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Effect of electrostatic polarization and bridging water on CDK2-ligand binding affinities calculated using a highly
Lili Duan1, Guoqiang Feng, Xianwei Wang
1School of Physics and Electronics, Shandong Normal University, Jinan 250014, China. duanll@sdnu.edu.cn.
Physical Chemistry Chemical Physics : PCCP
|April 4, 2017
Summary
A new interaction entropy (IE) method with polarized protein-specific charge (PPC) force fields accurately predicts CDK2-ligand binding free energies. Including bridging water and electronic polarization significantly improves simulation accuracy compared to traditional methods.
Area of Science:
- Computational chemistry
- Molecular dynamics
- Biophysics
Background:
- Accurate prediction of protein-ligand binding free energies is crucial for drug discovery.
- Traditional methods often struggle to account for the nuanced effects of water molecules and electronic polarization.
Purpose of the Study:
- To evaluate a new interaction entropy (IE) method combined with a polarized protein-specific charge (PPC) force field for CDK2-ligand binding.
- To assess the impact of bridging water and electronic polarization on binding free energy calculations.
Main Methods:
- Employed the interaction entropy (IE) method with the polarized protein-specific charge (PPC) force field.
- Performed molecular dynamics (MD) simulations of five CDK2-ligand complexes.
- Compared results with the traditional normal mode (Nmode) method and nonpolarized AMBER force field.
Main Results:
- The IE-PPC method achieved a high correlation (0.98) with experimental binding free energies when including bridging water.
- IE-PPC outperformed the Nmode method (0.95 correlation) and nonpolarized simulations (≤0.45 correlation).
- Bridging water was identified as critical for mediating hydrogen bonds and stabilizing the CDK2-ligand complex.
Conclusions:
- The novel IE method with PPC force fields offers superior accuracy for binding free energy calculations.
- Electronic polarization and the role of bridging water are essential considerations in MD simulations for drug discovery.