Identification of new potent A1 adenosine receptor antagonists using a multistage virtual screening approach

Abstract

The use of antagonists for each adenosine receptor (AR) subtype as potent clinical candidates is of growing interest due to their involvement in the treatment of various diseases. The recent resolution of several A1 and A2A ARs X-ray structures provides opportunities for structure-based drug design. In this study, we describe the discovery of novel A1AR antagonists by applying a multistage virtual screening approach, which is based on random forest (RF), e-pharmacophore modeling and docking methods. A multistage virtual screening approach was applied to screen the ChemDiv library (1,492,362 compounds). Among the final hits, 22 compounds were selected for further radioligand binding assay analysis against human A1AR, and 18 compounds (81.82% success) exhibited nanomolar or low micromolar binding potency (Ki). Then, we selected six compounds (pKi > 6) to further evaluate their antagonist profile in a cAMP functional assay, and we found that they had low micromolar antagonistic activity (pIC50 = 5.51–6.38) for the A1AR. Particularly, four of six compounds (pKi > 6) showed very good affinity (pKi = 6.11–7.13) and selectively (>100-fold) for A1AR over A2AAR. Moreover, the novelty analysis suggested that four of six compounds (pKi > 6) were dissimilar to existing A1AR antagonists and hence represented novel A1AR antagonists. Further molecular docking and molecular dynamics (MD) studies showed that the three selective compounds 15, 20 and 22 were stabilized (RMSlig value ≤ 2 Å) inside the binding pocket of A1AR with similar orientations to the docking pose in 100-ns MD simulations, whereas they escaped from the binding area of A2AAR with larger values of RMSlig (RMSlig ≥ 2 Å). We hope that these findings provide new insights into the discovery of drugs targeting A1AR and facilitate research on new drugs and treatments for A1AR-related human pathologies.