Novel ligands for the chemokine receptor-3 (CCR3): a receptor-modeling study based on 5D-QSAR

We recently reported the development of a receptor-modeling concept based on 5D-QSAR (quantitative structure-activity relationships) and which explicitly allows for the simulation of induced fit. In this account, we report its utilization toward the design of novel compounds able to inhibit the chemokine receptor-3 (CCR3). The study was based on a total of 141 compounds, representing four different substance classes. Using the Quasar software, we built two receptor surrogates that yielded a cross-validated r(2) value of 0.950/0.861 and a predictive r(2) of 0.879/0.798, respectively. The model was then employed to predict the activity of 58 hypothetical compounds featuring two variation patterns: lipophilic substitutions and amphiphilic H-bond acceptors. Eleven of the proposed ligands show a calculated binding affinity lower than any compound within the training set; the most potent candidate molecule is expected to bind at an IC(50) of 0.3 nM.