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A new set of atomic radii for accurate estimation of solvation free energy by Poisson-Boltzmann solvent model.

Yamagishi J, Okimoto N, Morimoto G, Taiji M - J Comput Chem (2014)

Bottom Line: The presented PB radii were optimized using results from explicit solvent simulations of the large systems.The performances using our PB radii showed high accuracy for the estimation of solvation free energies at the level of the molecular fragment.The obtained PB radii are effective for the detailed analysis of the solvation effects of biomolecules.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, 5-15 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan; Laboratory for Computational Molecular Design, Quantitative Biology Center (QBiC), RIKEN, 1-6-5 Minatojima-Minatomachi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan.

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Correlation between the solvation free energies of test molecules calculated by PB and explicit solvent simulations. Circles are the 12 peptides obtained from PDB, and triangles are the 11 conformations of chignolin.
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fig03: Correlation between the solvation free energies of test molecules calculated by PB and explicit solvent simulations. Circles are the 12 peptides obtained from PDB, and triangles are the 11 conformations of chignolin.

Mentions: The solvation free energies for molecules larger than the training molecules were further examined, because our PB radii were optimized using simple training molecules. The performances of the three PB methods on our test molecules are given in Table2 and Figure 3. These results clearly identified our PB as the most accurate method among the three PB methods examined. In addition to the total solvation free energies, our PB showed good accuracy for the estimation of solvation free energies on a per-residue basis (Fig. 4 for nonterminal residues, and Supporting Information, Figs. S2–S3 for N- and C-terminal residues). In these graphs, Swanson's PB showed large errors in solvation free energies on a per-residue basis, especially for charged residues, as expected from the results for training molecules. Some errors in the total solvation free energy may be compensated by the underestimated and overestimated solvation free energies on each residue for Swanson's PB; this degree of compensations is dependent on the amino acid sequences of proteins. Thus, it is difficult when using Swanson's PB to compare the results from proteins with different amino acid sequences. Unlike the results for training molecules, Tan's PB tended to underestimate both the total and per-residue solvation free energies for the test molecules. This tendency may originate from the training molecules used in their optimization of PB radii; their PB radii were parameterized without consideration of the interactions between backbone and side-chain atoms. In addition, they lacked consideration for the secondary structures of proteins. Their insufficient treatment for the selection of training molecules would thus induce estimation inaccuracies for larger peptides.


A new set of atomic radii for accurate estimation of solvation free energy by Poisson-Boltzmann solvent model.

Yamagishi J, Okimoto N, Morimoto G, Taiji M - J Comput Chem (2014)

Correlation between the solvation free energies of test molecules calculated by PB and explicit solvent simulations. Circles are the 12 peptides obtained from PDB, and triangles are the 11 conformations of chignolin.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263261&req=5

fig03: Correlation between the solvation free energies of test molecules calculated by PB and explicit solvent simulations. Circles are the 12 peptides obtained from PDB, and triangles are the 11 conformations of chignolin.
Mentions: The solvation free energies for molecules larger than the training molecules were further examined, because our PB radii were optimized using simple training molecules. The performances of the three PB methods on our test molecules are given in Table2 and Figure 3. These results clearly identified our PB as the most accurate method among the three PB methods examined. In addition to the total solvation free energies, our PB showed good accuracy for the estimation of solvation free energies on a per-residue basis (Fig. 4 for nonterminal residues, and Supporting Information, Figs. S2–S3 for N- and C-terminal residues). In these graphs, Swanson's PB showed large errors in solvation free energies on a per-residue basis, especially for charged residues, as expected from the results for training molecules. Some errors in the total solvation free energy may be compensated by the underestimated and overestimated solvation free energies on each residue for Swanson's PB; this degree of compensations is dependent on the amino acid sequences of proteins. Thus, it is difficult when using Swanson's PB to compare the results from proteins with different amino acid sequences. Unlike the results for training molecules, Tan's PB tended to underestimate both the total and per-residue solvation free energies for the test molecules. This tendency may originate from the training molecules used in their optimization of PB radii; their PB radii were parameterized without consideration of the interactions between backbone and side-chain atoms. In addition, they lacked consideration for the secondary structures of proteins. Their insufficient treatment for the selection of training molecules would thus induce estimation inaccuracies for larger peptides.

Bottom Line: The presented PB radii were optimized using results from explicit solvent simulations of the large systems.The performances using our PB radii showed high accuracy for the estimation of solvation free energies at the level of the molecular fragment.The obtained PB radii are effective for the detailed analysis of the solvation effects of biomolecules.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, 5-15 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan; Laboratory for Computational Molecular Design, Quantitative Biology Center (QBiC), RIKEN, 1-6-5 Minatojima-Minatomachi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan.

Show MeSH