How can categorical models provide value in supporting compound prioritisation?
Introduction In early-stage drug discovery, medicinal chemists rely on predictive models to help guide which compounds to synthesise or test…
We report a new method for X-ray density ligand fitting and refinement that is suitable for a wide variety of small-molecule ligands, including macrocycles. The approach (called “xGen”) augments a force field energy calculation with an electron density fitting restraint that yields an energy reward during the restrained conformational search. The resulting conformer pools balance goodness-of-fit with ligand strain. Real-space refinement from pre-existing ligand coordinates of 150 macrocycles resulted in occupancy-weighted conformational ensembles that exhibited low strain energy. The xGen ensembles improved upon electron density fit compared with the PDB reference coordinates without making use of atom-specific B-factors. Similarly, on nonmacrocycles, de novo fitting produced occupancy-weighted ensembles of many conformers that were generally better-quality density fits than the deposited primary/alternate conformational pairs. The results suggest ubiquitous low-energy ligand conformational ensembles in X-ray diffraction data and provide an alternative to using B-factors as model parameters.
Introduction In early-stage drug discovery, medicinal chemists rely on predictive models to help guide which compounds to synthesise or test…
Defining value is the best place to start Before diving into the specifics of testing AI’s value, the first step…
Introduction After training a classification model, we would like to evaluate its performance by using the trained model on an…