Research on unsolved proteins rose 15 to 40% after AlphaFold, a working paper finds

The paper treats AlphaFold as a test of how AI changes research. Solving one protein structure by experiment can take months to years and cost $100,000 or more. Free predictions for hundreds of thousands of proteins removed that bottleneck for the roughly 92% of curated SwissProt proteins that had no experimental structure, and attention moved toward them.

The effect has not yet reached drug discovery. The authors saw no change in early-stage drug research on the newly illuminated proteins in the three years after release, though they call the results noisy. Experimental structure determination has also barely slowed, so predictions are so far a complement to lab work, not a replacement.

The authors built a protein-level panel from SwissProt, a curated database of 546,646 proteins with AlphaFold predictions, linking each to curated papers, citations in OpenAlex and drug-binding data in ChEMBL. They dropped papers about structures themselves to measure research beyond structure solving. AlphaFold released 365,000 predicted structures in July 2021, 560,000 more in December 2021 and over 200 million in July 2022.

On experimental work, the paper finds little substitution. Using 61,638 Protein Data Bank deposits from 2017 to early 2024, researchers kept depositing structures at an indistinguishable or slightly higher rate, and the structures kept appearing in journals including Cell, Nature and Science. The predicted confidence of structures being solved dropped about one point, against a standard deviation above ten, so scientists did not pivot to proteins AlphaFold handles poorly.

The authors say predictions are not perfect stand-ins. They cite a comparison of about 100 structures in which roughly 10% of very confidently placed amino acids were meaningfully misplaced, and note that AlphaFold typically predicts a protein's default state. They also caution that continued lab work may reflect researcher incentives, not efficiency, and that AI could replace experiments as models improve.

In an example from the paper, Andrea Pauli's lab used an AlphaFold structure of a previously unsolved sperm protein, Tmem81, to hypothesize that three sperm proteins form a complex that recognizes the egg protein Bouncer. They validated the idea with experiments and published it in Cell in 2024.

On drugs, the authors say it is too early to expect new medicines. They argue that more basic science may be needed before the new structures become drug targets, and that activity could still emerge later.