From 73bddb998d025802363be736b1a9d609819f79db Mon Sep 17 00:00:00 2001 From: bc118 Date: Sat, 24 Aug 2024 09:42:52 -0400 Subject: [PATCH 1/3] adds other ways to get FF or dihedral parameters --- paper/paper.bib | 66 +++++++++++++++++++++++++++++++++++++++++++++++++ paper/paper.md | 3 ++- 2 files changed, 68 insertions(+), 1 deletion(-) diff --git a/paper/paper.bib b/paper/paper.bib index ebccc26..1cdfa29 100644 --- a/paper/paper.bib +++ b/paper/paper.bib @@ -383,3 +383,69 @@ @article{Ganesh:2004 doi = {10.1021/jp048581s}, URL = {https://doi.org/10.1021/jp048581s}, } + +# Other dihedral fit methods and difficulties with fits +@article{Kania:2021, +author = {Kania, Adrian and Sarapata, Krzysztof and Gucwa, Michał and Wójcik-Augustyn, Anna}, +title = {Optimal Solution to the Torsional Coefficient Fitting Problem in Force Field Parametrization}, +journal = {The Journal of Physical Chemistry A}, +volume = {125}, +number = {12}, +pages = {2673-2681}, +year = {2021}, +doi = {10.1021/acs.jpca.0c10845}, +URL = {https://doi.org/10.1021/acs.jpca.0c10845} + +} + +# Other ML dihedral fit methods +@article{Friederich:2018, +author = {Friederich, Pascal and Konrad, Manuel and Strunk, Timo and Wenzel, Wolfgang}, +title = {Machine learning of correlated dihedral potentials for atomistic molecular force fields}, +journal = {Scientific Reports}, +volume = {8}, +issue = {1}, +pages = {2559}, +year = {2018}, +doi = {10.1038/s41598-018-21070-0}, +URL = {https://doi.org/10.1038/s41598-018-21070-0} +} + +# Other ML vibrational fit dihedral +@article{Vermeyen:2023, +author = {Vermeyen, Tom and Cunha, Ana and Bultinck, Patrick and Herrebout, Wouter}, +title = {Impact of conformation and intramolecular interactions on vibrational circular dichroism spectra identified with machine learning}, +journal = {Communications Chemistry}, +volume = {6}, +issue = {1}, +pages = {148}, +year = {2023}, +doi = {10.1038/s42004-023-00944-z}, +URL = {https://doi.org/10.1038/s42004-023-00944-z} +} + +# CHARMM FFTK using vibrational spectra +@article{Mayne:2013, +author = {Christopher G. Mayne and Jan Saam and Klaus Schulten and Emad Tajkhorshid and James C. Gumbart}, +title = {Rapid parameterization of small molecules using the Force Field Toolkit}, +journal = {Journal of Computational Chemistry}, +volume = {34}, +issue = {32}, +pages = {2757-2770}, +year = {2013}, +doi = {10.1002/jcc.23422}, +URL = {https://doi.org/10.1002/jcc.23422} +} + +# dihedral - bonded parameters of GROMOS +@article{Schmid:2011, +author = {Schmid, Nathan and Eichenberger, Andreas P. and Choutko, Alexandra and Riniker, Sereina and Winger, Moritz and Mark, Alan E. and van Gunsteren, Wilfred F.}, +title = {Definition and testing of the GROMOS force-field versions 54A7 and 54B7}, +journal = {European Biophysics Journal}, +volume = {40}, +issue = {7}, +pages = {843}, +year = {2011}, +doi = {10.1007/s00249-011-0700-9}, +URL = {https://doi.org/10.1007/s00249-011-0700-9} +} \ No newline at end of file diff --git a/paper/paper.md b/paper/paper.md index c4ef2c3..671a7b4 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -60,7 +60,8 @@ bibliography: paper.bib # Summary -Molecular Mechanics (MM) simulations (molecular dynamics and Monte Carlo) provide a third method of scientific discovery, simulation modeling, adding to the traditional theoretical and experimental scientific methods. These molecular simulations provide visualizations and calculated properties that are difficult, too expensive, or unattainable by conventional methods. Additionally, molecular simulations can be used to obtain insights and properties on chemicals or materials that do not currently exist, are not easily attainable, or require hard-to-achieve conditions (i.e., very high pressures and temperatures). However, these MM models require force field parameters determined from Quantum Mechanics (QM) simulations, where the MM proper dihedrals (i.e., dihedrals) are difficult to obtain if they don't currently exist for the chosen force field. While the same QM simulations can be used to fit the dihedrals in all of the force field types, these MM dihedrals are also not easily transferable between different force fields due to the differing parameters and formulas used in each force field (e.g., Combining rules and 1-4 scaling factors). +Molecular Mechanics (MM) simulations (molecular dynamics and Monte Carlo) provide a third method of scientific discovery, simulation modeling, adding to the traditional theoretical and experimental scientific methods. These molecular simulations provide visualizations and calculated properties that are difficult, too expensive, or unattainable by conventional methods. Additionally, molecular simulations can be used to obtain insights and properties on chemicals or materials that do not currently exist, are not easily attainable, or require hard-to-achieve conditions (i.e., very high pressures and temperatures). However, these MM models require force field parameters to be determined ideally from Quantum Mechanics (QM) simulations or other methods, including the vibrational spectrum and machine learning methods [@Kania:2021; @Friederich:2018; @Vermeyen:2023; @Mayne:2013; @Schmid:2011], where the MM proper dihedrals (i.e., dihedrals) are challenging to obtain if they don't currently exist for the chosen force field or they do not properly scale-up to larger molecules or moiety combinations from their separately derived parameters using small molecules [@Kania:2021: @Mayne:2013]. While the same QM simulations can be used to fit the dihedrals in all of the force field types, these MM dihedrals are also not easily transferable between different force fields due to the differing parameters and formulas used in each force field (e.g., Combining rules and 1-4 scaling factors). + The `MoSDeF-Dihedral-Fit` [@Crawford:2023b] library lets users quickly calculate the MM proper dihedrals (dihedrals) directly from the QM simulations for several force fields (OPLS, TraPPE, AMBER, Mie, and Exp6) [@Jorgensen:1996; @Martin:1998; @Weiner:1984; @Weiner:1986; @Potoff:2009; @Hemmen:2015; @Errington:1999]. The user simply has to generate or use an existing Molecular Simulation Design Framework (MoSDeF) force field XML file [@Cummings:2021; @Summers:2020; @GMSO:2019; @forcefield-utilities:2022], provide Gaussian 16 or Gaussian-style Quantum Mechanics (QM) simulation files that cover the dihedral rotation (typically, 0-360 degrees), and provide the molecular structure information in a mol2 format [@Gaussian16:2016]. The `MoSDeF-Dihedral-Fit` software uses the QM and MM data to fit the dihedral for the specific force field, fitting the constants for the OPLS dihedral equation form with the correct combining rules and 1-4 scaling factors, as specified in the MoSDeF XML force field file. This software also accounts for multiple instances of the dihedral and the molecular symmetry in the molecule, and automatically removes all the unusable cosine power series values due to this symmetry. The user can set other dihedral energies in the molecule to zero, allowing for a more flexible and accurate dihedral fit; this allows the multiple dihedral's conformational energies to be calculated from a single dihedral angle, a strategy that was used in some of the original OPLS dihedral fits. The `MoSDeF-Dihedral-Fit` software analytically calculates the Ryckaert-Bellemans (RB)-torsions and the periodic dihedral from the OPLS dihedral. If another form of the dihedral equation that is not currently supported is needed, the software outputs the raw data points to enable users to fit any other dihedral form. Therefore, the `MoSDeF-Dihedral-Fit` software allows the fitting of any dihedral form, provided the force fields and software it utilizes are supported by MoSDeF and MoSDeF-GOMC (which uses GPU Optimized Monte Carlo - GOMC) [@Crawford:2023a; @Crawford:2022; @Crawford:2023b; @Nejahi:2019; @Nejahi:2021], vmd-python [@vmd-python:2016] (a derivative or modified version of the original VMD software [@Humphrey:1996; @Stone:2001]), and the QM data is provided as a Gaussian output file, or a generalized Gaussian-style output form [@Gaussian16:2016]. From 78725c5e261c2f5df21bcb8282093a2c44a27cc8 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sat, 24 Aug 2024 13:44:35 +0000 Subject: [PATCH 2/3] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- paper/paper.bib | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/paper/paper.bib b/paper/paper.bib index 1cdfa29..8fdefe9 100644 --- a/paper/paper.bib +++ b/paper/paper.bib @@ -398,7 +398,7 @@ @article{Kania:2021 } -# Other ML dihedral fit methods +# Other ML dihedral fit methods @article{Friederich:2018, author = {Friederich, Pascal and Konrad, Manuel and Strunk, Timo and Wenzel, Wolfgang}, title = {Machine learning of correlated dihedral potentials for atomistic molecular force fields}, @@ -411,7 +411,7 @@ @article{Friederich:2018 URL = {https://doi.org/10.1038/s41598-018-21070-0} } -# Other ML vibrational fit dihedral +# Other ML vibrational fit dihedral @article{Vermeyen:2023, author = {Vermeyen, Tom and Cunha, Ana and Bultinck, Patrick and Herrebout, Wouter}, title = {Impact of conformation and intramolecular interactions on vibrational circular dichroism spectra identified with machine learning}, @@ -448,4 +448,4 @@ @article{Schmid:2011 year = {2011}, doi = {10.1007/s00249-011-0700-9}, URL = {https://doi.org/10.1007/s00249-011-0700-9} -} \ No newline at end of file +} From 2234d4f74ff569093ff0055b7b1e2dd845354d5f Mon Sep 17 00:00:00 2001 From: bc118 Date: Sat, 24 Aug 2024 10:04:41 -0400 Subject: [PATCH 3/3] adds other ways to get FF or dihedral parameters --- paper/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paper/paper.md b/paper/paper.md index 671a7b4..fda4376 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -60,7 +60,7 @@ bibliography: paper.bib # Summary -Molecular Mechanics (MM) simulations (molecular dynamics and Monte Carlo) provide a third method of scientific discovery, simulation modeling, adding to the traditional theoretical and experimental scientific methods. These molecular simulations provide visualizations and calculated properties that are difficult, too expensive, or unattainable by conventional methods. Additionally, molecular simulations can be used to obtain insights and properties on chemicals or materials that do not currently exist, are not easily attainable, or require hard-to-achieve conditions (i.e., very high pressures and temperatures). However, these MM models require force field parameters to be determined ideally from Quantum Mechanics (QM) simulations or other methods, including the vibrational spectrum and machine learning methods [@Kania:2021; @Friederich:2018; @Vermeyen:2023; @Mayne:2013; @Schmid:2011], where the MM proper dihedrals (i.e., dihedrals) are challenging to obtain if they don't currently exist for the chosen force field or they do not properly scale-up to larger molecules or moiety combinations from their separately derived parameters using small molecules [@Kania:2021: @Mayne:2013]. While the same QM simulations can be used to fit the dihedrals in all of the force field types, these MM dihedrals are also not easily transferable between different force fields due to the differing parameters and formulas used in each force field (e.g., Combining rules and 1-4 scaling factors). +Molecular Mechanics (MM) simulations (molecular dynamics and Monte Carlo) provide a third method of scientific discovery, simulation modeling, adding to the traditional theoretical and experimental scientific methods. These molecular simulations provide visualizations and calculated properties that are difficult, too expensive, or unattainable by conventional methods. Additionally, molecular simulations can be used to obtain insights and properties on chemicals or materials that do not currently exist, are not easily attainable, or require hard-to-achieve conditions (i.e., very high pressures and temperatures). However, these MM models require force field parameters to be determined ideally from Quantum Mechanics (QM) simulations or other methods, including the vibrational spectrum and machine learning methods [@Kania:2021; @Friederich:2018; @Vermeyen:2023; @Mayne:2013; @Schmid:2011], where the MM proper dihedrals (i.e., dihedrals) are challenging to obtain if they don't currently exist for the chosen force field or they do not properly scale-up to larger molecules or moiety combinations from their separately derived parameters using small molecules [@Kania:2021; @Mayne:2013]. While the same QM simulations can be used to fit the dihedrals in all of the force field types, these MM dihedrals are also not easily transferable between different force fields due to the differing parameters and formulas used in each force field (e.g., Combining rules and 1-4 scaling factors). The `MoSDeF-Dihedral-Fit` [@Crawford:2023b] library lets users quickly calculate the MM proper dihedrals (dihedrals) directly from the QM simulations for several force fields (OPLS, TraPPE, AMBER, Mie, and Exp6) [@Jorgensen:1996; @Martin:1998; @Weiner:1984; @Weiner:1986; @Potoff:2009; @Hemmen:2015; @Errington:1999]. The user simply has to generate or use an existing Molecular Simulation Design Framework (MoSDeF) force field XML file [@Cummings:2021; @Summers:2020; @GMSO:2019; @forcefield-utilities:2022], provide Gaussian 16 or Gaussian-style Quantum Mechanics (QM) simulation files that cover the dihedral rotation (typically, 0-360 degrees), and provide the molecular structure information in a mol2 format [@Gaussian16:2016]. The `MoSDeF-Dihedral-Fit` software uses the QM and MM data to fit the dihedral for the specific force field, fitting the constants for the OPLS dihedral equation form with the correct combining rules and 1-4 scaling factors, as specified in the MoSDeF XML force field file. This software also accounts for multiple instances of the dihedral and the molecular symmetry in the molecule, and automatically removes all the unusable cosine power series values due to this symmetry. The user can set other dihedral energies in the molecule to zero, allowing for a more flexible and accurate dihedral fit; this allows the multiple dihedral's conformational energies to be calculated from a single dihedral angle, a strategy that was used in some of the original OPLS dihedral fits. The `MoSDeF-Dihedral-Fit` software analytically calculates the Ryckaert-Bellemans (RB)-torsions and the periodic dihedral from the OPLS dihedral. If another form of the dihedral equation that is not currently supported is needed, the software outputs the raw data points to enable users to fit any other dihedral form. Therefore, the `MoSDeF-Dihedral-Fit` software allows the fitting of any dihedral form, provided the force fields and software it utilizes are supported by MoSDeF and MoSDeF-GOMC (which uses GPU Optimized Monte Carlo - GOMC) [@Crawford:2023a; @Crawford:2022; @Crawford:2023b; @Nejahi:2019; @Nejahi:2021], vmd-python [@vmd-python:2016] (a derivative or modified version of the original VMD software [@Humphrey:1996; @Stone:2001]), and the QM data is provided as a Gaussian output file, or a generalized Gaussian-style output form [@Gaussian16:2016].