Leveraging the Sampling Efficiency of RE-EDS in OpenMM Using a Shifted Reaction-Field With an Atom-Based Cutoff


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Date

2022-09-14

Publication Type

Journal Article

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Abstract

Replica-exchange enveloping distribution sampling (RE-EDS) is a pathway-independent multistate free-energy method currently implemented in the GROMOS software package for molecular dynamics (MD) simulations. It has a high intrinsic sampling efficiency as the interactions between the unperturbed particles have to be calculated only once for multiple end-states. As a result, RE-EDS is an attractive method for the calculation of relative solvation and binding free energies. An essential requirement for reaching this high efficiency is the separability of the nonbonded interactions into solute–solute, solute–environment, and environment–environment contributions. Such a partitioning is trivial when using a Coulomb term with a reaction-field (RF) correction to model the electrostatic interactions but not when using lattice-sum schemes. To avoid cutoff artifacts, the RF correction is typically used in combination with a charge-group-based cutoff, which is not supported by most small-molecule force fields as well as other MD engines. To address this issue, we investigate the combination of RE-EDS simulations with a recently introduced RF scheme including a shifting function that enables the rigorous calculation of RF electrostatics with atom-based cutoffs. The resulting approach is validated by calculating solvation free energies with the generalized AMBER force field in water and chloroform using both the GROMOS software package and a proof-of-concept implementation in OpenMM.

Publication status

published

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Volume

157 (10)

Pages / Article No.

104117

Publisher

American Institute of Physics

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Edition / version

Methods

Software

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Organisational unit

09458 - Riniker, Sereina Z. / Riniker, Sereina Z. check_circle
08820 - Hünenberger, Philippe (Tit.-Prof.) check_circle

Notes

Funding

178762 - Passive Membrane-Permeability Prediction for Peptides and Peptidomimetics Using Computational Methods (SNF)
175944 - A Combinatorial Computational Chemistry Approach to Force-Field Development (SNF)

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