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

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 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 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.

Visualizing 3D Molecular Structures Using an Augmented Reality App

2019 ◽  
Author(s):  
Kristina Eriksen ◽  
Bjarne Nielsen ◽  
Michael Pittelkow
Keyword(s):  
Augmented Reality ◽  
Small Molecules ◽  
Computer Modelling ◽  
Simple Procedure ◽  
3D Structure ◽  
Molecular Structures ◽  
Free Software ◽  
Programming Skills ◽  
2D Space ◽  
Made In

<p>We present a simple procedure to make an augmented reality app to visualize any 3D chemical model. The molecular structure may be based on data from crystallographic data or from computer modelling. This guide is made in such a way, that no programming skills are needed and the procedure uses free software and is a way to visualize 3D structures that are normally difficult to comprehend in the 2D space of paper. The process can be applied to make 3D representation of any 2D object, and we envisage the app to be useful when visualizing simple stereochemical problems, when presenting a complex 3D structure on a poster presentation or even in audio-visual presentations. The method works for all molecules including small molecules, supramolecular structures, MOFs and biomacromolecules.</p>

Driving Torsion Scans with Wavefront Propagation

2020 ◽  
Author(s):  
Yudong Qiu ◽  
Daniel Smith ◽  
Chaya Stern ◽  
mudong feng ◽  
Lee-Ping Wang
Keyword(s):  
Potential Energy ◽  
Force Field ◽  
Degrees Of Freedom ◽  
Computational Cost ◽  
Initial Guess ◽  
Field Development ◽  
Force Field Development ◽  
Wavefront Propagation ◽  
Open Source Software Package

<div>The parameterization of torsional / dihedral angle potential energy terms is a crucial part of developing molecular mechanics force fields.</div><div>Quantum mechanical (QM) methods are often used to provide samples of the potential energy surface (PES) for fitting the empirical parameters in these force field terms.</div><div>To ensure that the sampled molecular configurations are thermodynamically feasible, constrained QM geometry optimizations are typically carried out, which relax the orthogonal degrees of freedom while fixing the target torsion angle(s) on a grid of values.</div><div>However, the quality of results and computational cost are affected by various factors on a non-trivial PES, such as dependence on the chosen scan direction and the lack of efficient approaches to integrate results started from multiple initial guesses.</div><div>In this paper we propose a systematic and versatile workflow called \textit{TorsionDrive} to generate energy-minimized structures on a grid of torsion constraints by means of a recursive wavefront propagation algorithm, which resolves the deficiencies of conventional scanning approaches and generates higher quality QM data for force field development.</div><div>The capabilities of our method are presented for multi-dimensional scans and multiple initial guess structures, and an integration with the MolSSI QCArchive distributed computing ecosystem is described.</div><div>The method is implemented in an open-source software package that is compatible with many QM software packages and energy minimization codes.</div>

Hydration Free Energies of Organic Molecules in the FreeSolv Database Calculated with Polarized Atom In Molecules Atomic Charges and the GAFF Force Field.

2018 ◽  
Author(s):  
Maximiliano Riquelme ◽  
Alejandro Lara ◽  
David L. Mobley ◽  
Toon Vestraelen ◽  
Adelio R Matamala ◽  
...  
Keyword(s):  
Force Field ◽  
Functional Groups ◽  
Electrostatic Interactions ◽  
Organic Molecules ◽  
Force Fields ◽  
Chemical Elements ◽  
Atomic Charges ◽  
Free Energies ◽  
Molecular Systems ◽  
Solvent Model

<div>Computer simulations of bio-molecular systems often use force fields, which are combinations of simple empirical atom-based functions to describe the molecular interactions. Even though polarizable force fields give a more detailed description of intermolecular interactions, nonpolarizable force fields, developed several decades ago, are often still preferred because of their reduced computation cost. Electrostatic interactions play a major role in bio-molecular systems and are therein described by atomic point charges.</div><div>In this work, we address the performance of different atomic charges to reproduce experimental hydration free energies in the FreeSolv database in combination with the GAFF force field. Atomic charges were calculated by two atoms-in-molecules approaches, Hirshfeld-I and Minimal Basis Iterative Stockholder (MBIS). To account for polarization effects, the charges were derived from the solute's electron density computed with an implicit solvent model and the energy required to polarize the solute was added to the free energy cycle. The calculated hydration free energies were analyzed with an error model, revealing systematic errors associated with specific functional groups or chemical elements. The best agreement with the experimental data is observed for the MBIS atomic charge method, including the solvent polarization, with a root mean square error of 2.0 kcal mol<sup>-1</sup> for the 613 organic molecules studied. The largest deviation was observed for phosphor-containing molecules and the molecules with amide, ester and amine functional groups.</div>

Sign in / Sign up

Export Citation Format

Share Document