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2022-04-26

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cc-by (c) Miñarro-Lleonar, Marina et al., 2022
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/191531

Development of an Automatic Pipeline for Participation in the CELPP Challenge

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Recurs relacionat

https://doi.org/10.3390/ijms23094756

Resum

The prediction of how a ligand binds to its target is an essential step for Structure-Based Drug Design (SBDD) methods. Molecular docking is a standard tool to predict the binding mode of a ligand to its macromolecular receptor and to quantify their mutual complementarity, with multiple applications in drug design. However, docking programs do not always find correct solutions, either because they are not sampled or due to inaccuracies in the scoring functions. Quantifying the docking performance in real scenarios is essential to understanding their limitations, managing expectations and guiding future developments. Here, we present a fully automated pipeline for pose prediction validated by participating in the Continuous Evaluation of Ligand Pose Prediction (CELPP) Challenge. Acknowledging the intrinsic limitations of the docking method, we devised a strategy to automatically mine and exploit pre-existing data, defining-whenever possible-empirical restraints to guide the docking process. We prove that the pipeline is able to generate predictions for most of the proposed targets as well as obtain poses with low RMSD values when compared to the crystal structure. All things considered, our pipeline highlights some major challenges in the automatic prediction of protein-ligand complexes, which will be addressed in future versions of the pipeline. Keywords: D3R; automated pipeline; binding mode prediction; docking; pocket detection.

Matèries

Disseny de medicaments, Lligands (Bioquímica), Desenvolupament de medicaments

Matèries (anglès)

Drug design, Ligands (Biochemistry), Drug development

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Articles publicats en revistes (Farmàcia, Tecnologia Farmacèutica i Fisicoquímica)

Citació

MIÑARRO-LLEONAR, Marina, et al. Development of an Automatic Pipeline for Participation in the CELPP Challenge. International Journal of Molecular Sciences. 2022. Vol. 23, num. 9, pags. 4756. ISSN 1661-6596. [consulted: 3 of August of 2026]. Available at: https://hdl.handle.net/2445/191531

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