scholarly journals Benchmark Assessment of Molecular Geometries and Energies from Small Molecule Force Fields

2020 ◽  
Author(s):  
Victoria T. Lim ◽  
David Mobley
Keyword(s):  
Force Field ◽  
Small Molecules ◽  
Gas Phase ◽  
Force Fields ◽  
Molecular Structures ◽  
Benchmark Assessment ◽  
Heavy Atoms ◽  
Chemical Groups ◽  
Optimized Geometries

<div>Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. </div><div>Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare six force fields: GAFF, GAFF2, MMFF94, MMFF94S, SMIRNOFF99Frosst, and the Open Force Field version 1.0 (Parsley) force field. On a dataset comprising over 26,000 molecular structures, we analyzed their force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. We show that most of these force fields are comparable in accuracy at reproducing gas-phase QM geometries and energetics, but that GAFF/GAFF2/Parsley do slightly better in reproducing QM energies and that MMFF94/MMFF94S perform slightly better in geometries. Parsley shows considerable improvement over its predecessor SMIRNOFF99Frosst, and we identify particular outlying chemical groups for further force field improvement.</div>

scholarly journals Benchmark Assessment of Molecular Geometries and Energies from Small Molecule Force Fields

2020 ◽  
Author(s):  
Victoria T. Lim ◽  
David F. Hahn ◽  
Gary Tresadern ◽  
Christopher I. Bayly ◽  
David Mobley
Keyword(s):  
Force Field ◽  
Small Molecules ◽  
Force Fields ◽  
Molecular Structures ◽  
Property Prediction ◽  
Benchmark Assessment ◽  
Heavy Atoms ◽  
Comparable Level ◽  
Optimized Geometries

<div>Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. </div><div>Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1 and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared these to reference quantum mechanical (QM) data. We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94s and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Our molecule set and results are available for other researchers to use in testing.</div>

scholarly journals Benchmark assessment of molecular geometries and energies from small molecule force fields

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1390
Author(s):  
Victoria T. Lim ◽  
David F. Hahn ◽  
Gary Tresadern ◽  
Christopher I. Bayly ◽  
David L. Mobley
Keyword(s):  
Force Field ◽  
Small Molecules ◽  
Force Fields ◽  
Molecular Structures ◽  
Benchmark Assessment ◽  
Heavy Atoms ◽  
Extensive Test ◽  
Better Than ◽  
Optimized Geometries

Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.

scholarly journals Benchmark Assessment of Molecular Geometries and Energies from Small Molecule Force Fields

2020 ◽  
Author(s):  
Victoria T. Lim ◽  
David F. Hahn ◽  
Gary Tresadern ◽  
Christopher I. Bayly ◽  
David Mobley
Keyword(s):  
Force Field ◽  
Small Molecules ◽  
Force Fields ◽  
Molecular Structures ◽  
Property Prediction ◽  
Benchmark Assessment ◽  
Heavy Atoms ◽  
Comparable Level ◽  
Optimized Geometries

<div>Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. </div><div>Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1 and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared these to reference quantum mechanical (QM) data. We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94s and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Our molecule set and results are available for other researchers to use in testing.</div>

scholarly journals Combining experimental and simulation data of molecular processes via augmented Markov models

2017 ◽  
Vol 114 (31) ◽  
pp. 8265-8270 ◽  
Author(s):  
Simon Olsson ◽  
Hao Wu ◽  
Fabian Paul ◽  
Cecilia Clementi ◽  
Frank Noé
Keyword(s):  
Force Field ◽  
Structural Changes ◽  
Markov Models ◽  
Force Fields ◽  
Divide And Conquer ◽  
Simulation Data ◽  
Wide Range ◽  
Simulation And Experiment ◽  
Kinetics Of

Accurate mechanistic description of structural changes in biomolecules is an increasingly important topic in structural and chemical biology. Markov models have emerged as a powerful way to approximate the molecular kinetics of large biomolecules while keeping full structural resolution in a divide-and-conquer fashion. However, the accuracy of these models is limited by that of the force fields used to generate the underlying molecular dynamics (MD) simulation data. Whereas the quality of classical MD force fields has improved significantly in recent years, remaining errors in the Boltzmann weights are still on the order of a few kT, which may lead to significant discrepancies when comparing to experimentally measured rates or state populations. Here we take the view that simulations using a sufficiently good force-field sample conformations that are valid but have inaccurate weights, yet these weights may be made accurate by incorporating experimental data a posteriori. To do so, we propose augmented Markov models (AMMs), an approach that combines concepts from probability theory and information theory to consistently treat systematic force-field error and statistical errors in simulation and experiment. Our results demonstrate that AMMs can reconcile conflicting results for protein mechanisms obtained by different force fields and correct for a wide range of stationary and dynamical observables even when only equilibrium measurements are incorporated into the estimation process. This approach constitutes a unique avenue to combine experiment and computation into integrative models of biomolecular structure and dynamics.

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.

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.

Comparison of STO-3G and 3-21G ab initio harmonic force fields for ethane, propane, dimethyl ether, and cyclobutane: effects of geometry and scaling on calculated frequencies, eigenvectors, and infrared absorption intensities

1988 ◽  
Vol 66 (5) ◽  
pp. 1318-1332 ◽  
Author(s):  
R. Anthony Shaw ◽  
Charles Ursenbach ◽  
Arvi Rauk ◽  
Hal Wieser
Keyword(s):  
Force Field ◽  
Ab Initio ◽  
Dimethyl Ether ◽  
Infrared Absorption ◽  
Force Fields ◽  
Vibrational Frequencies ◽  
Harmonic Force ◽  
Scaling Factors ◽  
Bond Lengths ◽  
Optimized Geometries

Ab initio harmonic force fields were calculated for ethane, propane, dimethyl ether, and cyclobutane at the STO-3G and 3-21G levels. The calculated frequencies, displacement eigenvectors, and calculated infrared absorption intensities were compared as they derive from force constants that were (i) unsealed; (ii) scaled to fit observed vibrational frequencies reported in the literature; (iii) evaluated at the optimized geometries; and (iv) evaluated at structures for which the bond lengths were corrected from the optimized geometries according to published procedures. A total of nine combinations of ab initio force field/reference geometry/G-matrix geometry were investigated for each of the four molecules. The ability of scaling factors as the only variables to predict vibrational parameters from STO-3G and 3-21G force fields was explored. Conditions were examined for which the scaling factors are satisfactorily transferable among different molecules.

Die Molekülstruktur des Vanadium-(N-chlorimid)-trichlorids, Cl3V=NCl, und des Vanadiumoxidtrichlorids, Cl3V = O, in der Gasphase / The Gas Phase Molecular Structure of Vanadium(N-Chlorimide)Trichloride, Cl3V=NCl, and Vanadium Oxide Trichloride, Cl3V=O

1975 ◽  
Vol 30 (3) ◽  
pp. 296-303 ◽  
Author(s):  
H. Oberhammer ◽  
J. Strähle
Keyword(s):  
Molecular Structure ◽  
Crystal Structure ◽  
Electron Diffraction ◽  
Force Field ◽  
Vanadium Oxide ◽  
Gas Phase ◽  
Infrared Spectra ◽  
Bond Distance ◽  
Molecular Structures ◽  
Gas Phase Electron Diffraction

The molecular structures of Cl3V = NCl and Cl3V = O were determined by gas-phase electron diffraction. For both molecules the rα0-structure was converted to restructure. In the case of Cl3V=O the necessary corrections were taken from the literature while for Cl3V=NCl an approximate force field was evaluated from the infrared spectra of the solid compound for calculating these corrections. The following rα0 parameters were derived for Cl3V = NCl: V = N = 1,651 (6), N-Cl = 1,597 (8), V - Cl = 2,138 (2), ⦓ ClVCl = 113,4° (0,3) and ⦓ VNCl = 169,7° (4,2). The most interesting result of this investigation is the structure of the V = N -Cl group which is almost linear and has a very short N -CI bond distance. Concerning the VNCl group the gas-phase results agree very well with the crystal structure. For vanadyl chloride the following rα0-values were obtained: V = 0 = 1,571 (4), V - Cl = 2,137 (1) and ⦓ ClVCl = 111,0° (0,1°). The error limits given in thousandth parts of an Angstrom or degrees are the threefold standard deviations of the least squares analysis.

Intrinsic Stacking Interactions of Natural and Artificial Nucleobases

2019 ◽  
Author(s):  
Drew P. Harding ◽  
Laura J. Kingsley ◽  
Glen Spraggon ◽  
Steven Wheeler
Keyword(s):  
Gas Phase ◽  
Electrostatic Interactions ◽  
Density Functional ◽  
Molecular Descriptors ◽  
Stacking Interactions ◽  
Interaction Energies ◽  
Functional Theory ◽  
Binding Partner ◽  
Heavy Atoms ◽  
Wide Range

The intrinsic (gas-phase) stacking energies of natural and artificial nucleobases were explored using density functional theory (DFT) and correlated ab initio methods. Ranking the stacking strength of natural nucleobase dimers revealed a preference in binding partner similar to that seen from experiments, namely G > C > A > T > U. Decomposition of these interaction energies using symmetry-adapted perturbation theory (SAPT) showed that these dispersion dominated interactions are modulated by electrostatics. Artificial nucleobases showed a similar stacking preference for natural nucleobases and were also modulated by electrostatic interactions. A robust predictive multivariate model was developed that quantitively predicts the maximum stacking interaction between natural and a wide range of artificial nucleobases using molecular descriptors based on computed electrostatic potentials (ESPs) and the number of heavy atoms. This model should find utility in designing artificial nucleobase analogs that exhibit stacking interactions comparable to those of natural nucleobases. Further analysis of the descriptors in this model unveil the origin of superior stacking abilities of certain nucleobases, including cytosine and guanine.

Sign in / Sign up

Export Citation Format

Share Document