"In Silico Assessment Of Ccr2 Gene Missense Variants: Implications For Antagonist Binding Affinity"
DOI:
https://doi.org/10.64252/4ec8dz15Keywords:
CCR2, Missense Variants, Molecular Docking, ADMET Profiling, AutoDock Vina, Chronic Kidney Disease (CKD), Precision Medicine, PharmacogenomicsAbstract
Background: The C-C chemokine receptor type 2 (CCR2) plays a pivotal role in modulating immune responses, particularly by guiding monocyte and macrophage chemotaxis in chronic kidney disease (CKD). Missense variants in the CCR2 gene may alter its protein structure and antagonist binding affinity, thereby impacting therapeutic efficacy. This study investigates the effects of six deleterious CCR2 missense variants (rs113340633, rs200491743, rs370278890, rs371121141, rs373211972, rs374045702) on the binding of three CCR2 antagonists—RS102895, RS-504393, and CCX140-B—using comprehensive in silico approaches.
Methods: Pharmacokinetic and toxicity profiles of the antagonists were evaluated using the pkCSM web server to predict ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. Homology models of the wild-type and variant CCR2 proteins (L119P, F125L, G127V, A141V, T153M, M249K) were generated using Phyre2. Molecular docking was performed using AutoDock Vina, and protein-ligand interactions were visualized with Discovery Studio.
Results: ADMET profiling revealed high intestinal absorption for RS102895 (87.7%) and RS-504393 (89.1%), with CCX140-B showing lower absorption (72.9%). All compounds exhibited predicted hepatotoxicity. Docking analysis showed RS-504393 had the highest binding affinity to wild-type CCR2 (-10.3 kcal/mol) and retained strong binding across all variants. The F125L variant improved RS102895 binding (-9.9 vs. -9.5 kcal/mol WT), whereas L119P and A141V reduced CCX140-B binding affinity (-8.6 vs. -9.6 kcal/mol WT).
Conclusion: RS-504393 demonstrates consistent binding across CCR2 variants, indicating broad therapeutic applicability. The F125L variant may enhance RS102895 efficacy, suggesting a potential for genotype-guided treatment strategies in CKD. These findings underscore the clinical importance of integrating genetic information into drug design and warrant further experimental validation.
