Molecular Force Field Development for Aqueous Electrolytes: 1. Incorporating Appropriate Experimental Data and the Inadequacy of Simple Electrolyte Force Fields Based on Lennard-Jones and Point Charge Interactions with Lorentz–Berthelot Rules

2013 ◽  
Vol 9 (11) ◽  
pp. 5076-5085 ◽  
Author(s):  
Filip Moučka ◽  
Ivo Nezbeda ◽  
William R. Smith
Keyword(s):  
Experimental Data ◽  
Force Field ◽  
Point Charge ◽  
Force Fields ◽  
Aqueous Electrolytes ◽  
Field Development ◽  
Force Field Development ◽  
Lennard Jones ◽  
Molecular Force ◽  
Molecular Force Field

scholarly journals Data-driven analysis of the number of Lennard-Jones types needed in a force field

2020 ◽  
Author(s):  
Michael Schauperl ◽  
Sophie Kantonen ◽  
Lee-Ping Wang ◽  
Michael Gilson
Keyword(s):  
Force Field ◽  
Predictive Accuracy ◽  
Force Fields ◽  
Global Optimum ◽  
Data Driven ◽  
Organic Liquids ◽  
Field Development ◽  
Force Field Development ◽  
Lennard Jones ◽  
Simple Sets

<p>We optimized force fields with smaller and larger sets of chemically motivated Lennard-Jones types against the experimental properties of organic liquids. Surprisingly, we obtained results as good as or better than those from much more complex typing schemes from exceedingly simple sets of LJ types; e.g. a model with only two types of hydrogen and only one type apiece for carbon, nitrogen and oxygen.</p><p>The results justify sharply limiting the number of parameters to be optimized in future force field development work, thus reducing the risks of overfitting and the difficulties of reaching a global optimum in the multidimensional parameter space. They thus increase our chances of arriving at well-optimized force fields that will improve predictive accuracy, with applications in biomolecular modeling and computer-aided drug design. The results also prove the feasibility and value of a rigorous, data-driven approach to advancing the science of force field development.</p>

scholarly journals Data-driven analysis of the number of Lennard-Jones types needed in a force field

2020 ◽  
Author(s):  
Michael Schauperl ◽  
Sophie Kantonen ◽  
Lee-Ping Wang ◽  
Michael Gilson
Keyword(s):  
Force Field ◽  
Predictive Accuracy ◽  
Force Fields ◽  
Global Optimum ◽  
Data Driven ◽  
Organic Liquids ◽  
Field Development ◽  
Force Field Development ◽  
Lennard Jones ◽  
Simple Sets

<p>We optimized force fields with smaller and larger sets of chemically motivated Lennard-Jones types against the experimental properties of organic liquids. Surprisingly, we obtained results as good as or better than those from much more complex typing schemes from exceedingly simple sets of LJ types; e.g. a model with only two types of hydrogen and only one type apiece for carbon, nitrogen and oxygen.</p><p>The results justify sharply limiting the number of parameters to be optimized in future force field development work, thus reducing the risks of overfitting and the difficulties of reaching a global optimum in the multidimensional parameter space. They thus increase our chances of arriving at well-optimized force fields that will improve predictive accuracy, with applications in biomolecular modeling and computer-aided drug design. The results also prove the feasibility and value of a rigorous, data-driven approach to advancing the science of force field development.</p>

scholarly journals Improving Small Molecule Force Fields by Identifying and Characterizing Small Molecules with Inconsistent Parameters

2020 ◽  
Author(s):  
Jordan Ehrman ◽  
Victoria T. Lim ◽  
Caitlin C. Bannan ◽  
Nam Thi ◽  
Daisy Kyu ◽  
...  
Keyword(s):  
Force Field ◽  
Small Molecules ◽  
Small Molecule ◽  
Force Fields ◽  
Use Of Force ◽  
Chemical System ◽  
Simulation Methods ◽  
Field Development ◽  
Force Field Development ◽  
Atomic Coordinates

Many molecular simulation methods use force fields to help model and simulate molecules and their behavior in various environments. Force fields are sets of functions and parameters used to calculate the potential energy of a chemical system as a function of the atomic coordinates. Despite the widespread use of force fields, their inadequacies are often thought to contribute to systematic errors in molecular simulations. Furthermore, different force fields tend to give varying results on the same systems with the same simulation settings. Here, we present a pipeline for comparing the geometries of small molecule conformers. We aimed to identify molecules or chemistries that are particularly informative for future force field development because they display inconsistencies between force fields. We applied our pipeline to a subset of the eMolecules database, and highlighted molecules that appear to be parameterized inconsistently across different force fields. We then identified over-represented functional groups in these molecule sets. The molecules and moieties identified by this pipeline may be particularly helpful for future force field parameterization.

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