Rational Design of De Novo CCL2 Binding Peptides

Chronic levels of inflammation lead to autoimmune diseases such as rheumatoid arthritis and atherosclerosis. A key molecular mediator responsible for the progression of these diseases is Chemokine C-C motif ligand 2 (CCL2), a homodimerized cytokine that dissociates into monomeric form and binds to the CCR2 receptor. CCL2, also known as monocyte chemoattractant protein-1 (MCP-1), attracts monocytes to migrate to areas of injury and mature into macrophages, leading to positive feedback inflammation with further release of proinflammatory molecules such as IL-1 beta and TNF-alpha. Sequestering CCL2 to prevent its binding to CCR2 may prevent this inflammatory activity. Prior work adapted an alpha-helical CCL2-binding peptide (WKNFQTI) from murine CCR2 through extracellular loop analysis. Here, higher-affinity peptide binders are computationally designed through homology modeling and energy calculations, yielding an 11-amino acid peptide with high binding affinity. In addition, Rosetta mutations improves binding affinity in silico with blockage of the CCL2 dimerization site. Future work in analyzing binding kinetics and in vivo inflammation abrogation will confirm the accuracy of computational modeling techniques in de novo rational design of CCL2 cytokine binders.

Automated summary

Chronic inflammation can lead to autoimmune diseases like rheumatoid arthritis and atherosclerosis. CCL2, also known as MCP-1, plays a crucial role in the progression of these diseases by attracting monocytes to the site of injury and promoting inflammation. In this study, computational modeling techniques were used to design high-affinity peptide binders for CCL2, with the aim of preventing its binding to CCR2 and reducing inflammation. Further analysis and experiments are needed to validate the accuracy of this computational approach in designing CCL2 cytokine binders.