2026-09-22 · Fragment-based drug discovery (FBDD) — computational/cheminformatics method for fragment-to-lead optimization (not target-specific) · ACS Medicinal Chemistry Letters (ACS)

Rule-Based SMILES Editing Tool Aids Fragment-to-Lead Optimization

fragment-based drug discoveryFBDDcheminformaticsSMILES manipulationhit-to-lead optimizationopen-source tools

A new method systematically edits SMILES strings—swapping atom types, resizing or opening rings, and grafting fragments—to generate analog ideas for fragment-to-lead optimization.
First implemented as a KNIME workflow tested on fragments from multiple programs, it's now also available as open-source Python code paired with AutoDock Vina docking.
This non-learned, rule-based approach complements AI/ML generative design, offering a practical option when training data for a target is scarce.

💡 Points

Honestly this is what I'd do by hand anyway—ring contraction, bioisostere swaps, fragment grafting—just automated and exhaustive instead of me sketching ten ideas on a whiteboard. For a scarce-data fragment series, I'd trust this over a generative model I can't sanity-check. Free KNIME/Python beats begging IT for another SaaS license too.

Fragment Optimization─Simple SMILES String Manipulation Strategies to Optimize a Hit or Fragment ↗