IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-38697-x.html
   My bibliography  Save this article

A multiplexed bacterial two-hybrid for rapid characterization of protein–protein interactions and iterative protein design

Author

Listed:
  • W. Clifford Boldridge

    (University of California)

  • Ajasja Ljubetič

    (National Institute of Chemistry
    EN-FIST Centre of Excellence)

  • Hwangbeom Kim

    (University of California
    Samsung Biologics)

  • Nathan Lubock

    (University of California
    Octant Inc)

  • Dániel Szilágyi

    (University of Primorska)

  • Jonathan Lee

    (University of California
    University of Southern California)

  • Andrej Brodnik

    (University of Primorska)

  • Roman Jerala

    (National Institute of Chemistry
    EN-FIST Centre of Excellence)

  • Sriram Kosuri

    (University of California
    University of California, Los Angeles
    University of California, Los Angeles
    University of California, Los Angeles)

Abstract

Protein-protein interactions (PPIs) are crucial for biological functions and have applications ranging from drug design to synthetic cell circuits. Coiled-coils have been used as a model to study the sequence determinants of specificity. However, building well-behaved sets of orthogonal pairs of coiled-coils remains challenging due to inaccurate predictions of orthogonality and difficulties in testing at scale. To address this, we develop the next-generation bacterial two-hybrid (NGB2H) method, which allows for the rapid exploration of interactions of programmed protein libraries in a quantitative and scalable way using next-generation sequencing readout. We design, build, and test large sets of orthogonal synthetic coiled-coils, assayed over 8,000 PPIs, and used the dataset to train a more accurate coiled-coil scoring algorithm (iCipa). After characterizing nearly 18,000 new PPIs, we identify to the best of our knowledge the largest set of orthogonal coiled-coils to date, with fifteen on-target interactions. Our approach provides a powerful tool for the design of orthogonal PPIs.

Suggested Citation

  • W. Clifford Boldridge & Ajasja Ljubetič & Hwangbeom Kim & Nathan Lubock & Dániel Szilágyi & Jonathan Lee & Andrej Brodnik & Roman Jerala & Sriram Kosuri, 2023. "A multiplexed bacterial two-hybrid for rapid characterization of protein–protein interactions and iterative protein design," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38697-x
    DOI: 10.1038/s41467-023-38697-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-38697-x
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-38697-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Po-Ssu Huang & Scott E. Boyken & David Baker, 2016. "The coming of age of de novo protein design," Nature, Nature, vol. 537(7620), pages 320-327, September.
    2. Jana Aupič & Žiga Strmšek & Fabio Lapenta & David Pahovnik & Tomaž Pisanski & Igor Drobnak & Ajasja Ljubetič & Roman Jerala, 2021. "Designed folding pathway of modular coiled-coil-based proteins," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    3. Jae-Seong Yang & Mireia Garriga-Canut & Nele Link & Carlo Carolis & Katrina Broadbent & Violeta Beltran-Sastre & Luis Serrano & Sebastian P. Maurer, 2018. "rec-YnH enables simultaneous many-by-many detection of direct protein–protein and protein–RNA interactions," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    4. Zibo Chen & Scott E. Boyken & Mengxuan Jia & Florian Busch & David Flores-Solis & Matthew J. Bick & Peilong Lu & Zachary L. VanAernum & Aniruddha Sahasrabuddhe & Robert A. Langan & Sherry Bermeo & T. , 2019. "Programmable design of orthogonal protein heterodimers," Nature, Nature, vol. 565(7737), pages 106-111, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thomas W. Linsky & Kyle Noble & Autumn R. Tobin & Rachel Crow & Lauren Carter & Jeffrey L. Urbauer & David Baker & Eva-Maria Strauch, 2022. "Sampling of structure and sequence space of small protein folds," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Estera Merljak & Benjamin Malovrh & Roman Jerala, 2023. "Segmentation strategy of de novo designed four-helical bundles expands protein oligomerization modalities for cell regulation," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    3. Jordan Yang & Nandita Naik & Jagdish Suresh Patel & Christopher S Wylie & Wenze Gu & Jessie Huang & F Marty Ytreberg & Mandar T Naik & Daniel M Weinreich & Brenda M Rubenstein, 2020. "Predicting the viability of beta-lactamase: How folding and binding free energies correlate with beta-lactamase fitness," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-26, May.
    4. Agnese I. Curatolo & Ofer Kimchi & Carl P. Goodrich & Ryan K. Krueger & Michael P. Brenner, 2023. "A computational toolbox for the assembly yield of complex and heterogeneous structures," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    5. Anna-Maria Makri Pistikou & Glenn A. O. Cremers & Bryan L. Nathalia & Theodorus J. Meuleman & Bas W. A. Bögels & Bruno V. Eijkens & Anne Dreu & Maarten T. H. Bezembinder & Oscar M. J. A. Stassen & Car, 2023. "Engineering a scalable and orthogonal platform for synthetic communication in mammalian cells," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    6. Biao Ruan & Yanan He & Yingwei Chen & Eun Jung Choi & Yihong Chen & Dana Motabar & Tsega Solomon & Richard Simmerman & Thomas Kauffman & D. Travis Gallagher & John Orban & Philip N. Bryan, 2023. "Design and characterization of a protein fold switching network," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    7. Noelia Ferruz & Steffen Schmidt & Birte Höcker, 2022. "ProtGPT2 is a deep unsupervised language model for protein design," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    8. Pengfei Tian & Robert B Best, 2020. "Exploring the sequence fitness landscape of a bridge between protein folds," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-19, October.
    9. Julia Skokowa & Birte Hernandez Alvarez & Murray Coles & Malte Ritter & Masoud Nasri & Jérémy Haaf & Narges Aghaallaei & Yun Xu & Perihan Mir & Ann-Christin Krahl & Katherine W. Rogers & Kateryna Maks, 2022. "A topological refactoring design strategy yields highly stable granulopoietic proteins," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    10. Anton Kocheturov & Panos M. Pardalos & Athanasia Karakitsiou, 2019. "Massive datasets and machine learning for computational biomedicine: trends and challenges," Annals of Operations Research, Springer, vol. 276(1), pages 5-34, May.
    11. Fatima A. Davila-Hernandez & Biao Jin & Harley Pyles & Shuai Zhang & Zheming Wang & Timothy F. Huddy & Asim K. Bera & Alex Kang & Chun-Long Chen & James J. Yoreo & David Baker, 2023. "Directing polymorph specific calcium carbonate formation with de novo protein templates," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    12. SM Bargeen Alam Turzo & Justin T. Seffernick & Amber D. Rolland & Micah T. Donor & Sten Heinze & James S. Prell & Vicki H. Wysocki & Steffen Lindert, 2022. "Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    13. Smrithi Krishnan R & Kalyanashis Jana & Amina H. Shaji & Karthika S. Nair & Anjali Devi Das & Devika Vikraman & Harsha Bajaj & Ulrich Kleinekathöfer & Kozhinjampara R. Mahendran, 2022. "Assembly of transmembrane pores from mirror-image peptides," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    14. Shunshi Kohyama & Béla P. Frohn & Leon Babl & Petra Schwille, 2024. "Machine learning-aided design and screening of an emergent protein function in synthetic cells," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    15. Shuangjia Zheng & Tao Zeng & Chengtao Li & Binghong Chen & Connor W. Coley & Yuedong Yang & Ruibo Wu, 2022. "Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    16. Sasha B. Ebrahimi & Devleena Samanta, 2023. "Engineering protein-based therapeutics through structural and chemical design," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    17. Amir Pandi & David Adam & Amir Zare & Van Tuan Trinh & Stefan L. Schaefer & Marie Burt & Björn Klabunde & Elizaveta Bobkova & Manish Kushwaha & Yeganeh Foroughijabbari & Peter Braun & Christoph Spahn , 2023. "Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    18. Alexander E. Vlahos & Jeewoo Kang & Carlos A. Aldrete & Ronghui Zhu & Lucy S. Chong & Michael B. Elowitz & Xiaojing J. Gao, 2022. "Protease-controlled secretion and display of intercellular signals," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    19. Sicong Yao & Adam Moyer & Yiwu Zheng & Yang Shen & Xiaoting Meng & Chong Yuan & Yibing Zhao & Hongwei Yao & David Baker & Chuanliu Wu, 2022. "De novo design and directed folding of disulfide-bridged peptide heterodimers," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38697-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.