Evidence map›Paper›PMID 40759748›Full record

ArticleNature methods2025

Rational engineering of allosteric protein switches by in silico prediction of domain insertion sites.

Benedict Wolf, Pegi Shehu, Luca Brenker, Anna-Lisa von Bachmann, Ann-Sophie Kroell, Nicholas Southern, Stefan Holderbach, Joshua Eigenmann, Sabine Aschenbrenner, Jan Mathony and 1 more

Abstract read
In one paragraph

Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Family-level specialization in protein domain insertion architectures.Protein science : a publication of the Protein Society · 2026
    Article
  10. Protein foundation models: a comprehensive survey.Science China. Life sciences · 2026
    Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
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

11 authors.

Benedict WolfInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.ORCID http://orcid.org/0009-0003-5688-3607
Pegi ShehuInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.
Luca BrenkerInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.
Anna-Lisa von BachmannInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.
Ann-Sophie KroellInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.
Nicholas SouthernInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.
Stefan HolderbachInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-0599-4716
Joshua EigenmannInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.ORCID http://orcid.org/0009-0007-5046-0661
Sabine AschenbrennerInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.
Jan MathonyInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany. jan.mathony@uni-heidelberg.de.ORCID http://orcid.org/0000-0003-4081-9953
Dominik NiopekInstitute of Pharmacy and Molecular Biotechnology, Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany. dominik.niopek@uni-heidelberg.de.ORCID http://orcid.org/0000-0001-7479-530X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Domain insertion engineering is a powerful approach to juxtapose otherwise separate biological functions, resulting in proteins with new-to-nature activities. A prominent example are switchable protein variants, created by receptor domain insertion into effector proteins. Identifying suitable, allosteric sites for domain insertion, however, typically requires extensive screening and optimization. We present ProDomino, a machine learning pipeline to rationalize domain recombination, trained on a semisynthetic protein sequence dataset derived from naturally occurring intradomain insertion events. ProDomino robustly identifies domain insertion sites in proteins of biotechnological relevance, which we experimentally validated in Escherichia coli and human cells. Finally, we used light- and chemically regulated receptor domains as inserts and demonstrate the rapid, model-guided creation of potent, single-component opto- and chemogenetic protein switches. These include novel CRISPR-Cas9 and -Cas12a variants for inducible genome engineering in human cells. Our work enables one-shot domain insertion engineering and substantially accelerates the design of customized allosteric proteins.

Indexed as

Protein EngineeringProteinsAllosteric RegulationAllosteric SiteComputer SimulationCRISPR-Cas SystemsEscherichia coliHumansMachine LearningProtein DomainsProteins

Identifiers

PMID40759748
PMCPMC12328240

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LicenceCC BY
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Registered trials

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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.