This shapeshifting controls the biological processes of living things—for example, opening the protein tunnels dotted along neurons or driving cancerous growth. But it also makes understanding protein behavior and developing drugs that interact with proteins a challenge.

While recent AI breakthroughs in the prediction (and even generation) of protein structures are a huge advance 50 years in the making, they still only offer snapshots of proteins. To capture whole biological processes—and identify which lead to diseases—we need predictions of protein structures in multiple “poses” and, more importantly, how each of these poses changes a cell’s inner functions. And if we’re to rely on AI to solve the challenge, we need more data.

Thanks to a new protein atlas published this month in Nature, we now have a great start.

What could the consequences be in the future?

An interesting tweet is making headlines regarding Amazon’s adoption of robots within its company. Posted by Sam Korus, the tweet includes a graph showing the relative numbers of robots and human employees (in the thousands) at the beginning of every year between 2013 and 2022.

The graph shows a growing trend in the number of humans and robots over time, with a noticeable uptick during the pandemic as people spent more time shopping online at home. Korus’ tweet predicts that more robots will be employed than humans at some point in the future; he might have a point.

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