Computational modeling approaches have lately been earning their place as viable tools in drug discovery. Research efforts more often include computational component and the usage of the scientific software is commonplace at more stages of the drug discovery pipeline. However, as software takes on more responsibility and the computational methods grow more involved, the gap grows between research entities that have the means to maintain the necessary computational infrastructure and those that lack the technical expertise or financial means to obtain and include computational component in their scientific efforts. To fill this gap and to meet the need of many, mainly academic, labs numerous community contributions collectively known as open source projects play an increasingly important role. This work describes design, implementation and application of a set of drug discovery workflows based on the CHARMMing (CHARMM interface and graphics) web-server. The protocols described herein include docking, virtual target screening, de novo drug design, SAR/QSAR modeling as well as chemical education. The performance of the newly developed workflows is evaluated by applying them to a number of scientific problems that include reproducibility of crystal poses of small molecules in protein-ligand systems, identification of potential targets of a library of natural compounds as well as elucidating molecular targets of a vitamin. The results of these inquiries show that protocols developed as part of this effort perform comparably to commercial products, are able to produce results consistent with the experimental data and can substantially enrich the research efforts of labs with otherwise little or no computational component.