In silico molecular docking is used to predict how a small molecule, the ligand, interacts with a target protein, its receptor. Together with experimental methods like NMR or X-ray crystallography, industrial and academic groups use it for their investigation of compounds with the potential to modulate the protein's function and become a lead molecule for drug development. The interpretation of raw data, from NMR, mass spectrometry or crystallography, is greatly assisted by computers. Biochemists can, perhaps better than anybody else, perform individual analyses for the computational modeling of interactions. However, an extension towards virtual screening of compound libraries, i.e. the computational docking of thousands or even millions of ligands to a target receptor, is often perceived as technically challenging and computationally too expensive in the biochemical community. Here we describe how to integrate spare resources of regular desktop computers on and off campus using the Berkeley Open Infrastructure for Network Computing (BOINC) infrastructure for volunteer grid computing. We have brought both the BOINC server and the Auto Dock software suite into the Debian and Ubuntu Linux distributions, and provide detailed instructions to help render the implementation of a large-scale high-throughput docking (HTD) project straightforward. Thus, this increased availability of computational resources, protocols and source code opens up the possibility of many new self-run projects and collaborations, for those who may be adopting the technology for the first time. On the technical level, we expect to observe more contributors from the Open Source and academic communities. On the biological side, we anticipate new and faster progress on commercially less interesting and so-called 'neglected' diseases.