Accurate Calculation of Hydration Free Energies Using Macroscopic Solvent Models

Sitkoff, Doree; Sharp, Kim A.; Honig, Barry

doi:10.1021/j100058a043

Cited by 2,031 publications

(2,179 citation statements)

References 12 publications

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“…It should be noted that the uncertainty in the estimated non-electrostatic terms may be quite substantial, although it is difficult to provide their accurate estimate. For computation of non-electrostatic terms we adapted methods described by Honig and coworkers [39,10] and by Beveridge and coworkers [40]. Both groups have found that the estimated total free energies of binding were overestimated.…”

Section: Resultsmentioning

confidence: 99%

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Poisson–Boltzmann model analysis of binding mRNA cap analogues to the translation initiation factor eIF4E

Szklarczyk

Zuberek

Antosiewicz

2009

Biophysical Chemistry

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT AbstractThe electrostatic free energy of binding of two analogues of the 5'-mRNA cap, differing in size and electric charge, to the wild type and mutated eukaryotic initiation factor eIF4E was computed using the finite difference solutions to the Poisson-Boltzmann equation. Two definitions of the solute-solvent dielectric boundary were used: van der Waals model, solvent exclusion (SE) model. The computed electrostatic energies were supplemented by estimations of the non polar and entropic contributions. A comparison with experimental data for the investigated systems was done. It appears that the SE model with additional contribution fits experimental findings better than the van der Waals model does.

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Section: Resultsmentioning

confidence: 99%

“…Calculation of the first component has been described above. The non polar contribution was estimated applying a model of the solvent accessible surface area (SASA) [39], in which the change of the free energy corresponding to non polar interactions is proportional to the change of SASA:…”

Section: Other Than Electrostatic Contributions To the Free Energymentioning

confidence: 99%

Poisson–Boltzmann model analysis of binding mRNA cap analogues to the translation initiation factor eIF4E

Szklarczyk

Zuberek

Antosiewicz

2009

Biophysical Chemistry

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“…The dielectric constant was set to 1 for the interior solute and 80 for the surrounding solvent. The LCPO method [27] was used to calculate the Solvent Accessible Surface Area (SASA) for the estimation of the nonpolar solvation free energy (ΔG np ) with =0.0072 kcal mol -1 Å -2 and =0.00 kcal mol -1 [28]. The polar contribution (ΔG GB ) of desolvation was computed using a modified GB model developed by Onufriev et al [29].…”

Section: Mm/gbsa Calculation and Free Energy Decompositionmentioning

confidence: 99%

Insight into ligand selectivity in HCV NS5B polymerase: molecular dynamics simulations, free energy decomposition and docking

Froeyen

Herdewijn

2009

J Mol Model

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Modeling studies were performed on HCV NS5B Polymerase in an effort to design new inhibitors. The binding models of five different scaffold inhibitors were investigated and compared by using molecular dynamics simulations, free energy calculation and decomposition. Our results show Tyr448 plays the most critical role in the binding of most inhibitors. In addition, favorable contributions of residues Pro197, Arg200, Cys366, Met414 and Tyr448 in a deep hydrophobic pocket prove to be important for the selectivity of inhibitors. Furthermore, an optimized docking protocol was presented based on cross-docking the five inhibitors in the palm binding site of this enzyme using the Autodock program. This protocol was used later to virtually screen NCI and Maybridge diversity set libraries. The binding site was profiled via the statistics and analysis of the hydrogen bond networks formed between the receptor and the top-ranked diversity set compounds. Based on our detailed binding site analysis two useful rules were proposed to guide the selection of promising hits.Response to Reviewers: Question1: It is a pity that nothing in detail is discussed about found structures resulting from the virtual screening. Did the authors find new promising ligands with high (higher than the template ligands?) affinity and are they structurally diverse or similar to the used ones?Answer: We have found some promising compounds after the virtual screening. They are structurally diverse. Most of them form hydrogen bonds with the critical residues such as Tyr448 and have strong hydrophobic interaction with the residues in the deep hydrophobic pocket mentioned in our article. These compounds are under biological test.Question2: Additionally to figure 5 at least one figure should be added, showing the amino acid residues of the active site with the discussed most important interactions with one (the best?) ligand. This would considerably help to understand the discussion without looking in the original pdb-files. AbstractModeling studies were performed on HCV NS5B Polymerase in an effort to design new inhibitors. The binding models of five different scaffold inhibitors were investigated and compared by using molecular dynamics simulations, free energy calculation and decomposition. Our results show Tyr448 plays the most critical role in the binding of most inhibitors. In addition, favorable contributions of residues Pro197, Arg200, Cys366, Met414 and Tyr448 in a deep hydrophobic pocket prove to be important for the selectivity of inhibitors.Furthermore, an optimized docking protocol was presented based on cross-docking the five inhibitors in the palm binding site of this enzyme using the Autodock program. This protocol was used later to virtually screen NCI and Maybridge diversity set libraries. The binding site was profiled via the statistics and analysis of the hydrogen bond networks formed between the receptor and the top-ranked diversity set compounds. Based on our detailed binding site analysis two useful rules were proposed to ...

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“…The solvation free energy, G sol , is decomposed into polar and nonpolar contributions: the polar contribution (G GB ) is calculated by solving the generalized Born equation [43] using dielectric constants of 1 and 78.5 for solute and solvent, respectively, whereas the nonpolar contribution, G nonpolar , is estimated from the solvent accessible surface area (SASA) [44], which is determined using a water probe with a radius of 1.4 Å . The surface tension constant g was set to 0.005 kcal/mol/Å 2 .…”

Section: Mm-gbsa Binding Calculationsmentioning

confidence: 99%

Identification of aspartic acid-203 in human thymidine phosphorylase as an important residue for both catalysis and non-competitive inhibition by the small molecule “crystallization chaperone” 5′-O-tritylinosine (KIN59)

Bronckaers

Aguado

Negri

et al. 2009

Biochemical Pharmacology

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Accurate Calculation of Hydration Free Energies Using Macroscopic Solvent Models

Cited by 2,031 publications

References 12 publications

Poisson–Boltzmann model analysis of binding mRNA cap analogues to the translation initiation factor eIF4E

Poisson–Boltzmann model analysis of binding mRNA cap analogues to the translation initiation factor eIF4E

Insight into ligand selectivity in HCV NS5B polymerase: molecular dynamics simulations, free energy decomposition and docking

Identification of aspartic acid-203 in human thymidine phosphorylase as an important residue for both catalysis and non-competitive inhibition by the small molecule “crystallization chaperone” 5′-O-tritylinosine (KIN59)

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