Characterizing the MSMP–CCR2 Interaction through Molecular Dynamics Simulations and Machine Learning Approaches

The MSMP (MicroSeminoProtein, Prostate-associated) protein is overexpressed in several cancers, including prostate, ovarian, and breast cancers. Its overexpression is particularly prevalent in tumors resistant to hormonal therapy, as well as to antiangiogenic treatments (e.g., anti-VEGF therapies). In hypoxic tumor microenvironments, characteristic of solid tumors, MSMP expression increases and facilitates tumor growth. MSMP binds to the transmembrane receptor CCR2 (C-C chemokine receptor type 2), a GPCR present on monocytes and lymphocytes. This interaction stabilizes an active conformation of CCR2, enabling downstream MAP kinase signaling pathways to reactivate androgen synthesis and promote tumor progression. In this study, we employed molecular modeling, molecular dynamics simulations, and machine learning techniques to elucidate the structural basis of the MSMP-CCR2 interaction. High-resolution models of the MSMP-CCR2-G protein complex were generated using AlphaFold2 and refined with MD simulations. Comparative analyses with the CCL2-CCR2-G protein complex and the unbound CCR2-G protein complex revealed key conformational rearrangements that modulate and stabilize the active state of the receptor. Binding free energy calculations revealed similar energetic profiles for MSMP and CCL2, despite distinct binding modes. Residue-level energy decomposition identified critical residues at the MSMP-CCR2 interface, offering insights into the receptor's activation mechanism. Additionally, machine learning models classified molecular dynamics trajectories, highlighting key structural features associated with stable MSMP-CCR2-G protein states. This integrative approach identified residues essential for maintaining a stable conformation of the MSMP-CCR2-G protein complex, providing a basis for targeting MSMP-CCR2 interactions in therapeutic development.