DeepMind’s Protein Folding AI Is Going After Coronavirus

In very broad strokes, AI could be enormously helpful for initial drug discovery in two main ways: one, screening through millions of chemical compounds for potential drugs in simulation tests, far faster than any human expert; two, identifying targets that new drugs can latch onto, either to reduce their impact, or to slow their spread among people.

Their secret sauce? AlphaFold, a deep learning system that tries to predict protein structures accurately when no similar proteins exist.

How a protein “Looks” in 3D is essential for developing new drugs, especially for new viruses.

COVID-19’s spikey proteins also harbor a Trojan Horse that “Activates” it in certain cells with a complementary component.

Bottom line: if a drug is going to “Fit” into a protein like a key into a lock to trigger a whole cascade of nasty reactions, then the first step is to figure out the structure of the lock.

DeepMind is taking these data to the next level by focusing on a few understudied but potentially important proteins that could become drug or vaccine targets using machine learning.

Protein folding has been a decades-long, fundamental problem in biochemistry and drug discovery.

Almost all of our existing drugs grab onto certain proteins to work, so identifying protein structure is akin to surveying the enemy landscape and figuring out best attack point simultaneously.

The problem is the genetic code doesn’t translate to how proteins look.

When it comes to a new virus, without predicting protein structures we’re basically fighting viruses and diseases as if they were the Invisible Man.

Traditional methods use high-tech microscopes, freezing proteins into crystal-looking entities, and other strange and expensive ways to understand their structure.

Under the scope, a protein is basically a chain of chemical “Letters” that wrap around itself into intricate structures-kinda like how your headphones always tangle into inconceivable structures while you’re sleeping.

AlphaFold stands out as a union of decades of deep learning progress, but guided by expertise from protein structure databases in the public domain.

In a nutshell, AlphaFold uses genome sequences to predict the properties of resulting proteins that actually do the work, by looking at the “Distance” of each “Letter” or component that makes up a certain protein.

China’s long-time Google surrogate and AI behemoth, Baidu, is using an algorithm to predict the structure of another important biomolecule, mRNA. mRNA shuttles information from the genome to protein factories, so shoot the mRNA messenger, then the viral proteins are never born.