Rationalizing protein–ligand interactions via the effective fragment potential method and structural data from classical molecular dynamics

The Effective Fragment Potential (EFP) method, a polarizable quantum mechanics-based force field for describing non-covalent interactions, is utilized to calculate protein-ligand interactions in seven inactive cyclin-dependent kinase 2-ligand complexes, employing structural data from molecular dynamics simulations to assess dynamic and solvent effects. Our results reveal high correlations between experimental binding affinities and EFP interaction energies across all the structural data considered. Using representative structures found by clustering analysis and excluding water molecules yields the highest correlation (R2 of 0.95). In addition, the EFP pairwise interaction energy decomposition analysis identifies critical interactions between the ligands and protein residues and provides insight into their nature. Overall, this study indicates the potential applications of the EFP method in structure-based drug design.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2025-01-27
DOI
https://doi.org/10.1063/5.0247878
Citations
5
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
4.03

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article

Rationalizing protein–ligand interactions via the effective fragment potential method and structural data from classical molecular dynamics

Lyudmila V. Slipchenko, Andrés S. Urbina
5 citations
The Journal of Chemical Physics
Protein Structure and Dynamics
4.03
article

Rationalizing protein–ligand interactions via the effective fragment potential method and structural data from classical molecular dynamics

Lyudmila V. Slipchenko, Andrés S. Urbina
article en
5 citations

Abstract

The Effective Fragment Potential (EFP) method, a polarizable quantum mechanics-based force field for describing non-covalent interactions, is utilized to calculate protein-ligand interactions in seven inactive cyclin-dependent kinase 2-ligand complexes, employing structural data from molecular dynamics simulations to assess dynamic and solvent effects. Our results reveal high correlations between experimental binding affinities and EFP interaction energies across all the structural data considered. Using representative structures found by clustering analysis and excluding water molecules yields the highest correlation (R2 of 0.95). In addition, the EFP pairwise interaction energy decomposition analysis identifies critical interactions between the ligands and protein residues and provides insight into their nature. Overall, this study indicates the potential applications of the EFP method in structure-based drug design.

The Journal of Chemical PhysicsVol. 162(4)
Purdue University West Lafayette (US)
National Science Foundation, National Institute of General Medical Sciences
Clean water and sanitation
Openalex Percentile: Top 7%
Protein Structure and Dynamics
4.03
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