Direct Derivation of van der Waals Force Field Parameters from Quantum Mechanical Interaction Energies

2003 ◽  
Vol 107 (35) ◽  
pp. 9601-9609 ◽  
Author(s):  
A. J. Bordner ◽  
C. N. Cavasotto ◽  
R. A. Abagyan
Keyword(s):  
Force Field ◽  
Van Der Waals ◽  
Van Der Waals Force ◽  
Quantum Mechanical ◽  
Interaction Energies ◽  
Mechanical Interaction ◽  
Direct Derivation ◽  
Force Field Parameters

Free energies of solvation with quantum mechanical interaction energies from classical mechanical simulations

1999 ◽  
Vol 110 (3) ◽  
pp. 1329-1337 ◽  
Author(s):  
Robert H. Wood ◽  
Eric M. Yezdimer ◽  
Shinichi Sakane ◽  
Jose A. Barriocanal ◽  
Douglas J. Doren
Keyword(s):  
Quantum Mechanical ◽  
Interaction Energies ◽  
Free Energies ◽  
Mechanical Interaction

scholarly journals Intermolecular Force Field Parameters Optimization for Computer Simulations of CH4in ZIF-8

2016 ◽  
Vol 2016 ◽  
pp. 1-6
Author(s):  
Phannika Kanthima ◽  
Pikul Puphasuk ◽  
Tawun Remsungnen
Keyword(s):  
Force Field ◽  
Md Simulations ◽  
Binding Energies ◽  
Parameters Optimization ◽  
Interaction Energies ◽  
Intermolecular Force ◽  
Amber Force Field ◽  
De Algorithm ◽  
Force Field Parameters ◽  
Structural Behaviors

The differential evolution (DE) algorithm is applied for obtaining the optimized intermolecular interaction parameters between CH4and 2-methylimidazolate ([C4N2H5]−) using quantum binding energies of CH4-[C4N2H5]−complexes. The initial parameters and their upper/lower bounds are obtained from the general AMBER force field. The DE optimized and the AMBER parameters are then used in the molecular dynamics (MD) simulations of CH4molecules in the frameworks of ZIF-8. The results show that the DE parameters are better for representing the quantum interaction energies than the AMBER parameters. The dynamical and structural behaviors obtained from MD simulations with both sets of parameters are also of notable differences.

Derivation of Force Field Parameters, and Force Field and Quantum Mechanical Studies of Layered α- and γ-Zirconium Phosphates

1999 ◽  
Vol 38 (19) ◽  
pp. 4249-4255 ◽  
Author(s):  
Giulio Alberti ◽  
Antonio Grassi ◽  
Giuseppe M. Lombardo ◽  
Giuseppe C. Pappalardo ◽  
Riccardo Vivani
Keyword(s):  
Force Field ◽  
Quantum Mechanical ◽  
Zirconium Phosphates ◽  
Force Field Parameters ◽  
Mechanical Studies

scholarly journals Development and Validation of the QUBE Protein Force Field

2019 ◽  
Author(s):  
Alice Allen ◽  
Michael J. Robertson ◽  
Michael C. Payne ◽  
Daniel Cole
Keyword(s):  
Force Field ◽  
Specific Protein ◽  
Biological Molecules ◽  
Quantum Mechanical ◽  
J Coupling ◽  
Force Field Parameters ◽  
Folded Proteins ◽  
Dynamics Simulations ◽  
Complete Protein ◽  
Development And Validation

<div><div><div><p>Molecular mechanics force field parameters for macromolecules, such as proteins, are traditionally fit to reproduce experimental properties of small molecules, and thus they neglect system-specific polarization. In this paper, we introduce a complete protein force field that is designed to be compatible with the QUantum mechanical BEspoke (QUBE) force field by deriving non-bonded parameters directly from the electron density of the specific protein under study. The main backbone and sidechain protein torsional parameters are re-derived in this work by fitting to quantum mechanical dihedral scans for compatibility with QUBE non-bonded parameters. Software is provided for the preparation of QUBE input files. The accuracy of the new force field, and the derived torsional parameters, are tested by comparing the conformational preferences of a range of peptides and proteins with experimental measurements. Accurate backbone and sidechain conformations are obtained in molecular dynamics simulations of dipeptides, with NMR J coupling errors comparable to the widely-used OPLS force field. In simulations of five folded proteins, the secondary structure is generally retained and the NMR J coupling errors are similar to standard transferable force fields, although some loss of the experimental structure is observed in certain regions of the proteins. With several avenues for further development, the use of system-specific non-bonded force field parameters is a promising approach for next-generation simulations of biological molecules.</p></div></div></div>

Introducing QUBE: Quantum Mechanical Bespoke Force Fields for Protein Simulations

2019 ◽  
Author(s):  
Alice Allen ◽  
Michael J. Robertson ◽  
Michael C. Payne ◽  
Daniel Cole
Keyword(s):  
Force Field ◽  
Force Fields ◽  
Specific Protein ◽  
Biological Molecules ◽  
Quantum Mechanical ◽  
Conformational Preferences ◽  
J Coupling ◽  
Force Field Parameters ◽  
Folded Proteins ◽  
Dynamics Simulations

<div><div><div><p>Molecular mechanics force field parameters for macromolecules, such as proteins, are traditionally fit to reproduce experimental properties of small molecules, and thus they neglect system-specific polarization. In this paper, we introduce a complete QUantum mechanical BEspoke (QUBE) protein force field, which derives non-bonded parameters directly from the electron density of the specific protein under study. The main backbone and sidechain protein torsional parameters are re-derived in this work by fitting to quantum mechanical dihedral scans for compatibibility with QUBE non-bonded parameters. Software is provided for the preparation of QUBE input files. The accuracy of the new force field, and the derived torsional parameters, are tested by comparing the conformational preferences of a range of peptides and proteins with experimental measurements. Accurate backbone and sidechain conformations are obtained in molecular dynamics simulations of dipeptides, with NMR J coupling errors comparable to the widely-used OPLS force field. In simulations of five folded proteins, the secondary structure is generally retained and the NMR J coupling errors are similar to standard transferable force fields, although some loss of the experimental structure is observed in certain regions of the proteins. Overall, with several avenues for further development, the use of system-specific non-bonded force field parameters is a promising approach for next-generation simulations of biological molecules.</p></div></div></div>

Development and Validation of the QUBE Protein Force Field

2019 ◽  
Author(s):  
Alice Allen ◽  
Michael J. Robertson ◽  
Michael C. Payne ◽  
Daniel Cole
Keyword(s):  
Force Field ◽  
Specific Protein ◽  
Biological Molecules ◽  
Quantum Mechanical ◽  
J Coupling ◽  
Force Field Parameters ◽  
Folded Proteins ◽  
Dynamics Simulations ◽  
Complete Protein ◽  
Development And Validation

<div><div><div><p>Molecular mechanics force field parameters for macromolecules, such as proteins, are traditionally fit to reproduce experimental properties of small molecules, and thus they neglect system-specific polarization. In this paper, we introduce a complete protein force field that is designed to be compatible with the QUantum mechanical BEspoke (QUBE) force field by deriving non-bonded parameters directly from the electron density of the specific protein under study. The main backbone and sidechain protein torsional parameters are re-derived in this work by fitting to quantum mechanical dihedral scans for compatibility with QUBE non-bonded parameters. Software is provided for the preparation of QUBE input files. The accuracy of the new force field, and the derived torsional parameters, are tested by comparing the conformational preferences of a range of peptides and proteins with experimental measurements. Accurate backbone and sidechain conformations are obtained in molecular dynamics simulations of dipeptides, with NMR J coupling errors comparable to the widely-used OPLS force field. In simulations of five folded proteins, the secondary structure is generally retained and the NMR J coupling errors are similar to standard transferable force fields, although some loss of the experimental structure is observed in certain regions of the proteins. With several avenues for further development, the use of system-specific non-bonded force field parameters is a promising approach for next-generation simulations of biological molecules.</p></div></div></div>

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