Characterizing CCR2 homodimers using homology-derived and AI-predicted interfaces
Lauri Urvas1, Amaia Nuñez-delMoral2, Célien Jacquemard1
1Laboratoire d'Innovation Thérapeutique, UMR 7200 CNRS, Université de Strasbourg, 67400 Illkirch-Graffenstaden, France.
Abstract:
Deciphering the functional roles of G protein-coupled receptors (GPCRs) oligomers requires defining their structural organization, which remains a challenge due to the inherent flexibility of their 7 transmembrane (TM) domains. Here, we focused on determining homodimer interfaces of the chemokine receptor CCR2, a major component of the inflammatory response, for which no antagonist has yet been approved. We generated models of CCR2 homodimers combining homology modeling, a conventional in silico approach, or an AI-based AlphaFold-Multimer predictions, with molecular dynamics simulations. We determined the biological relevance of our predicted models by in cellulo cross-linking experiments, introducing a cysteine in each predicted interface. This in cellulo assay supported the homology modeling predictions, but not those predicted by AlphaFold-Multimer, and demonstrated that CCR2 forms homodimers by at least two different interfaces involving the transmembrane domains TM5 (I5) or TM5 and TM6 (I56). This structural arrangement of the CCR2 homodimer represents a valuable model for further studies on the functional consequences of dimerization and for the rational design of CCR2-selective drugs.
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