Accurate Estimation of Solvation Free Energy Using Polynomial Fitting Techniques
Conrad Shyu, F. Marty Ytreberg

TL;DR
This paper presents polynomial fitting and spline interpolation methods to enhance the accuracy of solvation free energy estimates from thermodynamic integration data, reducing the need for additional simulations.
Contribution
It introduces polynomial and spline interpolation techniques for thermodynamic integration data, improving free energy estimates without extra simulations or soft-core scaling.
Findings
Polynomial techniques improve accuracy of free energy estimates.
Non-equidistant lambda values enhance precision.
Methods eliminate need for separate Lennard-Jones and charge simulations.
Abstract
This report details an approach to improve the accuracy and precision of free energy difference estimates using thermodynamic integration data (slope of the free energy with respect to the switching variable lambda) and its application to calculating solvation free energy. The central idea is to utilize polynomial fitting schemes to approximate the thermodynamic integration data to improve the accuracy and precision of the free energy difference estimates. In this report we introduce polynomial and spline interpolation techniques. Two systems with analytically solvable relative free energies are used to test the accuracy and precision of the interpolation approach (Shyu and Ytreberg, J Comput Chem 30: 2297-2304, 2009). We also use both interpolation and extrapolation methods to determine a small molecule salvation free energy. Our simulations show that, using such polynomial techniques…
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Taxonomy
TopicsPhase Equilibria and Thermodynamics · Protein Structure and Dynamics · Advanced Chemical Physics Studies
