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Response Surface Methodology01:16

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Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
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The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
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The free energy change for a reaction that occurs under the standard conditions of 1 bar pressure and at 298 K is called the standard free energy change. Since free energy is a state function, its value depends only on the conditions of the initial and final states of the system. A convenient and common approach to the calculation of free energy changes for physical and chemical reactions is by use of widely available compilations of standard state thermodynamic data. One method involves the...
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Chemical and Solubility Equilibria02:21

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The free energy change associated with dissolving a solute in a liter of solvent is called the free energy of a solution, ΔGsolution. The overall ΔGsolution is expressed as the balance of ΔGinteraction against the always-favorable free-energy of mixing, ΔGmixing. Solution formation is favorable if  ΔGsolution is less than zero, whereas it is unfavorable if ΔGsolution is greater than zero. In short, for a solution to form and complete dissolution to take place,...
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Chemical Shift: Internal References and Solvent Effects01:17

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In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...
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Related Experiment Video

Updated: Mar 25, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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High-Precision Solvation Free Energy Calculation via Multi-Input Linear Correction in 3D-RISM Theory.

Yutaka Maruyama1,2, Norio Yoshida3

  • 1Maruho Collaborative Project for Theoretical Pharmaceutics, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, 560-8531, Japan.

Journal of Chemical Theory and Computation
|March 24, 2026
PubMed
Summary
This summary is machine-generated.

The new multi-input linear correction (MILC) method significantly improves solvation free energy (SFE) calculations using 3D-RISM theory. This approach enhances accuracy for drug discovery and material design applications.

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Area of Science:

  • Computational Chemistry
  • Physical Chemistry
  • Theoretical Chemistry

Background:

  • The three-dimensional reference interaction site model (3D-RISM) theory offers computational efficiency for solvation free energy (SFE) calculations.
  • Conventional energy functionals in 3D-RISM often overestimate SFEs, necessitating corrections like partial molar volume (PMV).

Purpose of the Study:

  • To introduce the multi-input linear correction (MILC) method to enhance the accuracy of 3D-RISM SFE calculations.
  • To develop a physically motivated, data-driven approach that improves upon existing correction methods.

Main Methods:

  • The MILC method incorporates standard SFE components and physical quantities from calculations with zero solute atomic charges.
  • Requires two independent 3D-RISM calculations per solute.
  • Validated using nested cross-validation on the FreeSolv database (628 molecules).

Main Results:

  • Achieved a mean absolute deviation (MAD) of 0.38 kcal/mol compared to the Bennett acceptance ratio (BAR) method.
  • MILC outperforms conventional volume-based corrections.
  • Demonstrates predictive performance comparable or superior to complex machine learning models with high physical interpretability.

Conclusions:

  • The 3D-RISM theory combined with the MILC method provides a robust and efficient tool for accurate SFE calculations.
  • The MILC method offers high accuracy and statistical reliability for high-throughput applications.
  • This advancement is valuable for drug discovery and material design.