Related Experiment Video
Updated: Oct 22, 2025
08:49
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
640
Shape-Restrained Modeling of Protein-Small-Molecule Complexes with High Ambiguity Driven DOCKing
Panagiotis I Koukos1, Manon Réau1, Alexandre M J J Bonvin1
1Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht 3584CH, The Netherlands.
Journal of Chemical Information and Modeling
|August 26, 2021
Summary
We introduce a new HADDOCK (High Ambiguity Driven DOCKing) protocol using homology information for improved protein-small-molecule complex structure prediction. This template/shape-based docking achieves 81% success in unbound scenarios, nearing bound docking performance.
Area of Science:
- Computational chemistry
- Structural biology
- Drug discovery
Background:
- Small-molecule docking is crucial for predicting protein-small-molecule complex structures.
- Current methods require detailed information about the target or bound complex.
Purpose of the Study:
- To develop and evaluate a novel HADDOCK protocol for structure prediction using homology information.
- To improve the efficiency and accuracy of docking in an unbound scenario.
Main Methods:
- Incorporation of homology information for both receptor and small molecules.
- Development of two template/shape-based docking protocols using dummy atom beads and pharmacophore data.
- Utilizing ambiguous distance restraints to guide the docking simulation.
- Benchmarking against the unbound DUD-E dataset.
Main Results:
- The template/shape-based docking protocol achieved an 81% success rate in unbound docking scenarios.
- A reliable template was identified for 99 out of 102 complexes in the DUD-E dataset.
- Performance closely approaches that of established bound docking methods.
Conclusions:
- Homology-driven shape restraints significantly enhance unbound docking accuracy.
- The new HADDOCK protocol offers a powerful tool for structure prediction in drug discovery.
- This method provides a viable alternative when bound complex information is unavailable.
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