Optimization of Empirical Force Fields by Parameter Space Mapping: A Single-Step Perturbation Approach

Stroet, Martin; Koziara, Katarzyna B.; Malde, Alpeshkumar K.; Mark, Alan E.

doi:10.1021/acs.jctc.7b00800

Cited by 32 publications

(52 citation statements)

References 54 publications

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“…This included a total of 773 molecules for which experimental data in water (DG water ) was available and 218 molecules for which experimental data was available in either hexane (DG hexane ) or a surrogate apolar solvent (pentane, cyclohexane, heptane, octane, nonane, decane, undecane, dodecane, pentadecane, hexadecane). 38 The calculations were performed using the automated thermodynamic integration protocol described above. A complete list of all molecules, their ATB repository identifiers, the calculated values of (DG water ) and (DG hexane ) together with the collated experimental data is provided as Supporting in an alkane solvent than the value listed for hexane.…”

Section: Comparison Against All Available Datamentioning

confidence: 99%

Automated Topology Builder Version 3.0: Prediction of Solvation Free Enthalpies in Water and Hexane

Stroet

Caron

Visscher

et al. 2018

J. Chem. Theory Comput.

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378

230

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The ability of atomic interaction parameters generated using the Automated Topology Builder and Repository version 3.0 (ATB3.0) to predict experimental hydration free enthalpies (DG water) and solvation free enthalpies in the apolar solvent hexane (DG hexane) is presented. For a validation set of 685 molecules the average unsigned error (AUE) between DG water values calculated using the ATB3.0 and experiment is 3.9 kJ•mol-1. The slope of the line of best fit is 1.00, the intercept-1.0 kJ•mol-1 and the R 2 0.90. For the more restricted set of 239 molecules used to validate OPLS3 (J. Chem. Theory Comput. 2016, 12, 281-296.) the AUE using the ATB3.0 is just 2.7 kJ•mol-1 and the R 2 0.93. A roadmap for further improvement of the ATB parameters is presented together with a discussion of the challenges of validating force fields against the available experimental data.

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Section: Comparison Against All Available Datamentioning

confidence: 99%

Automated Topology Builder Version 3.0: Prediction of Solvation Free Enthalpies in Water and Hexane

Stroet

Caron

Visscher

et al. 2018

J. Chem. Theory Comput.

Self Cite

378

230

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“…While such an assignment would be difficult to perform manually it has to be ensured that automatically assigned parameters are consistent with the macromolecular force field applied to the other components of the system such that a combination of quantum chemical calculations with some heuristic rules will most likely deliver the most appropriate results. This will remain an on‐going challenge for force field development as the complexity and heterogeneity of systems studied by molecular simulation increases .…”

Section: Some Aspects Of Force Field Validationmentioning

confidence: 99%

Insights into Noncovalent Binding Obtained from Molecular Dynamics Simulations

Baz

Gebhardt

Kraus

et al. 2018

Chemie Ingenieur Technik

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The key to nanoscale control of physical, chemical, and biological processes lies in well‐founded models of noncovalent binding. Atomistic simulations probe the free‐energy surface underlying molecular assembly processes in solution. Two examples of noncovalent binding studied by molecular dynamics simulations are discussed, the dimerization of a water‐soluble perylene bisimide derivative in aqueous solution with a focus on the influence of solvent composition on the aggregation strength and the binding of 1‐butanol to α‐cyclodextrin at infinite dilution with the focus on the determination of method‐independent binding free energies.

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“…This included 773 molecules for which experimental data in water (DG water ) was available and 218 molecules for which experimental data was available in either hexane (DG hexane ) or a surrogate apolar solvent (pentane, cyclohexane, heptane, octane, nonane, decane, undecane, dodecane, pentadecane, hexadecane). 38 The calculations were performed using the automated thermodynamic integration protocol described above. A complete list of all molecules, their ATB repository identifiers, the calculated values of (DG water ) and (DG hexane ) together with the collated experimental data is provided as Supporting Information.…”

Section: Resultsmentioning

confidence: 99%

“…The experimental solvation free enthalpy data used in this study was obtained by aggregating 38 for details and for the validation of this approach. All experimental reference data that has been collated to date for molecules used in this work is provided as Supporting Information.…”

Section: Experimental Datamentioning

confidence: 99%

“…57 As noted above, the solvation free enthalpies of many compounds are highly correlated in a range of alkane solvents. 38 For example, the variation in the experimental solvation free enthalpy of phenol in hexane (-23.0 kJ·mol -1 ) and seven alternative alkane solvents (pentane, cyclohexane, heptane, octane, nonane, decane, hexadecane) is only 1.5 kJ·mol -1 . Similarly, the variation between benzaldehyde in hexane (-23.1 kJ·mol -1 ) and three alternative alkane solvents (cyclohexane, heptane, hexadecane) is only 0.75 kJ·mol -1 .…”

Section: The Atb30 Apolar Validation Setmentioning

confidence: 99%

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Improving automated force-field parametrisation for molecular simulation: a graph approach

Caron¹

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Classical molecular dynamics (MD) techniques offer atomic-level insights into a wide range of physical systems, including biomolecular systems. They rely on empirical, parametrised equations (force fields) to describe the interaction potential between the constituents of the systems. Their predictive ability is critically dependent on the accuracy of these parameters. Highly optimised, well-validated parameters have been developed for many important biomolecules such as proteins, lipids and sugars. However, developing parameters for small molecules such as drugs is very challenging given the scale of chemical space. For instance, the ChEMBL database contains in excess of 1.7 million bioactive compounds. Although stand-alone software (e.g antechamber 1, 2 ) or web-servers (e.g. the Automated Topology Builder, 3-5 atb.uq.edu.au) have been developed to assign parameters to drug-like molecules, they usually rely on fitting to quantum-mechanical (QM) calculations in combination with sets of empirical rules, and their applicability is limited to small molecules (less than a few tens of atoms). Automated parametrisation of large, bio-active, and often biologically relevant molecules is still impractical and greatly limits the predictive power of simulations involving such compounds.This thesis focuses on the use of graph-based approaches to develop new automated parametrisation paradigms which can exploit large data sets to simultaneously develop and assign force field parameters.An efficient Linear Programming method for deducing the charge state and bond order, based only on the molecular connectivity and chemical elements of its atoms, was developed. The algorithm was validated against the MMFF94 dataset containing 761 molecules with manually assigned bond orders. The approach was extended to i) cap molecular fragments (molecules having some atoms with incomplete valences) and ii) enumerate tautomeric (protomerism) forms of molecules. These extensions can be used for solving various problems related to drug-design and fragment-based empirical force-field parametrisation and can be applied to molecules containing hundreds of atoms.A new method for predicting chemically equivalent atoms in a molecule was developed. This method relies on identifying automorphisms of the molecule. False positives (non-chemically equivalent atoms treated as equivalent by the previous approach) were addressed by implementing a series of exceptions for double bonds, non-invertable rings and stereotopic atoms, respectively. This method was used to symmetrise force-field terms between chemically equivalent atoms in the Automated Topology Builder (ATB, 3-5 atb.uq.edu.au).Building on these chemical equivalence relationships, a representation-independent, symmetrycorrected distance metric was developed (Blind RMSD). This facilitates the alignment of molecules with identical chemical graphs but different atom naming and indexing arbitrarily assigned. This approach was extended to fragments (i.e. subset of atoms in a molecules) for mapping graph n...

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Optimization of Empirical Force Fields by Parameter Space Mapping: A Single-Step Perturbation Approach

Cited by 32 publications

References 54 publications

Automated Topology Builder Version 3.0: Prediction of Solvation Free Enthalpies in Water and Hexane

Automated Topology Builder Version 3.0: Prediction of Solvation Free Enthalpies in Water and Hexane

Insights into Noncovalent Binding Obtained from Molecular Dynamics Simulations

Improving automated force-field parametrisation for molecular simulation: a graph approach

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