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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Solvation free energy arithmetic for small organic molecules.

Aleksandar Lazaric¹, Viren Pattni¹, Kaprao Fuegner¹

¹School of Molecular Sciences, Arizona State University, Tempe, Arizona, USA.

Journal of Computational Chemistry

|March 3, 2023

Summary

Predicting solvation free energies is crucial for drug design. This study introduces solvation free energy arithmetic for additive models, revealing electrostatics as key to nonadditive contributions in benzene derivatives.

Keywords:

computational drug design solvation thermodynamics

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Area of Science:

Computational chemistry
Physical chemistry
Drug design

Background:

Solvent-mediated interactions significantly impact ligand binding affinities in computational drug design.
Accurate theoretical prediction of these interactions, particularly solvation free energies, remains a challenge.

Purpose of the Study:

To analyze solvation free energy contributions for benzene derivatives in water.
To develop predictive models for solvation free energies and solvent-mediated interactions.
To introduce solvation free energy arithmetic for additive modeling.

Main Methods:

Spatially resolved analysis of local solvation free energy contributions.
Definition and application of solvation free energy arithmetic.
Comparison of substituent effects (carboxyl and nitro-groups) on solvation.
Validation using computationally efficient continuum models.

Main Results:

Developed additive models for describing the solvation of complex compounds.
Identified electrostatics as the primary source of nonadditive solvation free energy contributions.
Demonstrated that continuum models can qualitatively reproduce these electrostatic effects.
Analyzed distinct water interactions of carboxyl and nitro-groups despite similar sterics.

Conclusions:

Solvation free energy arithmetic provides a framework for accurate additive models.
Electrostatic interactions are critical for understanding nonadditive solvation effects.
Computationally efficient continuum models show promise for predicting solvation in complex molecules.
The findings guide the development of improved computational drug design tools.