Identification of the selective chemical features for Aurora-B inhibitors gained much attraction in drug discovery for the treatment of cancer. Hence to identify the Aurora-B critical features various techniques were utilized such as pharmacophore generation, virtual screening, homology modeling, molecular dynamics, and docking. Top ten hypotheses were generated for Aurora-B and Aurora-A. Among ten hypotheses, HypoB1 and HypoA1 were selected as a best hypothesis for Aurora-B and Aurora-A based on cluster analysis and ranking score, respectively. Test set result revealed that ring aromatic (RA) group in HypoB1 plays an essential role in differentiates Aurora-B from Aurora-A inhibitors. Hence, HypoB1 used as 3D query in virtual screening of databases and the hits were sorted out by applying drug-like properties and molecular docking. The molecular docking result revealed that 15 hits have shown strong hydrogen bond interactions with Ala157, Glu155, and Lys106. Hence, we proposed that HypoB1 might be a reasonable hypothesis to retrieve the structurally diverse and selective leads from various databases to inhibit Aurora-B.