Every day, hundreds of millions of people worldwide take nonsteroidal antiinflammatory drugs (NSAIDs), often in conjunction with multiple other medications. In the bloodstream, NSAIDs are mostly bound to serum albumin (SA). We report the crystal structures of equine serum albumin complexed with four NSAIDs (ibuprofen, ketoprofen, etodolac, and nabumetone) and the active metabolite of nabumetone (6-methoxy-2naphthylacetic acid, 6-MNA). These compounds bind to seven drug-binding sites on SA. These sites are generally well-conserved between equine and human SAs, but ibuprofen binds to both SAs in two drug-binding sites, only one of which is common. We also compare the binding of ketoprofen by equine SA to binding of it by bovine and leporine SAs. Our comparative analysis of known SA complexes with FDA-approved drugs clearly shows that multiple medications compete for the same binding sites, indicating possibilities for undesirable physiological effects caused by drug−drug displacement or competition with common metabolites. We discuss the consequences of NSAID binding to SA in a broader scientific and medical context, particularly regarding achieving desired therapeutic effects based on an individual's drug regimen.

The first albumin structure in complex with testosterone and the hormone's binding affinity measured with two methods.

In the Special Issue on Tools for Protein Science in 2018, we presented Molstack: a concept of a cloud-based platform for sharing electron density maps and their interpretations. Molstack is a web platform that allows the interactive visualization of density maps through the simultaneous presentation of multiple datasets and models in a way that allows for easy pairwise comparison. We anticipated that the users of this conceptually simple platform would find many different uses for their projects, and we were not mistaken. We have observed researchers use Molstack to present experimental evidence for their models in the form of electron density maps, omit maps, and anomalous difference density maps. Users also employed Molstack to present alternative interpretations of densities, including rerefinements and speculative interpretations. While we anticipated these types of projects to be the main use cases, we were pleased to see Molstack used to display superpositions of different models, as a tool for story-driven presentations, and for collaboration as well. Here, we present developments in the platform that were driven by user feedback, highlight several cases that used Molstack to enhance the publication, and discuss possible directions for the platform.