Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology

Abstract

Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens ignore 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than existing methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode. Fragmenstein either takes the coordinates of ligands from a experimental fragment screen and stitches the atoms together to produce a novel merged compound, or uses them to predict the complex for a provided compound. The compound is then energy minimised under strong constraints to obtain a structurally plausible compound. This method is successful in showing the importance of using the coordinates of known binders when predicting the conformation of derivative compounds through a retrospective analysis of the COVID Moonshot data. It has also had a real-world application in hit-to-lead screening, yielding a sub-micromolar merger from parent hits in a single round.