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Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field.

Rae A Corrigan¹, Guowei Qi², Andrew C Thiel¹

¹Roy J Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa 52242, United States.

Journal of Chemical Theory and Computation

|March 26, 2021

Summary

New implicit solvent models for polarizable force fields accelerate computational protein design and folding simulations. These models offer accurate and efficient alternatives to explicit solvent treatments, enabling complex molecular studies.

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Area of Science:

Computational chemistry
Molecular modeling
Biophysics

Background:

Explicit solvent treatment is computationally expensive for large-scale molecular simulations.
Implicit solvent models offer a computationally efficient alternative for studying biomolecules.

Purpose of the Study:

To develop and validate implicit solvent models for the polarizable atomic multipole AMOEBA force field.
To enable computationally demanding applications like protein design and folding.

Main Methods:

Implemented three continuum electrostatics models: Poisson-Boltzmann equation (PBE) numerical solutions, domain-decomposition conductor-like screening model (ddCOSMO), and generalized Kirkwood (GK) approximation.
Combined electrostatics with novel nonpolar cavitation and dispersion terms.
Optimized electrostatic model parameters using small-molecule solvation free energy differences.

Main Results:

Achieved low mean signed errors (0.00-0.05 kcal/mol) and mean unsigned errors (0.58-0.70 kcal/mol) for solvation free energies.
Validated models against explicit solvent simulations for proteins and nucleic acids.
Models are available in Tinker, OpenMM, and Force Field X software packages.

Conclusions:

The developed implicit solvent models provide accurate and efficient electrostatic treatment for polarizable force fields.
These models significantly reduce computational cost, facilitating large-scale protein folding and design studies.
The availability of these models in popular software enhances their accessibility for researchers.