Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 20 min ago
Peer-reviewedCC BYScience

Structure and evolution-guided design of minimal RNA-guided nucleases

  • Petr Skopintsev1,2
  • Isabel Esain-Garcia1,2
  • Evan C. DeTurk1,2
  • Peter H. Yoon3,2
  • Zehan Zhou3,2
  • Trevor J. Weiss4
  • Maris Kamalu4
  • Ajit Chamraj3,2
  • Kenneth J. Loi1,2
  • Conner J. Langeberg1,2
  • Ron S. Boger5,1,2
  • Hunter M. Nisonoff6
8 more authors
  • Hannah Karp7,2
  • Lin-Xing Chen8
  • Honglue Shi1,2
  • Kamakshi Vohra1,2
  • Jillian F. Banfield8,9,2
  • Jamie H. D. Cate5,1,3,2,10
  • Steven E. Jacobsen4,11
  • Jennifer A. Doudna5,1,3,12,13,14,2,15,10
15 affiliations
  1. 1California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA, USA
  2. 2Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA
  3. 3Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
  4. 4Department of Molecular, Cell and Developmental Biology, University of California at Los Angeles, Los Angeles, CA, USA
  5. 5Biophysics Graduate Group, University of California, Berkeley, Berkeley, CA, CA, USA
  6. 6Center for Computational Biology, University of California Berkeley, Berkeley, CA, USA
  7. 7Department of Chemistry, University of California, Berkeley, Berkeley, CA, USA
  8. 8Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
  9. 9Department of Microbiology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
  10. 10Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
  11. 11Howard Hughes Medical Institute (HHMI), University of California at Los Angeles, Los Angeles, CA, USA
  12. 12Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
  13. 13Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
  14. 14Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA, USA
  15. 15Li Ka Shing Center for Genomic Engineering, University of California, Berkeley, Berkeley, CA, USA
Open at sourceDOICite

Abstract

The design of RNA-guided nucleases with properties not limited by evolution can expand programmable genome-editing capabilities. However, generating diverse multidomain proteins with robust enzymatic properties remains challenging. Here, we use a protein design strategy that couples a structure-guided inverse-folding model with evolution-informed residue constraints to generate active, divergent variants of TnpB, a minimal CRISPR-Cas12-like nuclease, termed SynTnpBs. High-throughput screening of artificial intelligence-generated variants yielded editors that retained or exceeded wild-type activity in bacterial, plant, and human cells. Cryo-electron microscopy-based structure determination of the most divergent variant revealed stabilizing contacts in the RNA-DNA interfaces across conformations, demonstrating the design potential of this approach. Together, these results establish a strategy for creating non-natural RNA-guided nucleases and conformationally active nucleic acid binders, enlarging the designable protein space.

Related

  1. Kinetics and Evolution-guided Design of High Fidelity CRISPR-Cas Endonucleases
    H. Liu, Z. Zhou, L. Yuan +15
    bioRxivPreprintAll rights reservedFull textBiophysicsbioRxiv
  2. Structure-guided design and dynamic evaluation of VP4-targeting siRNAs against rotavirus A
    Abu Nayeem Ahmed, Khaleda Jahan Satu, A. B. Z. Naimur Rahman +8
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textMolecular biology & gene regulationCrossref
  3. Convergent evolution of viral nucleases targeting cyclic dinucleotides
    Zichen Li, Leiliang Zhang
    PLOS PathogensPeer-reviewedCC BY 4.0Full textEnzymology & metabolismCell biologyPLOS
  4. PocketVE: Stable and Property-Guided Structure-Based Drug Design with Variance-Exploding Diffusion
    Peining Zhang, Jinbo Bi
    arXivPreprintCC BY 4.0Full textBiophysicsarXiv
  5. Probe Before You Edit: Probing-Guided Molecular Optimization for LLM Agents in Structure-Based Drug Design
    Zaifei Yang, Weiyu Chen, Yaqing Wang +1
    arXivPreprintCC BY 4.0Full textBiophysicsarXiv

Cite

BibTeXRIS
BibTeX
@article{skopintsev2026structure,
  title = {{Structure and evolution-guided design of minimal RNA-guided nucleases}},
  author = {Petr Skopintsev and Isabel Esain-Garcia and Evan C. DeTurk and Peter H. Yoon and Zehan Zhou and Trevor J. Weiss and Maris Kamalu and Ajit Chamraj and Kenneth J. Loi and Conner J. Langeberg and Ron S. Boger and Hunter M. Nisonoff and Hannah Karp and Lin-Xing Chen and Honglue Shi and Kamakshi Vohra and Jillian F. Banfield and Jamie H. D. Cate and Steven E. Jacobsen and Jennifer A. Doudna},
  journal = {Science},
  year = {2026},
  month = jul,
  doi = {10.1126/science.aed6123},
  url = {https://doi.org/10.1126/science.aed6123},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Structure and evolution-guided design of minimal RNA-guided nucleases
AU  - Petr Skopintsev
AU  - Isabel Esain-Garcia
AU  - Evan C. DeTurk
AU  - Peter H. Yoon
AU  - Zehan Zhou
AU  - Trevor J. Weiss
AU  - Maris Kamalu
AU  - Ajit Chamraj
AU  - Kenneth J. Loi
AU  - Conner J. Langeberg
AU  - Ron S. Boger
AU  - Hunter M. Nisonoff
AU  - Hannah Karp
AU  - Lin-Xing Chen
AU  - Honglue Shi
AU  - Kamakshi Vohra
AU  - Jillian F. Banfield
AU  - Jamie H. D. Cate
AU  - Steven E. Jacobsen
AU  - Jennifer A. Doudna
PY  - 2026
DA  - 2026/07/16
JO  - Science
DO  - 10.1126/science.aed6123
UR  - https://doi.org/10.1126/science.aed6123
AB  - The design of RNA-guided nucleases with properties not limited by evolution can expand programmable genome-editing capabilities. However, generating diverse multidomain proteins with robust enzymatic properties remains challenging. Here, we use a protein design strategy that couples a structure-guided inverse-folding model with evolution-informed residue constraints to generate active, divergent variants of TnpB, a minimal CRISPR-Cas12-like nuclease, termed SynTnpBs. High-throughput screening of artificial intelligence-generated variants yielded editors that retained or exceeded wild-type activity in bacterial, plant, and human cells. Cryo-electron microscopy-based structure determination of the most divergent variant revealed stabilizing contacts in the RNA-DNA interfaces across conformations, demonstrating the design potential of this approach. Together, these results establish a strategy for creating non-natural RNA-guided nucleases and conformationally active nucleic acid binders, enlarging the designable protein space.
SN  - 0036-8075
SN  - 0193-4511
SN  - 1095-9203
ER  -