In macromolecular crystallography, the rigorous detection of changed states (for example, ligand binding) is difficult unless signal is strong. Ambiguous (‘weak’ or ‘noisy’) density is experimentally common, since molecular states are generally only fractionally present in the crystal. Existing methodologies focus on generating maximally accurate maps whereby minor states become discernible; in practice, such map interpretation is disappointingly subjective, time-consuming and methodologically unsound. Here we report the PanDDA method, which automatically reveals clear electron density for the changed state—even from inaccurate maps—by subtracting a proportion of the confounding ‘ground state’; changed states are objectively identified from statistical analysis of density distributions. The method is completely general, implying new best practice for all changed-state studies, including the routine collection of multiple ground-state crystals. More generally, these results demonstrate: the incompleteness of atomic models; that single data sets contain insufficient information to model them fully; and that accuracy requires further map-deconvolution approaches.

Research into the chemical biology of bromodomains has been driven by the development of acetyl-lysine mimetics. The ligands are typically anchored by binding to a highly conserved asparagine residue. Atypical bromodomains, for which the asparagine is mutated, have thus far proven elusive targets, including PHIP(2) whose parent protein, PHIP, has been linked to disease progression in diabetes and cancers. The PHIP(2) binding site contains a threonine in place of asparagine, and solution screening have yielded no convincing hits. We have overcome this hurdle by combining the sensitivity of X-ray crystallography, used as the primary fragment screen, with a strategy for rapid follow-up synthesis using a chemically-poised fragment library, which allows hits to be readily modified by parallel chemistry both peripherally and in the core. Our approach yielded the first reported hit compounds of PHIP(2) with measurable IC₅₀ values by an AlphaScreen competition assay. The follow-up libraries of four poised fragment hits improved potency into the sub-mM range while showing good ligand efficiency and detailed structural data.

The steady expansion in the capacity of modern beamlines for high-throughput data collection, enabled by increasing X-ray brightness, capacity of robotics and detector speeds, has pushed the bottleneck upstream towards sample preparation. Even in ligand-binding studies using crystal soaking, the experiment best able to exploit beamline capacity, a primary limitation is the need for gentle and nontrivial soaking regimens such as stepwise concentration increases, even for robust and well characterized crystals. Here, the use of acoustic droplet ejection for the soaking of protein crystals with small molecules is described, and it is shown that it is both gentle on crystals and allows very high throughput, with 1000 unique soaks easily performed in under 10 min. In addition to having very low compound consumption (tens of nanolitres per sample), the positional precision of acoustic droplet ejection enables the targeted placement of the compound/solvent away from crystals and towards drop edges, allowing gradual diffusion of solvent across the drop. This ensures both an improvement in the reproducibility of X-ray diffraction and increased solvent tolerance of the crystals, thus enabling higher effective compound-soaking concentrations. The technique is detailed here with examples from the protein target JMJD2D, a histone lysine demethylase with roles in cancer and the focus of active structure-based drug-design efforts.

XChemExplorer(XCE) is a data-management and workflow tool to support large-scale simultaneous analysis of protein–ligand complexes during structure-based ligand discovery (SBLD). The user interfaces of established crystallographic software packages such asCCP4 [Winnet al.(2011),Acta Cryst.D67, 235–242] orPHENIX[Adamset al.(2010),Acta Cryst.D66, 213–221] have entrenched the paradigm that a `project' is concerned with solving one structure. This does not hold for SBLD, where many almost identical structures need to be solved and analysed quickly in one batch of work. Functionality to track progress and annotate structures is essential.XCEprovides an intuitive graphical user interface which guides the user from data processing, initial map calculation, ligand identification and refinement up until data dissemination. It provides multiple entry points depending on the need of each project, enables batch processing of multiple data sets and records metadata, progress and annotations in an SQLite database.XCEis freely available and works on any Linux and Mac OS X system, and the only dependency is to have the latest version ofCCP4 installed. The design and usage of this tool are described here, and its usefulness is demonstrated in the context of fragment-screening campaigns at the Diamond Light Source. It is routinely used to analyse projects comprising 1000 data sets or more, and therefore scales well to even very large ligand-design projects.

Galectin-3 (Gal-3), a lectin with preference for β-galactoside-containing carbohydrates, is a structurally unique member of the galectin family. It is ubiquitously expressed in various mammalian tissues with a wide distribution from the intracellular environment to the extracellular space. Gal-3 is a well-established player in numerous diseases, from infections to heart failure. Notably, as Gal-3 overexpression is associated with cancer drug resistance, it has been identified as a valuable therapeutic target in the fight against cancers. This review discusses the recent progress of patent applications (2008-present) and the current knowledge of pertinent Gal-3-inhibitor interactions in an effort to progress the development of selective and high affinity carbohydrate-based inhibitors targeting Gal-3, with an emphasis on engaging a structure-based drug design rationale. The lack of commercially available anti-Gal-3 therapeutic reagents and its clear involvement in serious disease, notably cancer, leads to an urgent need for development of inhibitors that specifically target Gal-3. Design of potent and selective carbohydrate inhibitors targeting Gal-3 is challenging due to relative weak protein-carbohydrate interactions along with the high sequence homology in the carbohydrate binding site region among galectins. To date, some chemical scaffolds have been exploited for design of promising effective Gal-3 inhibitors for cancer therapy.