ArticleProceedings of the National Academy of Sciences of the United States of America2026
Profile of David Baker, Demis Hassabis, and John Jumper: 2024 Nobel laureates in chemistry.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- AI-driven drug reposition for pathogens: a new paradigm in pandemic preparedness.Frontiers in chemistry · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The 2024 Nobel Prize in Chemistry recognized revolutionary computational success in predicting protein structures from amino acid sequences and for designing amino acid sequences that fold into desired protein structures. The ultimate accomplishment emerged principally from two labs, applying distinct approaches, culminating four decades of effort by the community of protein scientists. The lab of David Baker at the University of Washington made protein design a reality by adapting methods of classical physical chemistry. Demis Hassabis and John Jumper in the Deep Mind division of Google applied co-evolution and AI methods to enable prediction of protein models remarkably close to experimentally determined structures and prediction of vast numbers of structures of proteins not yet experimentally studied.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.