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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.
Cyclic peptides are of particular interest due to their pharmacological properties, but their design for binding to a target protein is challenging. Here, the authors present a computational “anchor extension” methodology for de novo design of cyclic peptides that bind to the target protein with high affinity, and validate the approach by developing cyclic peptides that inhibit histone deacetylases 2 and 6.
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1 Institute for Protein Design, University of Washington, Department of Biochemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); University of Oregon, Knight Campus Center, Eugene, USA (GRID:grid.170202.6) (ISNI:0000 0004 1936 8008)
2 University of Pennsylvania, Roy and Diana Vagelos Laboratories, Department of Chemistry, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972)
3 Institute for Protein Design, University of Washington, Department of Biochemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657)
4 Institute for Protein Design, University of Washington, Department of Biochemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); University of Washington, Molecular and Cellular Biology Ph.D. Program, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657)
5 Stanford University School of Medicine, Department of Structural Biology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)
6 Institute for Protein Design, University of Washington, Department of Biochemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); Flatiron Institute, Systems Biology, Center for Computational Biology, New York, USA (GRID:grid.34477.33)
7 Institute for Protein Design, University of Washington, Department of Biochemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); Westlake University, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Hangzhou, China (GRID:grid.494629.4) (ISNI:0000 0004 8008 9315)
8 Institute for Protein Design, University of Washington, Department of Biochemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); Lyell Immunopharma, Inc., Seattle, USA (GRID:grid.510010.5)
9 Institute for Protein Design, University of Washington, Department of Biochemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); University of Washington, Molecular Engineering Ph.D. Program, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657)
10 Institute for Protein Design, University of Washington, Department of Biochemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); Novo Nordisk A/S, Måløv, Denmark (GRID:grid.425956.9) (ISNI:0000 0001 2264 864X)