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Schuhmacher, M. ; Gruber, C. ; Lang, C.M.R. ; Ruijpers, R.M.W. ; Mazneykova, L. ; Beinsteiner, B. ; Krus, A. ; Tremmel, B. ; Reinhardt, F. ; Kadletz, K. ; Ma, Z. ; Casalta, L.* ; Cambra, J.M.* ; Otify, D.Y.* ; Balken, I. ; Hetzel, L. ; Merl-Pham, J. ; Dorn, T.* ; Luchner, M. ; Bauersachs, L. ; Ganea, K. ; Wieser, N. ; Emrich, A. ; Yağmur, E. ; Rager, K. ; Sagindykova, G. ; Armbrust, N. ; Geilenkeuser, J. ; Westmeyer, G.G. ; Bećirović, E.* ; Biel, M.* ; Istvánffy, R.* ; Weisenhorn, D.M. ; Truong, D.J.J. ; Theis, F.J. ; Ebert, G. ; Moretti, A.* ; Ertürk, A. ; Bähr, A.* ; Kupatt, C.* ; Jasnin, M. ; Klymiuk, N.* ; Giesert, F. ; Wurst, W.

Creating bottom-up RNA transfer vehicles from synthetic protein assemblies.

Nature, DOI: 10.1038/s41586-026-10952-3 (2026)
Verlagsversion Forschungsdaten DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
Evolution guides biological systems to populate ecological niches, with viruses among the most successful examples of this principle. Viruses evolved over billions of years to efficiently transfer genetic information. Although viruses are highly diverse, most have converged towards remarkable similarity in the size and shape of their capsids1,2. By contrast, generative models for protein design enable the creation of protein architectures that are absent from nature3-5. Here we investigate whether protein assemblies designed by artificial intelligence can be functionalized to construct nucleic acid transport vehicles that are independent of evolutionary trajectories. By combining natural protein domains with synthetic protein assemblies, we create more than 100 bottom-up RNA transfer vehicles with unique sizes and shapes. These vehicles surpass the RNA transfer efficiency of widely used delivery vehicles by several orders of magnitude. In addition, we demonstrate that their tropism can be programmed by incorporation of computationally designed peptide binders and use them to deliver therapeutically relevant cargo RNAs into a wide range of cellular models. We show the in vivo biodistribution of one of these vehicles in a mouse at near-single-cell resolution, confirm its safety, and use it to perform a gene-editing treatment strategy for Duchenne muscular dystrophy in patient-derived cells and a pig. Our work demonstrates how proteins created by generative artificial intelligence can be harnessed for the rational engineering of RNA transport systems with the desired properties by overcoming the limitations of natural protein diversity.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Synthetic Biology ; Rna ; Capsid ; Nucleic Acid ; Artificial Cell ; Protein Engineering ; Rational Design ; Fusion Protein; Recognition; Origin; Label
ISSN (print) / ISBN 0028-0836
e-ISSN 1476-4687
Zeitschrift Nature
Verlag Nature Publishing Group
Verlagsort London
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Stem Cell Research (ISF)
Helmholtz Pioneer Campus (HPC)
Institute for Intelligent Biotechnologies (IBIO)
Institute of Virology (VIRO)
Institute of Computational Biology (ICB)
Core Facility Metabolomics and Proteomics (CF-MPC)
Institute of Synthetic Biomedicine (ISBM)
Cryo-EM facility (CEMP)
Förderungen Helmholtz Zentrum Munchen - Deutsches Forschungszentrum fur Gesundheit und Umwelt (GmbH)
Helmholtz Association through the Helmholtz Enterprise-Spin-off programme project ViroCas13
Helmholtz Association
Else Kroner-Fresenius-Stiftung
Bavarian Ministry of Economic Affairs, Regional Development and Energy (StMWi)
SPARK-BIH programme of the Berlin Institute of Health at Charite through project FusigenX
Volkswagen Foundation
Helmholtz Zentrum Munchen through Innovation & Translation Call project 'Cell-type specific delivery of programmable antivirals' (2025)
Helmholtz Zentrum Munchen through Innovation & Translation Call project 'Lead-indication for the STV delivery platform' (2026)
PROFOUND project
Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme
Federal Ministry of Research, Technology and Space (BMFTR)