Assessing interaction recovery of predicted protein-ligand poses
<|reference_start|>Assessing interaction recovery of predicted protein-ligand poses: 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.<|reference_end|>
@article{errington2024assessing,
    title={Assessing interaction recovery of predicted protein-ligand poses},
    author={David Errington, Constantin Schneider, C'edric Bouysset, Fr'ed'eric
  A. Dreyer},
    journal={arXiv preprint arXiv:2409.20227},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.20227},
    primaryClass={q-bio.BM cs.LG}
}