AlphaFold might be the most exciting scientific innovation of this century. From Google DeepMind, and first reported in 2020, it uses artificial intelligence to figure out a protein’s 3D structure. The technology has already been used to solve fundamental questions in biology, awarded the Nobel prize (in chemistry – to Demis Hassabis and John Jumper) and revolutionised drug discovery. Like most AI, it’s only getting better – and just getting started.
A protein’s structure gives us clues about its function, and helps us design new drugs. AlphaFold, which was trained on a huge database of experimentally solved structures called the Protein Data Bank, predicts a protein’s structure based on its amino acid sequence.
In the past, the first step would be to produce a vast amount of protein – using litres of a bacterium, or a virus. You’d pray for the protein to assemble into a crystal lattice (notoriously difficult), and then fire high-energy X-rays at it. This is called X-ray crystallography, and it could take years. Now, AlphaFold can do it in minutes (and a hell of a lot more cheaply, too).
When AlphaFold competed at a protein structure-solving competition in 2020, it was so good that some accused the AlphaFold team of cheating. At its first appearance, AlphaFold became the state of the art. Now, there are approximately 250,000,000 protein structures in the AlphaFold database, which has been used by almost 2 million people from 190 countries – many more people than can do X-ray crystallography!
I did my PhD on cancer biology. I would have loved to solve the structure of the protein I worked on. Maybe I could have even used it to make a new drug. Now, I can go to the AlphaFold server and produce a structure in five minutes that would have consumed my whole PhD.
Dr Pauline Lascaux, a molecular and structural biologist at the University of Oxford, said that AlphaFold was central to her latest study, which discovered a new way that cells repair DNA, and that more than 90% of the studies she reviews are citing it.
So what does drug discovery with AlphaFold look like? In this recent Science study, researchers used AlphaFold to predict the structure of the serotonin receptor, which controls mood. Through in silico testing (on computers) they tested which of 1.6bn (!) molecules could bind the AlphaFold structure. What they found was a series of molecules that bound much more tightly than drugs generated via the conventional – experimental – approach, which could be new drugs for mood disorders.
AlphaFold has only been around since 2020, but its impact has been meteoric. Here are the top three discoveries enabled by AlphaFold so far:
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Solving a decades-old problem: the structure of the nuclear pore complex, one of the biggest structures in the cell. This complex is the guardian of entry to the nucleus, which holds the cell’s DNA. It’s implicated in cancer, ageing and neurodegeneration – and now we know what it looks like at the atomic level.
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Finding a new liver cancer drug. In a lab (not in patients), the drug, which targets the cancer protein CDK20, prevented liver cancer growth.
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Helping to design a “molecular syringe”, which delivers a therapeutic protein payload into human cells.
There are companies built on AlphaFold, too. If AlphaFold is solving the lock, then AlphaProteo provides the key. AlphaProteo uses AlphaFold’s structures to design molecules that can bind to and modulate other proteins. This has been used to generate molecules that have never been made before – to target Covid-19, cancer and autoimmunity.
Also from DeepMind, AlphaMissense tackles the problem of missense mutations – minor changes to genes, with uncertain functional impact. Despite their prevalence, we only know whether about 2% of these changes are pathogenic. AlphaMissense models the structure of the mutations using AlphaFold: if the protein structure changes, it’s probably pathogenic. This could transform the diagnosis and treatment of rare genetic diseases.
We don’t know yet whether drugs designed using AlphaFold will pass successfully through clinical trials, and none have been tested in humans yet – only time will tell.
In the future, AlphaFold could enable new medicines to be discovered by individuals, could find drugs for undruggable targets, and could unlock the secrets of molecular life. (Just the other day, AlphaFold helped to solve the structure of the sperm-egg bridge that forms during fertilisation.)
If the first generation of drug discovery was the nature generation, which gave us aspirin (from willow tree bark), and the second was the biotech generation, which gave us Ozempic, then we’ve now moved to the third generation: the AI generation.
