Development of chemokine network inhibitors using combinatorial saturation mutagenesis.

Targeting chemokine-driven inflammation has been elusive due to redundant pathways constituting chemokine-immune cell networks. Tick evasins overcome redundant pathways by broadly targeting either CC or CXC-chemokine classes. Recently identified evasin-derived peptides inhibiting both chemokine classes provide a starting point for developing agents with enhanced potency and breadth of action. Structure-guided and affinity maturation approaches to achieve this are unsuitable when multiple targets are concerned. Here we develop a combinatorial saturation mutagenesis optimisation strategy (CoSMOS). This identifies a combinatorially mutated evasin-derived peptide with significantly enhanced pIC against three different inflammatory disease chemokine pools. Using AlphaFold 3 to model peptide - chemokine interactions, we show that the combinatorially mutated peptide has increased total and hydrophobic inter-chain bonding via tryptophan residues and is predicted to sterically hinder chemokine interactions required for immune cell migration. We suggest that CoSMOS-generated promiscuous binding activities could target disease networks where structurally related proteins drive redundant signalling pathways.