Computational methods are playing an increasingly significant role in pharmaceutical and medical applications, particularly in drug discovery. If a good structural model of a receptor is available, in silico methods can easily test libraries containing millions of candidate compounds and reduce the cost of synthesis and experimental testing. Herein, we review the available methods to derive structural models from related targets, homology modeling, and the various state-of-the-art protocols for structure-based in silico drug design. We specifically emphasize the applicability of these methods for investigating privileged scaffolds as molecular frameworks that facilitate structural modification for multiple receptor targets. In this chapter, we highlight the progress in, and the remaining challenges of, computational methods that are commonly applied to drug design. In particular, we discuss protein structure prediction tools as a method to address the difficulty with insufficient structural information about receptor targets. Molecular docking techniques are compared with respect to their ability to determine the optimal docking conformations for further lead optimization. We illustrate the use of these methods for selected privileged scaffolds, some of which are addressed in other chapters of this volume.