Assessing interaction recovery of predicted protein-ligand poses

David Errington; Constantin Schneider; Cédric Bouysset; Frédéric A. Dreyer

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arXiv · 2409.20227

Assessing interaction recovery of predicted protein-ligand poses

David Errington·Constantin Schneider·Cédric Bouysset·Frédéric A. Dreyer

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Abstract

The field of protein-ligand pose prediction has seen significant advances in recent years, with machine learning-based methods now being commonly used in lieu of classical docking methods or even to predict all-atom protein-ligand complex structures. Most contemporary studies focus on the accuracy and physical plausibility of ligand placement to determine pose quality, often neglecting a direct assessment of the interactions observed with the protein. In this work, we demonstrate that ignoring protein-ligand interaction fingerprints can lead to overestimation of model performance, most notably in recent protein-ligand cofolding models which often fail to recapitulate key interactions.

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David Errington, Constantin Schneider, Cédric Bouysset, Frédéric A. Dreyer. 2024-09-30. Assessing interaction recovery of predicted protein-ligand poses. https://arxiv.org/abs/2409.20227

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