From Implicit to Explicit: An Interaction-Reorganization Approach to Molecular Solvation Energy

Accurate calculation of solvation energies has long fascinated researchers, but complex interactions within bulk water molecules pose significant challenges. Currently, molecular solvation energy calculations are mostly based on implicit solvent approximations in which the solvent molecules are treated as continuum dielectric media. However, the implicit solvent approach is not ideal because it lacks certain real solvation effects, such as that of the first solvation shell, etc. Here, we propose an explicit solvent approach, interaction-reorganization solvation (IRS) method, for molecular solvation energy calculations. The IRS approach achieves predictive accuracy comparable to that of the widely recognized solvation model based on the density (SMD) method and is significantly more accurate than that of the Poisson-Boltzmann/generalized Born surface area (PB/GBSA) methods. This is demonstrated in both the correlation coefficient and the mean absolute error (MAE) with respect to the experimental data. The IRS method is based on molecular dynamics simulation in explicit solvent and does not need to solve Poisson-Boltzmann or Schrödinger equations. On the other hand, the accuracy of the IRS method does depend on the accuracy of the molecular force field used in MD simulations. We expect that the IRS method will be very useful for the solvation energy calculations of molecules.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2024-12-13
DOI
https://doi.org/10.1021/acs.jctc.4c01283
Citations
9
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
3.25

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article

From Implicit to Explicit: An Interaction-Reorganization Approach to Molecular Solvation Energy

Kaifang Huang, Lili Duan, John Z. H. Zhang
9 citations
Journal of Chemical Theory and Computation
Computational Drug Discovery Methods
3.25
article

From Implicit to Explicit: An Interaction-Reorganization Approach to Molecular Solvation Energy

Kaifang Huang, Lili Duan, John Z. H. Zhang
article en
9 citations

Abstract

Accurate calculation of solvation energies has long fascinated researchers, but complex interactions within bulk water molecules pose significant challenges. Currently, molecular solvation energy calculations are mostly based on implicit solvent approximations in which the solvent molecules are treated as continuum dielectric media. However, the implicit solvent approach is not ideal because it lacks certain real solvation effects, such as that of the first solvation shell, etc. Here, we propose an explicit solvent approach, interaction-reorganization solvation (IRS) method, for molecular solvation energy calculations. The IRS approach achieves predictive accuracy comparable to that of the widely recognized solvation model based on the density (SMD) method and is significantly more accurate than that of the Poisson-Boltzmann/generalized Born surface area (PB/GBSA) methods. This is demonstrated in both the correlation coefficient and the mean absolute error (MAE) with respect to the experimental data. The IRS method is based on molecular dynamics simulation in explicit solvent and does not need to solve Poisson-Boltzmann or Schrödinger equations. On the other hand, the accuracy of the IRS method does depend on the accuracy of the molecular force field used in MD simulations. We expect that the IRS method will be very useful for the solvation energy calculations of molecules.

Journal of Chemical Theory and ComputationVol. 20(24)
Shenzhen University (CN), New York University Shanghai (CN), Shandong Normal University (CN), Shenzhen Institutes of Advanced Technology (CN), Shenzhen Technology University (CN), New York University (US), East China Normal University (CN)
New York University Shanghai, York University, National Natural Science Foundation of China, Chinese Academy of Sciences, East China Normal University, Natural Science Foundation of Shandong Province, Shenzhen University, Serbian Academy of Sciences and Arts, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
Affordable and clean energy
Openalex Percentile: Top 7%
Computational Drug Discovery Methods
3.25
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