Refinement of the Optimized Potentials for Liquid Simulations Force Field for Thermodynamics and Dynamics of Liquid Alkanes

Tips and Tricks in the Modeling of Supramolecular Peptide Assemblies

Supramolecular peptide assemblies (SPAs) hold promise as materials for nanotechnology and biomedicine. Although their investigation often entails adapting experimental techniques from their protein counterparts, SPAs are fundamentally distinct from proteins, posing unique challenges for their study. Computational methods have emerged as indispensable tools for gaining deeper insights into SPA structures at the molecular level, surpassing the limitations of experimental techniques, and as screening tools to reduce the experimental search space. However, computational studies have grappled with issues stemming from the absence of standardized procedures and relevant crystal structures. Fundamental disparities between SPAs and protein simulations, such as the absence of experimentally validated initial structures and the importance of the simulation size, number of molecules, and concentration, have compounded these challenges. Understanding the roles of various parameters and the capabilities of different models and simulation setups remains an ongoing endeavor. In this review, we aim to provide readers with guidance on the parameters to consider when conducting SPA simulations, elucidating their potential impact on outcomes and validity.

A polarizable valence electron density based force field for high-energy interactions between atoms and molecules

High-accuracy molecular force field models suited for hot gases and plasmas are not as abundant as those geared toward ambient pressure and temperature conditions. Here, we present an improved version of our previous electron-density based force field model that can now account for polarization effects by adjusting the atomic valence electron contributions to match ab initio calculated Mulliken partial charges. Using a slightly modified version of the Hohenberg-Kohn theorem, we also include an improved theoretical formulation of our model when applied to systems with degenerate ground states. We present two variants of our polarizable model, fitted from ab initio reference data calculated at CCSD(T)/cc-pVTZ and CCSD(T)/CEP-31G levels of theory, that both accurately model water dimer interaction energies. Further improvements include the additional interaction components with fictitious non-spherically symmetric, yet atom-centered, electron densities and fitting the exchange and correlation coefficients against analytical expressions. The latter removes all unphysical oscillations that are observed in the previous non-polarizable variant of our force field.

The effect of functional groups on the glass transition temperature of atmospheric organic compounds: a molecular dynamics study

Organic compounds constitute a substantial part of atmospheric particulate matter not only in terms of mass concentration but also in terms of distinct functional groups. The glass transition temperature provides an indirect way to investigate the phase state of the organic compounds, playing a crucial role in understanding their behavior and influence on aerosol processes. Molecular dynamics (MD) simulations were implemented here to predict the glass transition temperature (Tg) of atmospherically relevant organic compounds as well as the influence of their functional groups and length of their carbon chain. The cooling step used in the simulations was chosen to be neither too low (to supress crystallization) nor too high (to avoid Tg overprediction). According to the MD simulations, the predicted Tg is sensitive to the functional groups as follows: carboxylic acid (-COOH) > hydroxyl (-OH) and (-COOH) > carbonyls (-CO). Increasing the number of carbon atoms leads to higher Tg for the linearly structured compounds. Linear compounds with lower molecular weight were found to exhibit a lower Tg. No clear correlation between O : C and Tg was observed. The architecture of the carbon chain (linear, or branched, or ring) was also found to impact the glass transition temperature. Compounds containing a non-aromatic carbon ring are characterized by a higher Tg compared to linear and branched ones with the same number of carbon atoms.

OPLS/2020 Force Field for Unsaturated Hydrocarbons, Alcohols, and Ethers

The OPLS all-atom force field was updated and applied to modeling unsaturated hydrocarbons, alcohols, and ethers. Testing has included gas-phase conformational energetics, properties of pure liquids, and free energies of hydration. Monte Carlo statistical mechanics (MC) calculations were used to model 60 liquids. In addition, a robust, automated procedure was devised to compute the free energies of hydration with high precision via free-energy perturbation (FEP) calculations using double annihilation. Testing has included larger molecules than in the past, and parameters are reported for the first time for some less common groups including alkynes, allenes, dienes, and acetals. The average errors in comparison with experimental data for the computed properties of the pure liquids were improved with the modified force field (OPLS/2020). For liquid densities and heats of vaporization, the average unsigned errors are 0.01 g/cm3 and 0.2 kcal/mol. The average error and signed error for free energies of hydration are both 1.2 kcal/mol. As noted before, this reflects a systematic overestimate of the hydrophobicity of organic molecules when the parametrization is done to minimize the errors for properties of pure liquids. Implications for the modeling of biomolecular systems with standard force fields are considered.

Comprehensive Automated Routine Implementation, Validation, and Benchmark of the Anisotropic Force Field (AUA4) Using Python and GROMACS

Molecular simulation users are sometimes discouraged from using specific molecular models because of the inconvenience of finding the force field parameters and preparing and validating the topology files. To facilitate this process and make the accurate anisotropic force field AUA4 available to molecular dynamics users, we have created and validated an automated topology and coordinate file creation routine for the GROMACS molecular simulation software. In the present work, we describe the AUA4, explain its particularities and how it was implemented, thoroughly validating the implementation, and for the first time, perform a molecular dynamics benchmark for this transferable force field. Several properties were computed, namely, liquid density, vapor pressure, and vaporization enthalpy by conducting explicit vapor-liquid interface simulations. The results evidence the correct implementation showing slight deviations from the parametrization studies. The benchmark shows the superior predictive capability of the AUA4 in recreating liquid density (RMSD equal to 17.0 kg/m³) and vaporization enthalpy (RMSD equal to 1.3 kJ/mol) compared to other transferable force fields. In addition, its superior computational time performance doubles or even triples compared to an all-atom force field such as the OPLS, depending on whether the workstation counts with GPU.

Using physical property surrogate models to perform accelerated multi-fidelity optimization of force field parameters†

Accurate representations of van der Waals dispersion–repulsion interactions play an important role in high-quality molecular dynamics simulations. Training the force field parameters used in the Lennard Jones (LJ) potential typically used to represent these interactions is challenging, generally requiring adjustment based on simulations of macroscopic physical properties. The large computational expense of these simulations, especially when many parameters must be trained simultaneously, limits the size of training data set and number of optimization steps that can be taken, often requiring modelers to perform optimizations within a local parameter region. To allow for more global LJ parameter optimization against large training sets, we introduce a multi-fidelity optimization technique which uses Gaussian process surrogate modeling to build inexpensive models of physical properties as a function of LJ parameters. This approach allows for fast evaluation of approximate objective functions, greatly accelerating searches over parameter space and enabling the use of optimization algorithms capable of searching more globally. In this study, we use an iterative framework which performs global optimization with differential evolution at the surrogate level, followed by validation at the simulation level and surrogate refinement. Using this technique on two previously studied training sets, containing up to 195 physical property targets, we refit a subset of the LJ parameters for the OpenFF 1.0.0 (Parsley) force field. We demonstrate that this multi-fidelity technique can find improved parameter sets compared to a purely simulation-based optimization by searching more broadly and escaping local minima. Additionally, this technique often finds significantly different parameter minima that have comparably accurate performance. In most cases, these parameter sets are transferable to other similar molecules in a test set. Our multi-fidelity technique provides a platform for rapid, more global optimization of molecular models against physical properties, as well as a number of opportunities for further refinement of the technique.

We present a multi-fidelity method for optimizing nonbonded force field parameters against physical property data. Leveraging fast surrogate models, we accelerate the parameter search and find novel solutions that improve force field performance.