During the past years, efforts in the pharmaceutical industry have focused on optimizing the early phase hit-to-lead development of the drug discovery process. In silico-based high-throughput screening (HTS) approaches emerged, with a number of issues arising, such as the need for efficient search algorithms, library design, diversity, drug- and/or lead-likeness. These problems were addressed in numerous publications. This review focuses on the generation and use of virtual compound libraries, and on studies in which chemical feature-based pharmacophore models are used in combination with in silico screening. These procedures are generally used to obtain hits (or leads) that are more likely to give successful clinical candidates.