IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-51723-w.html
   My bibliography  Save this article

Triscysteine disulfide-directing motifs enabling design and discovery of multicyclic peptide binders

Author

Listed:
  • Zengping Duan

    (Xiamen University)

  • Chuilian Kong

    (Xiamen University)

  • Shihui Fan

    (Xiamen University)

  • Chuanliu Wu

    (Xiamen University)

Abstract

Peptides are valuable for therapeutic development, with multicyclic peptides showing promise in mimicking antigen-binding potency of antibodies. However, our capability to engineer multicyclic peptide scaffolds, particularly for the construction of large combinatorial libraries, is still limited. Here, we study the interplay of disulfide pairing between three biscysteine motifs, and designed a range of triscysteine motifs with unique disulfide-directing capability for regulating the oxidative folding of multicyclic peptides. We demonstrate that incorporating these motifs into random sequences allows the design of disulfide-directed multicyclic peptide (DDMP) libraries with up to four disulfide bonds, which have been applied for the successful discovery of peptide binders with nanomolar affinity to several challenging targets. This study encourages the use of more diverse disulfide-directing motifs for creating multicyclic peptide libraries and opens an avenue for discovering functional peptides in sequence and structural space beyond existing peptide scaffolds, potentially advancing the field of peptide drug discovery.

Suggested Citation

  • Zengping Duan & Chuilian Kong & Shihui Fan & Chuanliu Wu, 2024. "Triscysteine disulfide-directing motifs enabling design and discovery of multicyclic peptide binders," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51723-w
    DOI: 10.1038/s41467-024-51723-w
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-51723-w
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-51723-w?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. 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.
    2. Jennifer L Lahti & Adam P Silverman & Jennifer R Cochran, 2009. "Interrogating and Predicting Tolerated Sequence Diversity in Protein Folds: Application to E. elaterium Trypsin Inhibitor-II Cystine-Knot Miniprotein," PLOS Computational Biology, Public Library of Science, vol. 5(9), pages 1-15, September.
    3. Zachary R. Crook & Gregory P. Sevilla & Della Friend & Mi-Youn Brusniak & Ashok D. Bandaranayake & Midori Clarke & Mesfin Gewe & Andrew J. Mhyre & David Baker & Roland K. Strong & Philip Bradley & Jam, 2017. "Mammalian display screening of diverse cystine-dense peptides for difficult to drug targets," Nature Communications, Nature, vol. 8(1), pages 1-15, December.
    4. Edurne Rujas & Hong Cui & Taylor Sicard & Anthony Semesi & Jean-Philippe Julien, 2020. "Structural characterization of the ICOS/ICOS-L immune complex reveals high molecular mimicry by therapeutic antibodies," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    5. Bonny Gaby Lui & Nadja Salomon & Joycelyn Wüstehube-Lausch & Matin Daneschdar & Hans-Ulrich Schmoldt & Özlem Türeci & Ugur Sahin, 2020. "Targeting the tumor vasculature with engineered cystine-knot miniproteins," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    6. Gaurav Bhardwaj & Vikram Khipple Mulligan & Christopher D. Bahl & Jason M. Gilmore & Peta J. Harvey & Olivier Cheneval & Garry W. Buchko & Surya V. S. R. K. Pulavarti & Quentin Kaas & Alexander Eletsk, 2016. "Accurate de novo design of hyperstable constrained peptides," Nature, Nature, vol. 538(7625), pages 329-335, October.
    7. Aaron Chevalier & Daniel-Adriano Silva & Gabriel J. Rocklin & Derrick R. Hicks & Renan Vergara & Patience Murapa & Steffen M. Bernard & Lu Zhang & Kwok-Ho Lam & Guorui Yao & Christopher D. Bahl & Shin, 2017. "Massively parallel de novo protein design for targeted therapeutics," Nature, Nature, vol. 550(7674), pages 74-79, October.
    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. Edin Muratspahić & Kristine Deibler & Jianming Han & Nataša Tomašević & Kirtikumar B. Jadhav & Aina-Leonor Olivé-Marti & Nadine Hochrainer & Roland Hellinger & Johannes Koehbach & Jonathan F. Fay & Mo, 2023. "Design and structural validation of peptide–drug conjugate ligands of the kappa-opioid receptor," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    2. Tamuka M. Chidyausiku & Soraia R. Mendes & Jason C. Klima & Marta Nadal & Ulrich Eckhard & Jorge Roel-Touris & Scott Houliston & Tibisay Guevara & Hugh K. Haddox & Adam Moyer & Cheryl H. Arrowsmith & , 2022. "De novo design of immunoglobulin-like domains," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    3. Jorge Roel-Touris & Marta Nadal & Enrique Marcos, 2023. "Single-chain dimers from de novo immunoglobulins as robust scaffolds for multiple binding loops," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    4. Yan Zou & Yajing Sun & Yibin Wang & Dongya Zhang & Huiqing Yang & Xin Wang & Meng Zheng & Bingyang Shi, 2023. "Cancer cell-mitochondria hybrid membrane coated Gboxin loaded nanomedicines for glioblastoma treatment," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    5. Nathaniel R. Bennett & Brian Coventry & Inna Goreshnik & Buwei Huang & Aza Allen & Dionne Vafeados & Ying Po Peng & Justas Dauparas & Minkyung Baek & Lance Stewart & Frank DiMaio & Steven Munck & Savv, 2023. "Improving de novo protein binder design with deep learning," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    6. Lucien F. Krapp & Fernando A. Meireles & Luciano A. Abriata & Jean Devillard & Sarah Vacle & Maria J. Marcaida & Matteo Dal Peraro, 2024. "Context-aware geometric deep learning for protein sequence design," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    7. 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.
    8. Karen J. Gonzalez & Jiachen Huang & Miria F. Criado & Avik Banerjee & Stephen M. Tompkins & Jarrod J. Mousa & Eva-Maria Strauch, 2024. "A general computational design strategy for stabilizing viral class I fusion proteins," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    9. Julia Koehler Leman & Sergey Lyskov & Steven M. Lewis & Jared Adolf-Bryfogle & Rebecca F. Alford & Kyle Barlow & Ziv Ben-Aharon & Daniel Farrell & Jason Fell & William A. Hansen & Ameya Harmalkar & Je, 2021. "Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    10. Betz, Ulrich A.K. & Arora, Loukik & Assal, Reem A. & Azevedo, Hatylas & Baldwin, Jeremy & Becker, Michael S. & Bostock, Stefan & Cheng, Vinton & Egle, Tobias & Ferrari, Nicola & Schneider-Futschik, El, 2023. "Game changers in science and technology - now and beyond," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    11. Fabian Sesterhenn & Che Yang & Jaume Bonet & Johannes T. Cramer & Xiaolin Wen & Yimeng Wang & Chi I. Chiang & Luciano Andres Abriata & Iga Kucharska & Giacomo Castoro & Sabrina S. Vollers & Marie Gall, 2020. "De novo protein design enables the precise induction of RSV-neutralizing antibodies," Post-Print hal-02677103, HAL.
    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. 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:15:y:2024:i:1:d:10.1038_s41467-024-51723-w. 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.