Proteins involved in immune checkpoint pathways, such as CTLA4, PD1, and PD-L1, have become important targets for cancer immunotherapy; however, development of small molecule drugs targeting these pathways has proven difficult due to the nature of their protein–protein interfaces. Here, using a hierarchy of computational techniques, we design a cyclic peptide that binds CTLA4 and follow this with experimental verification of binding and biological activity, using bio-layer interferometry, cell culture, and a mouse tumor model. Beginning from a template excised from the X-ray structure of the CTLA4:B7-2 complex, we generate several peptide sequences using flexible docking and modeling steps. These peptides are cyclized head-to-tail to improve structural and proteolytic stability and screened using molecular dynamics simulation and MM-GBSA calculation. The standard binding free energies for shortlisted peptides are then calculated in explicit-solvent simulation using a rigorous multistep technique. The most promising peptide, cyc(EIDTVLTPTGWVAKRYS), yields the standard free energy −6.6 ± 3.5 kcal mol^−1, which corresponds to a dissociation constant of ∼15 μmol L^−1. The binding affinity of this peptide for CTLA4 is measured experimentally (31 ± 4 μmol L^−1) using bio-layer interferometry. Treatment with this peptide inhibited tumor growth in a co-culture of Lewis lung carcinoma (LLC) cells and antigen primed T cells, as well as in mice with an orthotropic Lewis lung carcinoma allograft model.
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Peptide design by optimization on a data-parameterized protein interaction landscape
Many applications in protein engineering require optimizing multiple protein properties simultaneously, such as binding one target but not others or binding a target while maintaining stability. Such multistate design problems require navigating a high-dimensional space to find proteins with desired characteristics. A model that relates protein sequence to functional attributes can guide design to solutions that would be hard to discover via screening. In this work, we measured thousands of protein–peptide binding affinities with the high-throughput interaction assay amped SORTCERY and used the data to parameterize a model of the alpha-helical peptide-binding landscape for three members of the Bcl-2 family of proteins: Bcl-xL, Mcl-1, and Bfl-1. We applied optimization protocols to explore extremes in this landscape to discover peptides with desired interaction profiles. Computational design generated 36 peptides, all of which bound with high affinity and specificity to just one of Bcl-xL, Mcl-1, or Bfl-1, as intended. We designed additional peptides that bound selectively to two out of three of these proteins. The designed peptides were dissimilar to known Bcl-2–binding peptides, and high-resolution crystal structures confirmed that they engaged their targets as expected. Excellent results on this challenging problem demonstrate the power of a landscape modeling approach, and the designed peptides have potential uses as diagnostic tools or cancer therapeutics.
more » « less- NSF-PAR ID:
- 10077282
- Publisher / Repository:
- Proceedings of the National Academy of Sciences
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 115
- Issue:
- 44
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- p. E10342-E10351
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract De novo design provides an attractive approach, which allows one to test and refine the principles guiding metalloproteins in defining the geometry and reactivity of their metal ion cofactors. Although impressive progress has been made in designing proteins that bind transition metal ions including iron–sulfur clusters, the design of tetranuclear clusters with oxygen‐rich environments remains in its infancy. In previous work, we described the design of homotetrameric four‐helix bundles that bind tetra‐Zn2+clusters. The crystal structures of the helical proteins were in good agreement with the overall design, and the metal‐binding and conformational properties of the helical bundles in solution were consistent with the crystal structures. However, the correspondingapo ‐proteins were not fully folded in solution. In this work, we design three peptides, based on the crystal structure of the original bundles. One of the peptides forms tetramers in aqueous solution in the absence of metal ions as assessed by CD and NMR. It also binds Zn2+in the intended stoichiometry. These studies strongly suggest that the desired structure has been achieved in theapo state, providing evidence that the peptide is able to actively impart the designed geometry to the metal cluster. -
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