Rational Design of De Novo CCL2 Binding Peptides

Erika Davidoff Aguas, Abdul Rahman Azizogli, Jatin Kashyap, Joseph Dodd-o, Zain Siddiqui, Jay Sy, Vivek Kumar

Research output: Contribution to journalArticlepeer-review

Abstract

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-1β and TNF-α. Sequestering CCL2 to prevent its binding to CCR2 may prevent this inflammatory activity. Prior work adapted an α-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.

Original languageEnglish (US)
JournalAdvanced Theory and Simulations
DOIs
StateAccepted/In press - 2022

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Numerical Analysis
  • Modeling and Simulation
  • General

Keywords

  • CCR2
  • computational peptide design
  • inflammation
  • MCP-1
  • molecular docking

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