bioRxivBiochemistryPreprint
Selective suppression and biasing of chemokine receptors CCR9 and ACKR4 through targeting CCL25 with de novo miniproteins
Bas De BoeriD, Thomas D LammeiD, Karlijn Verdwaald, Sara Santamaria Medina, Csongor G NemethiD, Elisabeth M ElfrinkiD, Martine J. SmitiD, Iwan J. P. de EschiD, Christopher T. SchaferiD
Abstract
Chemokines and their receptors mediate cell migration and coordinate immune responses, while dysregulation can lead to inflammation. Therapeutic modulation of the chemokine signaling axis has proven difficult. Most drug discovery efforts target the receptors, whereas natural regulatory mechanisms modulate immune responses by directly binding to or modifying the chemokine ligands. Despite this insight, development of effective chemokine-directed modulators has remained elusive. Recent advances in de novo protein design offer an unprecedented opportunity to produce high-affinity binders that efficiently block protein-protein interactions. We implemented a computational workflow leveraging the BindCraft platform to generate miniprotein binders against CCL25, the chemokine ligand for the receptors CCR9 and ACKR4 and implicated in inflammatory bowel diseases. The unbiased development results in several miniproteins designed to block the receptor N-terminus from wrapping the chemokine and prevent productive engagement. Thus, these proteins suppress CCL25-mediated effector coupling and halt MOLT-4 lymphoblast migration. Another class of miniprotein, represented by VUP25111, is predicted to bind CCL25 along the chemokine {beta}1 strand and retained receptor binding. This complex inhibited arrestin recruitment to CCR9, but not to ACKR4, indicating receptor specificity. Additionally, G protein recruitment to CCR9 was unimpeded by VUP25111, suggesting that the miniprotein biased the native agonist towards G proteins. These results demonstrate the effectiveness of differentially targeting CCL25 to suppress CCR9 signaling and new tools to resolve the structural basis of chemokine receptor activation and bias.
- organism: human
- assay: protein structure
- research focus: drug response / drug discovery
- research focus: protein design
- research focus: cell-cell communication
- research focus: differential expression
- approach: deep learning
- approach: statistical model
- Citations
- 0
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