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paper/paper.bib

@@ -655,3 +655,20 @@ @article{Louie:2021
 doi = {10.1038/s41563-021-01015-1},
 URL = {https://doi.org/10.1038/s41563-021-01015-1},
 }
+
+# Molecular simulations books 
+@Inbook{Allen:2017,
+author={Allen, M. P. and Tildesley, D. J},
+title="Computer simulation of liquids (2nd ed.)",
+year={2017},
+publisher={Oxford University Press},
+}
+
+# Molecular simulations books 
+@Inbook{Frekel:2002,
+author={Daan Frenkel and Berend Smit},
+title={Understanding Molecular Simulation From Algorithms to Applications (2nd ed.)},
+year={2002},
+publisher={Academic Press},
+}
+

paper/paper.md

@@ -60,7 +60,9 @@ bibliography: paper.bib
 
 # Summary
 
-Molecular Mechanics (MM) simulations (e.g., molecular dynamics and Monte Carlo) provide a third method of scientific discovery, adding to the traditional theoretical and experimental scientific methods [@Mielke:2019; @Siegfried:2014].  These molecular simulations provide visualizations and calculated properties that are difficult, too expensive, or unattainable by conventional methods [@Hollingsworth:2018; @Hirst:2014].  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, such as very high pressures and temperatures [@Yu:2023; @Koneru:2022; @Swai:2020; @Kumar:2022; @Louie:2021].  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; @Vanommeslaeghe:2014], 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 (e.g., combining rules and 1-4 scaling factors) used in each force field [@Huang:2013; @Vanommeslaeghe:2010; @Vanommeslaeghe:2014; @Chen:2015].
+Molecular Mechanics (MM) simulations (e.g., molecular dynamics and Monte Carlo) provide a third method of scientific discovery, adding to the traditional theoretical and experimental scientific methods [@Mielke:2019; @Siegfried:2014].  Experimental methods measure the data under set conditions (e.g., temperature and pressure), whereas the traditional theoretical methods are based on analytical equations, and sometimes their constants are fitted to experimental data (e.g., equations of state).  The MM simulations are deterministic and stochastic, and their models can be optimized to match experimental data, similar to analytical theory-based methods [@Allen:2017; @Frekel:2002; @Jorgensen:1996; @Martin:1998; @Weiner:1984; @Weiner:1986; @Potoff:2009; @Hemmen:2015; @Errington:1999].  In larger, more complex systems, the stochastic simulation's molecules can jump large energy barriers that deterministic simulations may not be able to overcome in a reasonable timeframe, even with modern computing capabilities [@Allen:2017; @Frekel:2002].  However, deterministic and stochastic systems that provide adequate sampling for calculating a given property can provide critical insights into the system's phase space, which are not obtainable via traditional theoretical and experimental methods.  Additionally, molecular simulations provide critical insights from visualizations and by obtaining chemical or material properties that do not currently exist, are not easily attainable (e.g., too expensive or dangerous) by traditional theoretical and experimental methods [@Hollingsworth:2018; @Hirst:2014], or require hard-to-achieve conditions, such as very high pressures and temperatures [@Yu:2023; @Koneru:2022; @Swai:2020; @Kumar:2022; @Louie:2021].   
+
+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; @Vanommeslaeghe:2014], 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 (e.g., combining rules and 1-4 scaling factors) used in each force field [@Huang:2013; @Vanommeslaeghe:2010; @Vanommeslaeghe:2014; @Chen:2015].
 
 
 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].