Assessing interaction recovery of predicted protein-ligand poses

• URL: http://arxiv.org/abs/2409.20227v1
• Date: Mon, 30 Sep 2024 12:06:13 GMT
• Title: Assessing interaction recovery of predicted protein-ligand poses
• Authors: David Errington, Constantin Schneider, Cédric Bouysset, Frédéric A. Dreyer,
• Abstract summary: We show that ignoring protein-ligand interaction fingerprints can lead to overestimation of model performance. In this work, we demonstrate that ignoring protein-ligand interaction fingerprints can lead to overestimation of model performance.
• Score: 0.39331876802505306
• License: http://creativecommons.org/licenses/by/4.0/
• 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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