Evidence map›Paper›PMID 42539255›Full record

ArticlebioRxiv : the preprint server for biology2026

Programming protein shape as an explicit design layer via CAD blueprint-guided diffusion.

Yilun Qi, Guoxun Zhang, Klaus Yserentant, Sonya Lee, Artem Lyubimov, Kyrellos Ibrahim, Giuseppe Cimicata, James S Fraser, Bo Huang, Tanja Kortemme

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yilun QiDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA.
Guoxun ZhangDepartment of Pharmaceutical Chemistry, University of California, San Francisco; San Francisco, CA, USA.
Klaus YserentantDepartment of Pharmaceutical Chemistry, University of California, San Francisco; San Francisco, CA, USA.
Sonya LeeDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA.
Artem LyubimovDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA.
Kyrellos IbrahimDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA.
Giuseppe CimicataDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA.
James S FraserDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA.ORCID 0000-0002-5080-2859
Bo HuangDepartment of Pharmaceutical Chemistry, University of California, San Francisco; San Francisco, CA, USA.ORCID 0000-0003-1704-4141
Tanja KortemmeDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In engineering, industrial design principles link geometric form with function. In nature, global protein shape, curvature, and chirality similarly drive critical processes like membrane remodeling and cellular motility. However, explicitly programming these global features remains a challenge for generative AI. Here, we integrate computer-aided design (CAD) blueprints with diffusion models, establishing protein shape as an explicit, programmable layer. We engineered diverse, tunable architectures, including single-chain shapes, scaffolds with unusual twist handedness, and superhelical assemblies, structurally validating 31 of 59 designs via X-ray crystallography or electron microscopy. To demonstrate shape-encoded function, we coupled fluid-flow-optimized helical propellers to an F1-ATPase rotor, yielding a prototype ATP-dependent molecular swimmer. This framework translates industrial design principles to the molecular scale, enabling the programmable engineering of biomimetic architecture with emergent functions.

Identifiers

PMID42539255
PMCPMC13419775

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.