scholarly journals Exploration and Validation of Force Field Design Protocols through QM-to-MM Mapping

2021 ◽  
Author(s):  
Chris Ringrose ◽  
Joshua Horton ◽  
Lee-Ping Wang ◽  
Daniel Cole
Keyword(s):  
Quantum Mechanics ◽  
Force Field ◽  
Molecular Mechanics ◽  
Organic Molecule ◽  
Force Fields ◽  
Small Organic Molecule ◽  
Field Development ◽  
Force Field Development ◽  
Fitting Parameters ◽  
Made In

The scale of the parameter optimisation problem in traditional molecular mechanics force field construction means that design of a new force field is a long process, and sub-optimal choices made in the early stages can persist for many generations of the force field. We hypothesise that careful use of quantum mechanics to inform molecular mechanics parameter derivation (QM-to-MM mapping) should be used to significantly reduce the number of parameters that require fitting to experiment and increase the pace of force field development. Here, we design a collection of 15 new protocols for small, organic molecule force field design, and test their accuracy against experimental liquid properties. Our best performing model has only seven fitting parameters, yet achieves mean unsigned errors of just 0.031 g/cm3 and 0.69 kcal/mol in liquid densities and heats of vaporisation, compared to experiment. The software required to derive the designed force fields is freely available at https://github.com/qubekit/QUBEKit.

Molecular mechanics force-field development for amino acid zwitterions

2003 ◽  
Vol 24 (1) ◽  
pp. 111-128 ◽  
Author(s):  
K. N. Kirschner ◽  
A. H. Lewin ◽  
J. P. Bowen
Keyword(s):  
Amino Acid ◽  
Force Field ◽  
Molecular Mechanics ◽  
Field Development ◽  
Force Field Development

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.

Molecular Mechanics Force Field Development and Applications

ChemInform ◽  
2003 ◽  
Vol 34 (19) ◽  
Author(s):  
Pat Metthe Todebush ◽  
J. Phillip Bowen
Keyword(s):  
Force Field ◽  
Molecular Mechanics ◽  
Field Development ◽  
Force Field Development

Molecular mechanics (MM4) force field development for phosphine and its alkyl derivatives

Chirality ◽  
2002 ◽  
Vol 14 (2-3) ◽  
pp. 220-231 ◽  
Author(s):  
Patricia Metthe Todebush ◽  
Guyan Liang ◽  
J. Phillip Bowen
Keyword(s):  
Force Field ◽  
Molecular Mechanics ◽  
Field Development ◽  
Force Field Development ◽  
Alkyl Derivatives

scholarly journals Force Field Development of β-lactam Class Antibiotics

2020 ◽  
Vol 5 (Spring 2020) ◽  
Author(s):  
Trevor Heinzmann
Keyword(s):  
Force Field ◽  
Force Fields ◽  
Molecular System ◽  
Equations Of Motion ◽  
Computational Cost ◽  
Potential Energy Function ◽  
Md Simulations ◽  
Field Development ◽  
Force Field Development ◽  
Low Computational Cost

Molecular dynamics (MD) simulation is a computational chemistry technique used to observe how a molecular system behaves as time passes. MD is based on solving Newton’s equations of motion. This requires the use of force fields to describe the potential energy function of each different molecule type in molecular system. In order to develop a force field, charges, bonds, angles, and dihedrals must be parameterized to fit quantum mechanics (QM) data. By basing the force field on QM data, MD simulations have higher accuracy while still using the low computational cost of molecular mechanics. This project focuses on developing well-fit force fields for β-lactam class antibiotics for future MD simulations. Full antibiotics are too large of a molecule to parameterize from scratch, so instead we broke them down into fragments. Smaller molecule fragments allow less terms to be optimized which greatly simplifies force field development. By the transferable nature of parameters in CHARMM force fields, the fragment parameters can be transferred to connecting molecules. Due to this, we can build up larger organic molecule force fields piece by piece.In this work, we developed CHARMM force fields for cephalothin, cefotaxime, ceftazidime, and aztreonam.

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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