Chemistry in high school is often presented as a jumbled mass of topics drawn from inorganic, analytical, and physical sub-disciplines. With no central theme to build on, students may have trouble grasping the chemical sciences as a coherent field. We believe that a relevant, compelling, accessible framework might better engage students in chemistry. In this article, we describe an activity aligned with the Next Generation Science Standards (NGSS Lead States 2013; see box, p. 46) that integrates different facets of chemistry and biology into a scaffold structured around small-molecule medicinal drug discovery. This investigation was inspired by laboratory work the authors--a researcher (RS) and a high school teacher (JE)--undertook to pursue a new class of historie deacetylase (HDAC) inhibitors (Wang et al. 2015). Small-molecule therapies, forged by evolution or human effort--from antibiotics to chemotherapeutics to anti-retrovirals--can combat many of the maladies that plague humanity. Despite past successes, current therapies are not guaranteed to work forever, and further development of molecular medicines is always required. The constant arms race against antibiotic-resistant bacteria serves as one example of the perpetual need for new therapies. To discover new medicinal molecules, intrepid chemists often must obtain and modify a lead compound of interest. Leads may arise either from nature or through the screening of large compound libraries against protein targets relevant to a particular disease. Once a lead is found, medicinal chemists must modify it through the iterative creation of structurally related analogs in order to arrive at a potent, selective, and relatively non-toxic clinical candidate. Modern biomedical researchers can model the interactions between small molecules and their macromolecular target on a computer and thereby plan structural modifications that seem most likely to increase compound tightness of binding. Through the use of these in silico (computer-based) models, scientists can bias those molecules they make in the lab on the basis of binding affinity predictions resultant from virtual screens containing millions of small molecules. The rapid increase in both personal computing power and efficient algorithms for small molecule binding-mode prediction has enabled researchers to access computer-aided molecular docking tools using commercially available laptops--a feat that would have been unthinkable a few years ago. Throughout this exercise, students assume the role of medicinal chemists searching for a new anticancer medicine by pursuing (structurally similar) analogs to a chemotherapeutic lead compound of interest. [ILLUSTRATION OMITTED] Software tools Free software tools (Figure 1) can help students explore small molecule-protein interactions. For example, students can use AutoDockTools (Huey et al. 2007; Morris et al. 2009; Morris et al. 1998) to prepare the crystallographic macromolecule representation obtained from the Protein Data Bank (PDB) for screening; the PDB offers free downloadable macromolecular structures (including many disease targets). AutoDock Vina (Trott and Olson 2010) can perform the molecular dynamics calculations necessary to generate binding mode predictions, and PyRx (Wolf 2009) can provide the graphical user interface (GUI) for all screening protocols. Inhibitors may be visualized using Schrodinger LLC's Pymol software (Pymol 2015). Ligand preparation requires Marvin-sketch and Marvinview (Marvin 2016). To implement this challenging activity, teachers may need a refresher in organic chemistry, biochemistry, and/or molecular biology. Students need a background in chemistry and biology. Our class--an advanced placement (AP) chemistry course--was our students' second chemistry class, and most students had already taken AP biology (or an equivalent course). For help understanding computer-aided drug design, see the References section and the On the web section for links to helpful videos and supplemental information. …