Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field

2021 ◽  
Vol 17 (4) ◽  
pp. 2323-2341
Author(s):  
Rae A. Corrigan ◽  
Guowei Qi ◽  
Andrew C. Thiel ◽  
Jack R. Lynn ◽  
Brandon D. Walker ◽  
...  
Keyword(s):  
Force Field ◽  
Implicit Solvents ◽  
Amoeba Force Field

scholarly journals Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field

2020 ◽  
Author(s):  
Rae Corrigan ◽  
Guowei Qi ◽  
Andrew Thiel ◽  
Jack Lynn ◽  
Brandon Walker ◽  
...  
Keyword(s):  
Force Field ◽  
Protein Design ◽  
Numerical Solutions ◽  
Target Function ◽  
Model Parameters ◽  
Implicit Solvent ◽  
Electrostatic Model ◽  
Implicit Solvents ◽  
Poisson Boltzmann Equation ◽  
Amoeba Force Field

Computational protein design, ab initio protein/RNA folding, and protein-ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the Poisson-Boltzmann equation (PBE), the domain-decomposition Conductor-like Screening Model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatic models are combined with a nonpolar estimator based on novel cavitation and dispersion terms. Electrostatic model parameters are numerically optimized using a least squares style target function based on a library of 103 small molecule solvation free energy differences. Mean signed errors for the APBS, ddCOSMO, and GK models are 0.05, 0.00, and 0.00 kcal/mol, respectively, while the mean unsigned errors are 0.70, 0.63, and 0.51 kcal/mol, respectively. Validation of the electrostatic response of the resulting implicit solvents, which are available in the Tinker (or Tinker-HP), OpenMM, and Force Field X software packages, is based on comparisons to explicit solvent simulations for a series of proteins and nucleic acids. Overall, the emergence of performative implicit solvent models for polarizable force fields will open the door to their use for folding and design applications.<br>

scholarly journals Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field

2020 ◽  
Author(s):  
Rae Corrigan ◽  
Guowei Qi ◽  
Andrew Thiel ◽  
Jack Lynn ◽  
Brandon Walker ◽  
...  
Keyword(s):  
Force Field ◽  
Protein Design ◽  
Numerical Solutions ◽  
Target Function ◽  
Model Parameters ◽  
Implicit Solvent ◽  
Electrostatic Model ◽  
Implicit Solvents ◽  
Poisson Boltzmann Equation ◽  
Amoeba Force Field

Computational protein design, ab initio protein/RNA folding, and protein-ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the Poisson-Boltzmann equation (PBE), the domain-decomposition Conductor-like Screening Model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatic models are combined with a nonpolar estimator based on novel cavitation and dispersion terms. Electrostatic model parameters are numerically optimized using a least squares style target function based on a library of 103 small molecule solvation free energy differences. Mean signed errors for the APBS, ddCOSMO, and GK models are 0.05, 0.00, and 0.00 kcal/mol, respectively, while the mean unsigned errors are 0.70, 0.63, and 0.51 kcal/mol, respectively. Validation of the electrostatic response of the resulting implicit solvents, which are available in the Tinker (or Tinker-HP), OpenMM, and Force Field X software packages, is based on comparisons to explicit solvent simulations for a series of proteins and nucleic acids. Overall, the emergence of performative implicit solvent models for polarizable force fields will open the door to their use for folding and design applications.<br>

scholarly journals Polarizable Atomic Multipole-Based AMOEBA Force Field for Proteins

2013 ◽  
Vol 9 (9) ◽  
pp. 4046-4063 ◽  
Author(s):  
Yue Shi ◽  
Zhen Xia ◽  
Jiajing Zhang ◽  
Robert Best ◽  
Chuanjie Wu ◽  
...  
Keyword(s):  
Force Field ◽  
Amoeba Force Field

AMOEBA force field parameterization of the azabenzenes

2014 ◽  
Vol 134 (1) ◽  
Author(s):  
David Semrouni ◽  
Christopher J. Cramer ◽  
Laura Gagliardi
Keyword(s):  
Force Field ◽  
Force Field Parameterization ◽  
Amoeba Force Field

scholarly journals Polarizable Amoeba Force Field Metadynamics with Minimization Predicts Missing Protein Loops

2017 ◽  
Vol 112 (3) ◽  
pp. 55a
Author(s):  
Armin Avdic ◽  
Mallory R. Tollefson ◽  
Nicole Tatro ◽  
Stephen D. LuCore ◽  
Jacob M. Litman ◽  
...  
Keyword(s):  
Force Field ◽  
Amoeba Force Field ◽  
Protein Loops

Evaluation of the AMOEBA force field for simulating metal halide perovskites in the solid state and in solution

2020 ◽  
Vol 152 (2) ◽  
pp. 024117
Author(s):  
P. V. G. M. Rathnayake ◽  
Stefano Bernardi ◽  
Asaph Widmer-Cooper
Keyword(s):  
Solid State ◽  
Force Field ◽  
Metal Halide ◽  
Halide Perovskites ◽  
Amoeba Force Field
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