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SoS:BIO How Artificial Intelligence Shapes Science: Evidence from Structural Biology

Award Number: R01GM169340
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 07/03/2026
PERIOD OF PERFORMANCE END DATE: 06/30/2029

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SoS:BIO How Artificial Intelligence Shapes Science: Evidence from Structural Biology - PROJECT SUMMARY (See instructions): Artificial intelligence (Al) is transforming scientific research, yet systematic evidence on how specific Al tools alter the pace, direction, and productivity of science remains limited. This project investigates the effects of AlphaFold2 - a deep learning system released by Google DeepMind in 2021 that predicts protein three-dimensional structures with near-experimental accuracy - on structural biology and downstream biomedical research. Understanding protein structure is foundational to medicine: it informs how diseases arise and guides the design of drugs that bind to specific targets. Prior to AlphaFold2, determining protein structures required expensive, time-consuming experiments; AlphaFold2 has since made predicted structures available for over 200 million proteins, including the entire human proteome. The project pursues three specific aims. Aim 1 examines how AlphaFold2 has affected structural biologists' careers, including labor market outcomes for early-career researchers and salary and grant trajectories for established scientists whose experimental expertise may be displaced. Aim 2 investigates how AlphaFold2 has altered the rate and direction of experimental structure determination, including whether it has shifted research toward previously understudied proteins and changed individual researcher productivity. Aim 3 assesses downstream consequences for biomedical research and drug discovery, examining whether predicted structures have expanded follow-on research on proteins lacking experimental counterparts and accelerated early-stage pharmaceutical development. The research design combines causal inference methods with administrative datasets - including the Protein Data Bank, UniProt/Swiss-Prot, the Alpha Fold database, and OpenAlex - and an original survey of active structural biologists. The core identification strategy exploits the universal release of AlphaFold2 predictions as a natural experiment, comparing proteins with and without prior experimental structures in a difference-in-differences framework. The findings will contribute to the economics of science, the economics of Al, and the empirical literature on how research tools shape biomedical discovery.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $206,410 )
2026	2026	REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE	119 CALIFORNIA HALL	BERKELEY	CA	94720	ALAMEDA	USA	Biomedical Research and Research Training	000	1	7/3/2026	NEW	$206,410
														Subtotal = $206,410

Grand Total All Awards = $206,410

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SoS:BIO How Artificial Intelligence Shapes Science: Evidence from Structural Biology

Award Number: R01GM169340

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 07/03/2026

PERIOD OF PERFORMANCE END DATE: 06/30/2029

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