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Evaluation of Hydration Free Energy by Level-Set Variational Implicit-Solvent Model with Coulomb-Field Approximation

Overview
Specialties Biochemistry
Chemistry
Date 2013 Mar 19
PMID 23505345
Citations 15
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Abstract

In this article, we systematically apply a novel implicit-solvent model, the variational implicit-solvent model (VISM) together with the Coulomb-Field Approximation (CFA), to calculate the hydration free energy of a large set of small organic molecules. Because these molecules have been studied in detail by molecular dynamics simulations and other implicit-solvent models, they provide a good benchmark for evaluating the performance of VISM-CFA. With all-atom Amber force field parameters, VISM-CFA is able to reproduce well not only the experimental and MD simulated total hydration free energy but also the polar and nonpolar contributions individually. The correlation between VISM-CFA and experiments is = 0.763 for the total hydration free energy, with a root-mean-square deviation (RMSD) of 1.83 kcal/mol, and the correlation to results from TIP3P explicit water MD simulations is = 0.839 with a RMSD = 1.36 kcal/mol. In addition, we demonstrate that VISM captures dewetting phenomena in the p53/MDM2 complex and hydrophobic characteristics in the system. This work demonstrates that the level-set VISM-CFA can be used to study the energetic behavior of realistic molecular systems with complicated geometries in solvation, protein-ligand binding, protein-protein association, and protein folding processes.

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References
1.
Uesugi M, Verdine G . The alpha-helical FXXPhiPhi motif in p53: TAF interaction and discrimination by MDM2. Proc Natl Acad Sci U S A. 1999; 96(26):14801-6. PMC: 24728. DOI: 10.1073/pnas.96.26.14801. View

2.
Liu M, Li C, Pazgier M, Li C, Mao Y, Lv Y . D-peptide inhibitors of the p53-MDM2 interaction for targeted molecular therapy of malignant neoplasms. Proc Natl Acad Sci U S A. 2010; 107(32):14321-6. PMC: 2922601. DOI: 10.1073/pnas.1008930107. View

3.
Zhou S, Wang Z, Li B . Mean-field description of ionic size effects with nonuniform ionic sizes: a numerical approach. Phys Rev E Stat Nonlin Soft Matter Phys. 2011; 84(2 Pt 1):021901. PMC: 3727298. DOI: 10.1103/PhysRevE.84.021901. View

4.
Chen Z, Baker N, Wei G . Differential geometry based solvation model I: Eulerian formulation. J Comput Phys. 2010; 229(22):8231-8258. PMC: 2951687. DOI: 10.1016/j.jcp.2010.06.036. View

5.
Dzubiella J, Swanson J, McCammon J . Coupling hydrophobicity, dispersion, and electrostatics in continuum solvent models. Phys Rev Lett. 2006; 96(8):087802. DOI: 10.1103/PhysRevLett.96.087802. View