Interactions between proteins and their ligands, such as small molecules, other proteins, and DNA, depend on specific interatomic interactions that can be classified on the basis of atom type and distance and angle constraints. Visualisation of these interactions provides insights into the nature of molecular recognition events and has practical uses in guiding drug design and understanding the structural and functional impacts of mutations. We present Arpeggio, a web server for calculating interactions within and between proteins and protein, DNA, or small-molecule ligands, including van der Waals', ionic, carbonyl, metal, hydrophobic, and halogen bond contacts, and hydrogen bonds and specific atom–aromatic ring (cation–π, donor–π, halogen–π, and carbon–π) and aromatic ring–aromatic ring (π–π) interactions, within user-submitted macromolecule structures. PyMOL session files can be downloaded, allowing high-quality publication images of the interactions to be generated. Arpeggio is implemented in Python and available as a user-friendly web interface at http://structure.bioc.cam.ac.uk/arpeggio/ and as a downloadable package at https://bitbucket.org/harryjubb/arpeggio.

Small aromatic ring systems are of central importance in the development of novel synthetic protein ligands. Here we generate a complete list of 24,847 such ring systems. We call this list and associated annotations VEHICLe, which stands for virtual exploratory heterocyclic library. Searches of literature and compound databases, using this list as substructure queries, identified only 1701 as synthesized. Using a carefully validated machine learning approach, we were able to estimate that the number of unpublished, but synthetically tractable, VEHICLe rings could be over 3000. However, analysis also shows that the rate of publication of novel examples to be as low as 5-10 per year. With this work, we aim to provide fresh stimulus to creative organic chemists by highlighting a small set of apparently simple ring systems that are predicted to be tractable but are, to the best of our knowledge, unconquered.

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Growing evidence of the possibility of modulating protein-protein interactions with small molecules is opening the door to new approaches and concepts in drug discovery. In this paper, we describe the creation of TIMBAL, a hand-curated database holding an up to date collection of small molecules inhibiting multi-protein complexes. This database has been analysed and profiled in terms of molecular properties. Protein-protein modulators tend to be large lipophilic molecules with few hydrogen bond features. An analysis of TIMBAL's intersection with other structural databases, including CREDO (protein-small molecule from the PDB) and PICCOLO (protein-protein from the PDB) reveals that TIMBAL molecules tend to form mainly hydrophobic interactions with only a few hydrogen bonding contacts. With respect to potency, TIMBAL molecules are slightly less efficient than an average medicinal chemistry hit or lead. The database provides a resource that will allow further insights into the types of molecules favoured by protein interfaces and provide a background to continuing work in this area. Access at http://www-cryst.bioc.cam.ac.uk/timbal.