriber? Log in

Keep reading with a free trial

Subscribe and get your first month of online and app access for free. After that it’s just £1 a week.

There’s no commitment, you can cancel any time.

Or

Unlock more articles

REGISTER

Comments

Don't miss out

Join the conversation with other Spectator readers. Subscribe to leave a comment.

Already a subscriber? Log in