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.
Highlights
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
We chose Histone deacetlyase (HDACs) as model targets to test our approach because of the wealth of structural data available for these enzymes, the simplicity of testing binding through enzymatic inhibition, and the relative ease of growing crystals of HDACs which facilitates structural characterization of new designs
HDAC2 belongs to a protein superfamily with 11 members, many of which share high structural homology[29,30] (Fig. 1a, Supplementary Fig. 1b); being able to selectively bind to only HDAC2 present a challenge for computational design of selectivity
Summary
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. Most current peptide binder design methods take advantage of one or more co-crystal structures of the target protein with a protein binding partner, and generate binders by stabilizing or scaffolding the interacting structural elements[20,21,22,23,24], or mimicking[25] or enhancing the binding interface by amino acid substitions[26]. The three-dimensional structure of the target surface is needed for this approach and can be derived from an experimentally determined or computationally predicted protein structure This method takes advantage of a functional group from a molecule known to bind to the target surface of interest which serves as an anchor, around which a cyclic peptide is built using the generalized kinematic loop closure method in Rosetta software.
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