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Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites

Author

Listed:
  • Parisa Hosseinzadeh

    (Institute for Protein Design
    University of Oregon)

  • Paris R. Watson

    (University of Pennsylvania)

  • Timothy W. Craven

    (Institute for Protein Design)

  • Xinting Li

    (Institute for Protein Design)

  • Stephen Rettie

    (Institute for Protein Design
    University of Washington)

  • Fátima Pardo-Avila

    (Stanford University School of Medicine)

  • Asim K. Bera

    (Institute for Protein Design)

  • Vikram Khipple Mulligan

    (Institute for Protein Design
    Flatiron Institute)

  • Peilong Lu

    (Institute for Protein Design
    Westlake University)

  • Alexander S. Ford

    (Institute for Protein Design)

  • Brian D. Weitzner

    (Institute for Protein Design
    Lyell Immunopharma, Inc.)

  • Lance J. Stewart

    (Institute for Protein Design)

  • Adam P. Moyer

    (Institute for Protein Design
    University of Washington)

  • Maddalena Piazza

    (Institute for Protein Design)

  • Joshua G. Whalen

    (Institute for Protein Design)

  • Per Jr. Greisen

    (Institute for Protein Design
    Novo Nordisk A/S)

  • David W. Christianson

    (University of Pennsylvania)

  • David Baker

    (Institute for Protein Design)

Abstract

Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational “anchor extension” methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC50 values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain.

Suggested Citation

  • Parisa Hosseinzadeh & Paris R. Watson & Timothy W. Craven & Xinting Li & Stephen Rettie & Fátima Pardo-Avila & Asim K. Bera & Vikram Khipple Mulligan & Peilong Lu & Alexander S. Ford & Brian D. Weitzn, 2021. "Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-23609-8
    DOI: 10.1038/s41467-021-23609-8
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    Cited by:

    1. Sijie Chen & Tong Lin & Ruchira Basu & Jeremy Ritchey & Shen Wang & Yichuan Luo & Xingcan Li & Dehua Pei & Levent Burak Kara & Xiaolin Cheng, 2024. "Design of target specific peptide inhibitors using generative deep learning and molecular dynamics simulations," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    2. Pritha Ghosh & Nishant Raj & Hitesh Verma & Monika Patel & Sohini Chakraborti & Bhavesh Khatri & Chandrashekar M. Doreswamy & S. R. Anandakumar & Srinivas Seekallu & M. B. Dinesh & Gajanan Jadhav & Pr, 2023. "An amide to thioamide substitution improves the permeability and bioavailability of macrocyclic peptides," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. 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.

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