Facilitating the identification of cryo-EM hit matter in drug discovery with Astex-Faro

Cryogenic electron microscopy (cryo-EM) is emerging as a tool for large-scale ligand screening and fragment-based drug discovery, generating extensive collections of reconstructions. At the same time, the systematic inspection of local density variations remains challenging, particularly when identifying weak or partially occupied features. Here, we present Astex-Faro, a statistical framework that defines an expected specimen state from a reference ensemble and identifies significant structural deviations in a target map through comparison against this reference. Furthermore, the method allows the enhancement of weak or poorly resolved features, enabling the recovery of signals that would otherwise be difficult to interpret. Fourier Shell Coherence (FSCoh) is introduced as a metric that quantifies consistency across reconstruction ensembles. We show that Astex-Faro reliably detects subtle structural features and improves their interpretability across datasets spanning a broad range of experimental challenges, from highly homogeneous specimens to membrane proteins, low-occupancy ligands and fragment-screening experiments. Together, these developments provide a practical framework for cryo-EM screening, increasing confidence in hit identification and reducing the risk of missed binding events.