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>

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>

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>

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>

scholarly journals Empirical optimization of molecular simulation force fields by Bayesian inference

2021 ◽  
Vol 94 (12) ◽  
Author(s):  
Jürgen Köfinger ◽  
Gerhard Hummer
Keyword(s):  
Bayesian Inference ◽  
Force Field ◽  
Force Fields ◽  
Chem Phys ◽  
Exascale Computing ◽  
Wide Range ◽  
Force Field Parameters ◽  
Dynamics Simulations ◽  
High Level ◽  
Predictor Corrector

Abstract The demands on the accuracy of force fields for classical molecular dynamics simulations are steadily growing as larger and more complex systems are studied over longer times. One way to meet these growing demands is to hand over the learning of force fields and their parameters to machines in a systematic (semi)automatic manner. Doing so, we can take full advantage of exascale computing, the increasing availability of experimental data, and advances in quantum mechanical computations and the calculation of experimental observables from molecular ensembles. Here, we discuss and illustrate the challenges one faces in this endeavor and explore a way forward by adapting the Bayesian inference of ensembles (BioEn) method [Hummer and Köfinger, J. Chem. Phys. (2015)] for force field parameterization. In the Bayesian inference of force fields (BioFF) method developed here, the optimization problem is regularized by a simplified prior on the force field parameters and an entropic prior acting on the ensemble. The latter compensates for the unavoidable over simplifications in the parameter prior. We determine optimal force field parameters using an iterative predictor–corrector approach, in which we run simulations, determine the reference ensemble using the weighted histogram analysis method (WHAM), and update the force field according to the BioFF posterior. We illustrate this approach for a simple polymer model, using the distance between two labeled sites as the experimental observable. By systematically resolving force field issues, instead of just reweighting a structural ensemble, the BioFF corrections extend to observables not included in ensemble reweighting. We envision future force field optimization as a formalized, systematic, and (semi)automatic machine-learning effort that incorporates a wide range of data from experiment and high-level quantum chemical calculations, and takes advantage of exascale computing resources. Graphic abstract

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>

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

Derivation of Class II Force Fields. 7. Nonbonded Force Field Parameters for Organic Compounds

1999 ◽  
Vol 103 (33) ◽  
pp. 6998-7014 ◽  
Author(s):  
Carl S. Ewig ◽  
Thomas S. Thacher ◽  
Arnold T. Hagler
Keyword(s):  
Force Field ◽  
Organic Compounds ◽  
Force Fields ◽  
Class Ii ◽  
Force Field Parameters

The Future

1992 ◽  
Author(s):  
John A. Tossell ◽  
David J. Vaughan
Keyword(s):  
Ab Initio ◽  
Quantum Chemical ◽  
Force Fields ◽  
Structural Characteristics ◽  
Future Research ◽  
Quantum Mechanical ◽  
Bond Lengths ◽  
Hartree Fock ◽  
Qualitative Level ◽  
Dynamics Simulations

In this final chapter, an attempt is made to provide an overview of the capabilities of quantum-mechanical methods at the present time, and to highlight the needs for future development and possible future applications of these methods, particularly in areas related to mineral structures, energetics, and spectroscopy. There is also a brief account of some new areas of application, specific directions for future research, and possible developments in the perception and use of quantum-mechanical approaches. The book ends with an epilog on the overall role of “theoretical geochemistry” in the earth and environmental sciences. The local structural characteristics of minerals such as Mg2SiO4, which contain only main-group elements, are reasonably well reproduced by ab initio Hartree-Fock-Roothaan (SCF) cluster calculations at the mediumbasis- set level. Calculations incorporating configuration interaction will inevitably follow and probably lead to somewhat better agreement with experiment. The most pressing needs in this area of study are for the development of systematic procedures for cluster selection and embedding, for a greater understanding of the results at a qualitative level, and for more widespread efficient application of the quantum-chemical results currently available. In the last area, substantial progress has already been made by Lasaga and Gibbs (1987), Sanders et al. (1984), Tsuneyuki et al. (1988), and others, who have used ab initio calculations to generate theoretical force fields which can then be used in molecular-dynamics simulations. If the characteristics of the resultant force fields can be understood at a first-principles level, then it may be possible to understand details of the simulated structures at the same level. Unfortunately, as regards a greater qualitative understanding of the quantum-mechanical calculations, little progress has been made. Rather old qualitative theories describe some aspects of bond-angle variation (Tossell, 1986), but no general model to interpret variations in bond lengths has been developed within either chemistry or geochemistry beyond the model of additive atomic (Slater) or ionic (Shannon and Prewitt) radii. Indeed, global theories of bond-length variations within an ab initio framework seem to be nonexistent. Nonetheless, quantum-chemical studies have shown the presence of intriguing systematics in bond lengths (Gibbs et al., 1987), which had been already noted empirically.

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