Development of chemokine network inhibitors using combinatorial saturation mutagenesis

Area of Science:

• Immunology and Pharmacology
• Drug Discovery and Development

Background:

• Chemokine-driven inflammation involves complex, redundant immune cell signaling networks, making targeted therapies challenging.
• Existing tick evasin-derived peptides can target CC or CXC chemokine classes, but broader action is needed.
• Traditional optimization methods are insufficient for targeting multiple chemokine classes simultaneously.

Purpose of the Study:

• To develop a novel strategy for creating broadly acting chemokine-targeting peptides.
• To identify a peptide with enhanced potency and breadth against multiple inflammatory chemokines.
• To understand the molecular interactions underlying the enhanced peptide's activity.

Main Methods:

• Development of a combinatorial saturation mutagenesis optimisation strategy (CoSMOS).
• Application of CoSMOS to generate and screen mutated evasin-derived peptides.
• In vitro assessment of peptide efficacy against inflammatory chemokine pools and molecular modeling using AlphaFold 3.

Main Results:

• CoSMOS identified a combinatorially mutated peptide with significantly enhanced potency (pIC50) against three distinct inflammatory chemokine pools.
• AlphaFold 3 modeling revealed increased inter-chain bonding and predicted steric hindrance of chemokine-immune cell interactions.
• The optimized peptide demonstrates enhanced binding and potential to disrupt immune cell migration pathways.

Conclusions:

• CoSMOS is an effective strategy for generating peptides with promiscuous binding activity against multiple chemokine targets.
• The developed peptide shows promise for targeting complex inflammatory disease networks driven by redundant signaling pathways.
• This approach offers a new avenue for developing potent and broad-acting anti-inflammatory agents.