Abstract Systematic investigation of older approved drugs for newer therapeutic indications helps in reducing the time and money required to bring a medicine to the market, by circumventing absorption, distribution, metabolism, elimination, and toxicity (ADMET) and toxicological investigations in both preclinical and clinical trials. In this connection, application of computer-aided drug design (CADD) techniques could be more relevant to identify drugs that could interact with new drug targets in silico. These in silico predictions could be backed by experimental proof for the activity from in vitro and in vivo assays, followed by clinical investigations. This could eventually bring the drug to the market for a new indication identified for the old drug. In this chapter, we discuss the common CADD techniques used for drug design and discovery, with particular emphasis on the open source in silico tools, databases, and servers available for this purpose. Information regarding open access databases for drugs, protein sequences, 3D protein structures; tools/software tools and servers for homology modeling, docking and pharmacophore modeling are listed and discussed. Moreover, to demonstrate the use of these tools/software, the 3D structure of Aurora Kinase C was modeled and used to identify drugs that could interact with this target using docking-based virtual screening. The open source information provided in the chapter could be useful for drug discovery scientists to speed up not only drug repurposing/repositioning but also new drug discovery.