In the present research, a few well-known artificial intelligence tools were explored for efficient hit selection which could be further utilized for the discovery of CaMK-II inhibitors for the Treatment of arrhythmia. To achieve the desired goals pharmacophore modelling, database retrieval, molecular docking studies, and toxicity prediction were performed. Pharmacophore modelling was performed with the Pharmit open-source database which gave the features viz. Hydrogen Bond Donor, Hydrogen Bond Acceptor, and Hydrophobic. This pharmacophore is generated with the aid of the protein of CaMK-II (PDB ID: 2WEL) and co-crystallized ligand K88. Further, this generated pharmacophore was screened through the various Pharmit databases which include CHEMBL30, ChemDiv, ChemSpace, MCULE, MolPort, NCI Open Chemical Repository, Lab Network, and ZINC. Further, the top two hits from each database that has maximum similarity with the pharmacophore have been selected for the molecular docking and ADMET studies. Among, all the hits CHEMBL 1952032 showed good binding interactions with CaMK-II. Also, it was found to be non-toxic upon evaluation through the OSIRIS property explorer. In the future, it can be explored against the CaMK-II for the development of novel CaMK-II inhibitors which can be used for the mitigation of arrhythmia.