Potential of mean force calculation of solute molecules in water by a modified solvent-accessible surface method

Fukunishi, Yoshifumi

doi:10.1002/(sici)1096-987x(199710)18:13<1656::aid-jcc7>3.0.co;2-q

Cited by 9 publications

(15 citation statements)

References 65 publications

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“…The two‐methane PMF prediction by SASA is much poorer compared to that by MSA, as has been noted before 46, 47, 61, 62, 65, 66. The SASA‐predicted contact minimum in Figure 6 is at −1.20 kcal/mol, which is almost twice as deep as the simulated value.…”

Section: Comparing Explicit‐ and Implicit‐water Hydrophobic Potentialsmentioning

confidence: 73%

“…A main focus here is on the effectiveness of several surface area and volume‐based implicit‐solvent hydrophobic interaction potentials 55–72. Despite their many limitations,73 such as some of these approaches' failure to account for the significant effects of curvature of nonpolar surfaces,74–77 implicit‐solvent models have played a major role in shaping our conceptualization of hydrophobic interactions in proteins 55–72. Here we assess to what degree they are capable of capturing nonadditive effects by comparing the predictions from several of these models against the three‐methane PMF that we recently obtained by explicit‐water simulations 12…”

Section: Explicit‐water Simulations Of Nonadditive Hydrophobic Effectsmentioning

confidence: 99%

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Anti‐cooperativity and cooperativity in hydrophobic interactions: Three‐body free energy landscapes and comparison with implicit‐solvent potential functions for proteins

Shimizu

Chan

2002

Proteins

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Potentials of mean force (PMFs) of three-body hydrophobic association are investigated to gain insight into similar processes in protein folding. Free energy landscapes obtained from explicit simulations of three methanes in water are compared with that predicted by popular implicit-solvent effective potentials for the study of proteins. Explicit-water simulations show that for an extended range of three-methane configurations, hydrophobic association at 25 degrees C under atmospheric pressure is mostly anti-cooperative, that is, less favorable than if the interaction free energies were pairwise additive. Effects of free energy nonadditivity on the kinetic path of association and the temperature dependence of additivity are explored by using a three-methane system and simplified chain models. The prevalence of anti-cooperativity under ambient conditions suggests that driving forces other than hydrophobicity also play critical roles in protein thermodynamic cooperativity. We evaluate the effectiveness of several implicit-solvent potentials in mimicking explicit water simulated three-body PMFs. The favorability of the contact free energy minimum is found to be drastically overestimated by solvent accessible surface area (SASA). Both the SASA and a volume-based Gaussian solvent exclusion model fail to predict the desolvation barrier. However, this barrier is qualitatively captured by the molecular surface area model and a recent "hydrophobic force field." None of the implicit-solvent models tested are accurate for the entire range of three-methane configurations and several other thermodynamic signatures considered.

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Section: Comparing Explicit‐ and Implicit‐water Hydrophobic Potentialsmentioning

confidence: 73%

Section: Explicit‐water Simulations Of Nonadditive Hydrophobic Effectsmentioning

confidence: 99%

Anti‐cooperativity and cooperativity in hydrophobic interactions: Three‐body free energy landscapes and comparison with implicit‐solvent potential functions for proteins

Shimizu

Chan

2002

Proteins

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“…The van der Waals interaction is relatively short-range interaction compared with the Coulomb interaction, and E ASA can include E vdW . 24 The free energy of the protein is divided into the following five terms:…”

Section: Methodsmentioning

confidence: 99%

“…E ASA can partially represent the intrapeptide vdW interactions by changing the solvation parameters. 24 Hence, only E h-bond , E ASA , and TS are estimated. The free energy of this model for a protein/peptide of n residues is thus expressed…”

Section: Methodsmentioning

confidence: 99%

Folding-unfolding energy change of a simple sphere model protein and an energy landscape of the folding process

Fukunishi

1998

Proteins

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We have calculated the free energy of a spherical model of a protein or part of a protein generated in the way of protein folding. Two spherical models are examined; one is a homogeneous model consisting of only one residue type--hydrophobic. The other is a heterogeneous model consisting of two residue types--strong hydrophobic and weak hydrophobic. Both models show a folding transition state, and the latter model reproduces the trend of the experimental folded-unfolded energy change. The heterogeneous model suggests that in the folding process of a protein of more than 70 residues, a specific region of the protein folds first to form a stable region, then the other residues follow the folding process. The energy landscape of folding of a small protein is approximately a funnel model, whereas a flatter energy landscape is suggested for larger proteins of more than 55-70 residues.

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“…One problem with the GB method is the calculation of the cavity effect. When a cavity is generated between the solutes, the calculated electrostatic interactions in the GB model are underestimated because of the continuum solvent model [11,15,24]. In the SA method, the hydrophobic interaction between solute and solvent is calculated only approximately.…”

Section: Introductionmentioning

confidence: 99%

Calculation of Protein–ligand Binding Free Energy Using Smooth Reaction Path Generation (Srpg) Method: A Comparison of the Explicit Water Model, Gb/Sa Model and Docking Score Function

Mitomo¹,

Fukunishi²,

Higo³

et al. 2009

Genome Informatics 2009

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We compared the protein-ligand binding free energies (flG) obtained by the explicit water model, the MM-G8/SA (molecular-mechanics generalized 80m surface area) model, and the docking scoring function. The free energies by the explicit water model and the MM-G8/SA model were calculated by the previously developed Smooth Reaction Path Generation (SRPG) method. In the SRPG method, a smooth reaction path was generated by linking two coordinates, one a bound state and the other an unbound state. The free energy surface along the path was calculated by a molecular dynamics (MD) simulation, and the binding free energy was estimated from the free energy surface. We applied these methods to the streptavidin-and-biotin system. The flG value by the explicit water model was close to the experimental value. The flG value by the MM-G8/SA model was overestimated and that by the scoring function was underestimated. The free energy surface by the explicit water model was close to that by the G8/SA model around the bound state (distances of < 6 A), but the discrepancy appears at distances of> 6 A. Thus, the difference in long-range Coulomb interaction should cause the error in flG. The scoring function cannot take into account the entropy change of the protein. Thus, the error of flG could depend on the target protein.

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Potential of mean force calculation of solute molecules in water by a modified solvent-accessible surface method

Cited by 9 publications

References 65 publications

Anti‐cooperativity and cooperativity in hydrophobic interactions: Three‐body free energy landscapes and comparison with implicit‐solvent potential functions for proteins

Anti‐cooperativity and cooperativity in hydrophobic interactions: Three‐body free energy landscapes and comparison with implicit‐solvent potential functions for proteins

Folding-unfolding energy change of a simple sphere model protein and an energy landscape of the folding process

Calculation of Protein–ligand Binding Free Energy Using Smooth Reaction Path Generation (Srpg) Method: A Comparison of the Explicit Water Model, Gb/Sa Model and Docking Score Function

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