The accelerated weight histogram method for alchemical free energy calculations.

M Lundborg,J Lidmar,B Hess

doi:10.1063/5.0044352

M Lundborg, J Lidmar + Show 1 more

Open Access

https://doi.org/10.1063/5.0044352

Copy DOI

Abstract

The accelerated weight histogram method is an enhanced sampling technique used to explore free energy landscapes by applying an adaptive bias. The method is general and easy to extend. Herein, we show how it can be used to efficiently sample alchemical transformations, commonly used for, e.g., solvation and binding free energy calculations. We present calculations and convergence of the hydration free energy of testosterone, representing drug-like molecules. We also include methane and ethanol to validate the results. The protocol is easy to use, does not require a careful choice of parameters, and scales well to accessible resources, and the results converge at least as quickly as when using conventional methods. One benefit of the method is that it can easily be combined with other reaction coordinates, such as intermolecular distances.

Highlights

Molecular simulation is a powerful tool for studying and understanding conformations and dynamics of molecules, ranging from simple liquids to complex biomolecules
Accelerated Weight Histogram24 (AWH) is an extended ensemble method to accelerate the calculation of the free energy difference along one or more reaction coordinates
We have presented the application of using AWH for alchemical free energy calculations

Summary

Introduction

Molecular simulation is a powerful tool for studying and understanding conformations and dynamics of molecules, ranging from simple liquids to complex biomolecules. The most common applications are the free energy of solvation of a molecule and the free energy of drugs binding to one of different molecules. The results of such computations are important for designing new drugs and improving existing drugs as part of a virtual screening workflow or for lead optimization.. The results of such computations are important for designing new drugs and improving existing drugs as part of a virtual screening workflow or for lead optimization.1–6 Both relative free energy differences between, e.g., two different molecules in a medium, by transforming one into the other, and absolute free energy differences between a molecule in a medium and in vacuum are of interest.. The results of such computations are important for designing new drugs and improving existing drugs as part of a virtual screening workflow or for lead optimization. Both relative free energy differences between, e.g., two different molecules in a medium, by transforming one into the other, and absolute free energy differences between a molecule in a medium and in vacuum are of interest. The medium can be a solvent, a binding site of a protein, or an active site of an enzyme

Methods

Results

Conclusion