BioExcel Webinar #80: Accounting for protein and ligand flexibility in molecular docking and virtual screening of challenging targets (2025-1-28)

Knowledge of atomic-level structures of ligand-protein complexes is key for basic research and structure-based drug design. Computational methods have become a valid complement to experiments, but accuracy of predictions generally degrades with the extent of the structural changes associated to binding. Accurate description of ligand flexibility is equally crucial, particularly in a virtual screening (VS) whereby initial structures are often generated without accounting for structural adaptation in binding. To address this issue on the proteins side, we recently introduced gEDES (generalized Ensemble Docking with Enhanced-sampling of pocket Shape), a computational method based on metadynamics to generate bound-like conformations of proteins by only exploiting their unbound structure. In this talk, I will first introduce the gEDES protocol; next, I will talk about SHAPER, an algorithm aiming to generate ligand structures snugly fitting into the binding pocket of a generic receptor, adapting to its geometry. Preliminary results demonstrate that using this dynamic shape-matching algorithm improves the accuracy of VS campaigns compared to flexible docking calculations.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-28
DOI
https://doi.org/10.5281/zenodo.14755264
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

BioExcel Webinar #80: Accounting for protein and ligand flexibility in molecular docking and virtual screening of challenging targets (2025-1-28)

Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

BioExcel Webinar #80: Accounting for protein and ligand flexibility in molecular docking and virtual screening of challenging targets (2025-1-28)

article en

Abstract

Knowledge of atomic-level structures of ligand-protein complexes is key for basic research and structure-based drug design. Computational methods have become a valid complement to experiments, but accuracy of predictions generally degrades with the extent of the structural changes associated to binding. Accurate description of ligand flexibility is equally crucial, particularly in a virtual screening (VS) whereby initial structures are often generated without accounting for structural adaptation in binding. To address this issue on the proteins side, we recently introduced gEDES (generalized Ensemble Docking with Enhanced-sampling of pocket Shape), a computational method based on metadynamics to generate bound-like conformations of proteins by only exploiting their unbound structure. In this talk, I will first introduce the gEDES protocol; next, I will talk about SHAPER, an algorithm aiming to generate ligand structures snugly fitting into the binding pocket of a generic receptor, adapting to its geometry. Preliminary results demonstrate that using this dynamic shape-matching algorithm improves the accuracy of VS campaigns compared to flexible docking calculations.

Zenodo (CERN European Organization for Nuclear Research)
University of Cagliari (IT)
Openalex Percentile: Top 59%
Computational Drug Discovery Methods
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BioExcel Webinar #80: Accounting for protein and ligand flexibility in molecular docking and virtual screening of challenging targets (2025-1-28) · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS