Elucidating details of the relationship between molecular structure and a particular biological end point is essential for successful, rational drug discovery. Molecular docking is a widely accepted tool for lead identification however, navigating the intricacies of the software can be daunting. Our objective was therefore to provide a step-by-step guide for those interested in incorporating contemporary basic molecular docking and homology modelling into their design strategy. Three molecular docking programs, AutoDock4, SwissDock and Surflex-Dock, were compared in the context of a case study where a set of steroidal and non-steroidal ligands were docked into the human androgen receptor (hAR) using both rigid and flexible target atoms. Metrics for comparison included how well each program predicted the X-ray structure orientation via root mean square deviation (rmsd), predicting known actives via ligand ranking and comparison to biological data where available. Benchmarking metrics were discussed in terms of identifying accurate and reliable results. For cases where no three dimensional structure exists, we provided a practical example for creating a homology model using Swiss-Model. Results showed an rmsd between X-ray ligands from wild-type and mutant receptors and docked poses were 4.15Å and 0.83Å (SwissDock), 2.69Å and 8.80Å (AutoDock4) and 0.39Å and 0.71Å (Surflex-Dock) respectively. Surflex-Dock performed consistently well in pose prediction (less than 2Å) while Auto- Dock4 predicted known active non-steroidal antiandrogens most accurately. Introducing flexibility into target atoms produced the largest degree of change in ligand ranking in Surflex-Dock. We produced a viable homology model of the P2X1 purireceptor for subsequent docking analysis.

A fluorescent boronate receptor with a unique response to free sialic acid has been developed; this divergent response system may find use in design of other fluorophores to discriminate between structurally similar analytes.

Boric acid catalyzes the monoesterification of malonic acid, likely through a chelation mechanism that is not available to the monoester product. Under more forcing conditions, diesters form to some extent, but conditions can be optimized to favour the monoester product (56–80%). With the easily handled solid acid catalyst, these reactions can be run with excess alcohol as solvent or with stoichiometric amounts of alcohol in acetonitrile with moderate heating.

Poly(ADP-ribose)polymerase, member 14 (PARP14, alternatively named ARTD8, BAL2, and COAST6) is an intracellular mono(ADP-ribosyl) transferase. PARP14 transfers a negatively charged ADP-ribose unit from a donor NAD + molecule onto a target protein, post-translationally. PARP14's domain architecture consists of three macrodomains (Macro1, Macro2 and Macro3), a WWE domain and an ARTD (or catalytic domain). The Macro2 and Macro3 domains bind ADP-ribose (ADPr) with high affinity, whereas the WWE domain stabilizes the protein structure by binding to ADPr derivatives. The catalytic domain is involved in binding the NAD + and catalyzing the mono-ADP-ribosylation reaction. PARP14 has been identified as a possible anti-cancer and anti-inflammatory target. Acting as a transcriptional coactivator for STAT6, PARP14 acts to promote the over activation of the Th2 immune response, thus promoting the metabolic change to an anaerobic state (Warburg effect) and activation of cell survival pathways through JNK2 and the PGI/AMF complex. These changes are consistent with the metabolic sophistication observed in cancer, and the immune imbalance in inflammatory diseases. Current literature on selective and unselective PARP14 inhibitors are reviewed and discussed. Although there is no evidence that selective PARP inhibitors would be advantageous we have proposed some strategies for future design of selective PARP14 inhibitors.

Organic reaction mechanisms are one of the most challenging question types in introductory organic chemistry subjects. We identified that the students within our health-based programs had traditionally performed poorly with these question types. With the aim to increase student engagement, we have developed a series of lightboard videos demonstrating key organic mechanisms. The effectiveness of these lightboard videos was first evaluated in a postlecture group learning session, and second as an extra resource over a four year period by comparing the exam results. The students overall showed an increase in performance in the subject, and a deeper engagement over the time during which we analyzed the effectiveness of these resources.