Stages in a typical drug discovery organization include target selection, hit identification, lead optimization, preclinical and clinical studies. Hit identification and lead optimization are very much intertwined with computational modeling. Structure-based virtual screening (VS) has been a staple for more than a decade now in drug discovery with its underlying computational technique, docking, extensively studied. Depending on the objective, the parameters for VS may change, but the overall protocol is very straightforward. The idea behind VS is that a library of small compounds are docked into the binding pocket of a protein (e.g., receptor, enzyme), a number of solutions per molecule, among the top-ranked, are being returned, and a choice is made on the fraction of compounds to be moved forward for testing toward hit identification. The underlying principle of VS is that it differentiates between active and inactive compounds, thus reducing the number of molecules moving forward and possibly offering a complementary tool to high-throughput screening (HTS). Best practices in library selection, target preparation and refinement, criteria in selecting the most appropriate docking/scoring scheme, and a step-wise approach in performing Glide VS are discussed.