Hydration of platinum(II) complexes: a molecular mechanics study using atom-based force-field parameters

2000 ◽  
Vol 104 (3-4) ◽  
pp. 247-251 ◽  
Author(s):  
Jacqueline Langlet ◽  
Jacqueline Berg�s ◽  
Jacqueline Caillet ◽  
Jiri Kozelka
Keyword(s):  
Force Field ◽  
Molecular Mechanics ◽  
Force Field Parameters

Molecular Mechanics (MM3*) Force Field Parameters for Calculations on Palladium Olefin Complexes with Phosphorus Ligands

1999 ◽  
Vol 18 (22) ◽  
pp. 4574-4583 ◽  
Author(s):  
Helena Hagelin ◽  
Mats Svensson ◽  
Björn Åkermark ◽  
Per-Ola Norrby
Keyword(s):  
Force Field ◽  
Molecular Mechanics ◽  
Phosphorus Ligands ◽  
Mm3 Force Field ◽  
Force Field Parameters

A new spectroscopic molecular mechanics force field. Parameters for proteins

1995 ◽  
Vol 102 (21) ◽  
pp. 8586-8605 ◽  
Author(s):  
Philippe Derreumaux ◽  
Gérard Vergoten
Keyword(s):  
Force Field ◽  
Molecular Mechanics ◽  
Force Field Parameters

Derivation of a molecular mechanics force field for cholesterol

2004 ◽  
Vol 76 (1) ◽  
pp. 189-196 ◽  
Author(s):  
Zoe Cournia ◽  
A. C. Vaiana ◽  
G. M. Ullmann ◽  
J. C. Smith
Keyword(s):  
Force Field ◽  
Molecular Mechanics ◽  
Quantum Chemical ◽  
Reference Data ◽  
Rhodamine 6G ◽  
Normal Modes ◽  
Frequency Matching ◽  
Automated Method ◽  
Force Field Parameters ◽  
Different Levels

As a necessary step toward realistic cholesterol:biomembrane simulations, we have derived CHARMM molecular mechanics force-field parameters for cholesterol. For the parametrization we use an automated method that involves fitting the molecular mechanics potential to both vibrational frequencies and eigenvector projections derived from quantum chemical calculations. Results for another polycyclic molecule, rhodamine 6G, are also given. The usefulness of the method is thus demonstrated by the use of reference data from two molecules at different levels of theory. The frequency-matching plots for both cholesterol and rhodamine 6G show overall agreement between the CHARMM and quantum chemical normal modes, with frequency matching for both molecules within the error range found in previous benchmark studies.

QUBEKit: Automating the Derivation of Force Field Parameters from Quantum Mechanics

2019 ◽  
Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole
Keyword(s):  
Quantum Mechanics ◽  
Force Field ◽  
Organic Molecules ◽  
Force Fields ◽  
Liquid Density ◽  
Small Organic Molecules ◽  
Automated Generation ◽  
Energy Of Hydration ◽  
Novel Method ◽  
Force Field Parameters

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>

QUBEKit: Automating the Derivation of Force Field Parameters from Quantum Mechanics

2019 ◽  
Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole
Keyword(s):  
Quantum Mechanics ◽  
Force Field ◽  
Organic Molecules ◽  
Force Fields ◽  
Liquid Density ◽  
Small Organic Molecules ◽  
Automated Generation ◽  
Energy Of Hydration ◽  
Novel Method ◽  
Force Field Parameters

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>

Specific force field parameters determination for the hybridab initioQM/MM LSCF method

2002 ◽  
Vol 23 (6) ◽  
pp. 610-624 ◽  
Author(s):  
Nicolas Ferré ◽  
Xavier Assfeld ◽  
Jean-Louis Rivail
Keyword(s):  
Force Field ◽  
Specific Force ◽  
Force Field Parameters
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