Google Research says AI agents running physical lab robots found protein binders with single digit nanomolar affinity for a cancer target
We are bringing agents to the wet-lab bench at Google Research to navigate complex biological landscapes. Learn how we are grounding agents in physical lab robotics to run fast closed-loop molecular design cycles, ultimately discovering single-digit nanomolar protein binders for cancer targets →
Context
Letting agents run real experiments, not just design them on a computer, could speed up the slowest part of drug discovery, which is testing ideas in the lab.
This is a first hand post from Google Research linking a blog post by three of its scientists. The results come from Google's own papers and have not been independently reproduced.
Deep dive
On October 16, Google Research posted that it is bringing agents to the wet lab bench, grounding them in physical lab robotics to run fast closed loop molecular design cycles, and ultimately discovering single digit nanomolar protein binders for cancer targets.
The linked blog post, by Pooja Rao, Petar Sirkovic and Annalisa Pawlosky, describes three projects. The first, called VERID, is a live digital twin of the lab that tracks robot geometry, well volumes, reagents and pipette tips, so agents can simulate liquid handling protocols and have unsafe commands blocked before they reach the robot. Google says that in one test an agent improved accuracy more than fivefold by spotting its own errors across runs.
The second project used DNA aptamers, short strands that bind proteins, over three design and test rounds. Google says agents raised confirmed hit rates to 33.5% for myoglobin and 42.1% for thrombin, after revising their design rules when lab results exposed problems.
The third targeted FAP, a protein overexpressed in solid tumors. Google says a pipeline that cuts out only the binding pocket sped up structure prediction 8.6 times, and that a scientist working with an agent nearly doubled the computer hit rate of a scientist alone. The top designs bound with single digit nanomolar affinity, which Google calls drug like.
Google says humans approve designed sequences and supervise robot runs, and every sequence goes through biosecurity screening.
What to expect next
Watch whether Google publishes the underlying papers and data so other labs can check the results, and whether the FAP binders move toward testing as possible treatments.
Also watch Google's stated next step of combining VERID with closed loop protein discovery, and how rivals such as OpenAI, Anthropic and Isomorphic Labs respond with their own lab automation work. How safety and biosecurity checks scale as agents take on more lab work will be an open question.