scholarly journals Structures of MERS‐CoV Macro Domain in Aqueous Solution with Dynamics: Impacts of Parallel Tempering Simulation Techniques and CHARMM36m and AMBER99SB Force Field Parameters

2021 ◽  
Author(s):  
Ibrahim Yagiz Akbayrak ◽  
Sule Irem Caglayan ◽  
Serdar Durdagi ◽  
Lukasz Kurgan ◽  
Vladimir N. Uversky ◽  
...  
Keyword(s):  
Aqueous Solution ◽  
Force Field ◽  
Parallel Tempering ◽  
Simulation Techniques ◽  
Macro Domain ◽  
Force Field Parameters

Secondary structure dependence of amyloid‐β(1–40) on simulation techniques and force field parameters

2021 ◽  
Vol 97 (5) ◽  
pp. 1100-1108
Author(s):  
Murat Caliskan ◽  
Sunay Y. Mandaci ◽  
Vladimir N. Uversky ◽  
Orkid Coskuner‐Weber
Keyword(s):  
Secondary Structure ◽  
Force Field ◽  
Amyloid Β ◽  
Structure Dependence ◽  
Simulation Techniques ◽  
Force Field Parameters

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>

Molecular Dynamics Study of Aqueous Solution of Polyethylene Oxide: Critical Test of Force Field Models

2013 ◽  
Vol 11 (4) ◽  
pp. 371-383 ◽  
Author(s):  
Yong-Lei Wang ◽  
Rochelle S. Lawrence ◽  
Zhong-Yuan Lu ◽  
Aatto Laaksonen
Keyword(s):  
Molecular Dynamics ◽  
Aqueous Solution ◽  
Force Field ◽  
Polyethylene Oxide ◽  
Critical Test

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

scholarly journals New CHARMM force field parameters for dehydrated amino acid residues, the key to lantibiotic molecular dynamics simulations

RSC Advances ◽  
2014 ◽  
Vol 4 (89) ◽  
pp. 48621-48631 ◽  
Author(s):  
Eleanor R. Turpin ◽  
Sam Mulholland ◽  
Andrew M. Teale ◽  
Boyan B. Bonev ◽  
Jonathan D. Hirst
Keyword(s):  
Molecular Dynamics ◽  
Amino Acid ◽  
Force Field ◽  
Molecular Dynamics Simulations ◽  
Amino Acid Residues ◽  
Charmm Force Field ◽  
Force Field Parameters ◽  
Dynamics Simulations

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
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