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Abstract Heart failure (HF) has become an important social problem that seriously threatens human health due to its high morbidity and mortality. G Protein-Coupled Receptors Kinase 2 (GRK2), as a novel target of heart failure, is overexpressed in the pathogenesis and progression of HF. In this study, we conducted a multistep virtual screening process from the ZINC database to discover potential GRK2 inhibitors. First, by using 6 known GRK2 inhibitors with high bioactivity and diverse structures as the template molecules, 7499 compounds were obtained from ligand-based similarity screening by 4 types of fingerprints. Subsequently, these hits were further screened by three quantitative structure-activity relationship (QSAR) models, which were built by 197 known GRK2 compounds and represented by two-dimensional MOE descriptors (MOE2D), molecular fragments (MACCS) and 2- dimensional pharmacophore (CATS) based on random forest algorithm, respectively. These hit compounds were then filtered by three molecular docking packages (MOE, GOLD and GLIDE) to improve the docking accuracy for avoid losing candidate compounds. The compounds with high docking scores were selected for the evaluation of absorption, distribution, metabolism, excretion, and toxicity (ADMET). Finally, 17 compounds were identified the binding affinity to GRK2 by using SPR assay, three of which were considered as novel GRK2 inhibitors, and their binding modes with GRK2 active sites were analyzed. As new potential GRK2 inhibitors, COM5(K D = 0.172 μM) and COM17(K D = 0.595 μM) with the KD value less than 1 μM could be directly used in the next study, while the remaining hit COM4 (K D = 4.72 μM) whose K D over 1 μM can be optimized into the required low nanomole range for further study. Highlights • GRK2 is considered as an important potential pharmaceutical target for the treatment of heart failure. • To discover novel GRK2 inhibitors, a multi-step computational study was conducted, including similarity screening based on fingerprints, QSAR models screening based on random forest algorithm, docking studies, ADMET filtering, and the final activity validation. • Three hit compounds with novelty structures were identified as the potential GRK2 inhibitors, its binding affinity were COM5(KD=0.172µM), COM17(KD=0.595µM), and COM4 (KD =4.72µM). [ABSTRACT FROM AUTHOR]