An mRNA Display Approach for Covalent Targeting of a Virulence Factor.

Staphylococcus aureus () is an opportunistic human pathogen that causes over one million deaths around the world each year. We recently identified a family of serine hydrolases termed fluorophosphonate binding hydrolases (Fphs) that play important roles in lipid metabolism and colonization of a host. Because many of these enzymes are only expressed in bacteria, they are valuable targets for diagnostics and therapeutics.

Structural insights into IMP2 dimerization and RNA binding.

IGF2BP2 (IMP2) is an RNA-binding protein that contributes to cancer tumorigenesis and metabolic disorders. Structural studies focused on individual IMP2 domains have provided important mechanistic insights into IMP2 function; however, structural information on full-length IMP2 is lacking but necessary to understand how to target IMP2 activity in drug discovery. In this study, we investigated the behavior of full-length IMP2 and the influence of RNA binding using biophysical and structural methods including mass photometry, hydrogen-deuterium exchange coupled to mass spectrometry (HDX-MS), and small angle x-ray scattering (SAXS).

The conformational landscape of human transthyretin revealed by cryo-EM.

Transthyretin (TTR) is a natively tetrameric thyroxine transporter found in blood and cerebrospinal fluid whose misfolding and aggregation causes transthyretin amyloidosis. A rational drug design campaign identified the small molecule tafamidis (Vyndaqel/Vyndamax) as an effective stabilizer of the native TTR fold, and this aggregation inhibitor is regulatory agency-approved for the treatment of TTR amyloidosis. Despite 50 years of structural studies on TTR and this triumph of structure-based drug design, there remains a notable dearth of structural information available to understand ligand binding allostery and amyloidogenic TTR unfolding intermediates.

Reactive Docking: A Computational Method for High-Throughput Virtual Screenings of Reactive Species.

We describe the formalization of the reactive docking protocol, a method developed to model and predict reactions between small molecules and biological macromolecules. The method has been successfully used in a number of applications already, including recapitulating large proteomics data sets, performing structure-reactivity target optimizations, and prospective virtual screenings. By modeling a near-attack conformation-like state, no QM calculations are required to model the ligand and receptor geometries.

Ringtail: A Python Tool for Efficient Management and Storage of Virtual Screening Results.

Virtual screening using molecular docking is now routinely used for the rapid evaluation of very large ligand libraries in early stage drug discovery. As the size of compound libraries which can feasibly be screened grows, so do the challenges in result management and storage. Here we introduce Ringtail, a new Python tool in the AutoDock Suite for efficient storage and analysis of virtual screening data based on portable SQLite databases.