Study Overview
We study how a frontier AI model affects scientific discovery by examining the release of the AlphaFold2 algorithm and its impact on structural biology and related fields of science. Structural biology is the field of science concerned with understanding the structure and function of proteins. Researchers in this field historically devoted substantial time and resources to experimentally solving three-dimensional protein structures. AlphaFold can predict these structures without running experiments.
Study Results
In July 2021, researchers gained access to hundreds of thousands of these AI-predicted structures virtually overnight. Yet, to date, we find that the rate of experimental structure determination has remained almost unchanged. Instead, researchers appear to use predicted structures to facilitate and complement experimental structure determination. Looking at downstream science that builds on protein structures, we find that basic research on proteins that had no structure information prior to AlphaFold increases by 15 to 40% relative to proteins that already had a structure, shifting the direction of research toward less-studied proteins. However, we find no evidence so far that more applied, early-stage drug development is targeting these proteins, though such activity may emerge in the future.
News & media
AI is expanding the boundaries of biological research. Will drug development follow?
May 27, 2026
A scant few years after a powerful artificial intelligence tool was hailed as a revolution that would transform drug discovery, a new UC Berkeley Haas study finds that Google’s AlphaFold2 has fundamentally broadened the landscape of scientific research by unlocking the structure of millions of proteins that had been too poorly understood to study.