FoXSight: Facilitating Computational Hit Identification in Crystallographic Fragment Screening Experiments

FoXSight detects recurring, target-specific ligand density features in crystallographic fragment screening using Difference-of-Gaussian filtering, enabling interpretable hit maps across seven protein targets.

• Why it matters: Weak, noisy, partially occupied electron-density signals and thousands of datasets make reliable hit identification difficult, especially when established outputs are too hard to inspect systematically.
• What they did: FoXSight applies DoG filtering to multi-reference subtraction maps to highlight recurring density patterns, and it was evaluated on in-house and public datasets across seven protein targets, with comparisons to PanDDA when possible.
• The result: In a challenging human Cathepsin L fragment screening campaign, FoXSight served as the primary hit identification tool when other methods’ outputs were impractical to review, supporting downstream ligand modeling.

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