ArticleJournal of computational chemistry2024
Accurate prediction of dynamic protein-ligand binding using P-score ranking.
Article in Journal of computational chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- FMOPhore for hotspot identification and efficient fragment-to-lead growth strategies.Nature communications · 2026Article
- Visualization of Properties in the Fragment Molecular Orbital Method Using Facio.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Analyzing Many-Body Charge Transfer Effects With the Fragment Molecular Orbital Method.Journal of computational chemistry · 2025Article
- Quantum Mechanics-Based Ranking of Predicted Proteolysis Targeting Chimeras-Mediated Ternary Complexes.ACS medicinal chemistry letters · 2025Article
- Thermal Titration Molecular Dynamics: The Revenge of the Fragments.Journal of chemical information and modeling · 2025Article
- Accurate prediction of dynamic protein-ligand binding using P-score ranking.Journal of computational chemistry · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Protein-ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein-ligand system, solvent-mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions. The workflow described here attempts to address these limitations by combining supervised molecular dynamics with dynamical averaging quantum mechanics fragment molecular orbital. This combination significantly increased the ability to predict the experimental binding structure of protein-ligand complexes independent from the starting position of the ligands or the binding site conformation. We found that the predictive power could be enhanced by combining the residence time and interaction energies as descriptors in a novel scoring function named the P-score. This is illustrated using six different protein-ligand targets as case studies.
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Registered trials
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