General Force Field Research Articles

Fine-Tuning the Polarizable CL&Pol Force Field for the Deep Eutectic Solvent Ethaline.

Polarizable force fields are gradually becoming a common choice for ionic soft matter, in particular, for molecular dynamics (MD) simulations of ionic liquids (ILs) and deep eutectic solvents (DESs). The CL&Pol force field introduced in 2019 is the first general, transferable, and polarizable force field for MD simulations of different types of DESs. The original formulation contains, however, some problems that appear in simulations of ethaline and may also have a broader impact. First, the originally proposed atomic diameter parameters are unbalanced, resulting in too weak interactions between the chlorides and the hydroxyl groups of the ethylene glycol molecules. This, in turn, causes an artificial phase separation in long simulations. Second, there is an overpolarization of chlorides due to strong induced dipoles that give rise to the presence of peaks and antipeaks at very low q-vector values (2.4 nm-1) in the partial components of the structure factors. In physical terms, this is equivalent to overestimated spatial nanoscale heterogeneity. To correct these problems, we adjusted the chloride-hydroxyl radial distribution functions against ab initio data and then extended the use of the Tang-Toennis damping function for the chlorides' induced dipoles. These adjustments correct the problems without losing the robustness of the CL&Pol force field. The results were also compared with the nonpolarizable version, the CL&P force field. We expect that the corrections will facilitate reliable use of the CL&Pol force field for other types of DESs.

Global Optimization of the Lennard-Jones Parameters for the Drude Polarizable Force Field.

Molecular dynamics (MD) simulations based on atomic models play an important role in the drug-discovery process to screen molecules, estimate binding free energies, and optimize lead compounds in chemical space. Accurate computations of thermodynamic and kinetic properties using MD simulations are highly dependent on the accuracy of the underlying atomic force field. In this context, going beyond the nonpolarizable fixed-charge model by accounting explicitly for induced polarization is highly desirable. The CHARMM polarizable force field based on classical Drude oscillators, in which an auxiliary charged particle is attached via a harmonic spring to its parent nucleus, offers both a computationally convenient and rigorous framework to model explicitly induced electronic polarization in MD simulations. For any molecule of interest, electrostatic partial charges, atomic polarizabilities, and Thole shielding factors, as well as bonded parameters can either be determined from ab initio calculations or ascribed from the knowledge-based library of the CHARMM Generalized force field. While this approach is fairly reliable in general, it is well understood that the overall accuracy of the models with respect to thermodynamic properties such as bulk density, enthalpies, and solvation free energies is particularly sensitive to the nonbonded Lennard-Jones (LJ) parameters. In the present study, we systematically refined the set of LJ parameters for the atom types available in the Drude force field to best match the experimental thermodynamic properties for 416 small druglike organic molecules. To further test the transferability of the optimized parameters, the hydration free energy of 372 molecules was computed. The calculations resulted in a small average error of 0.46 kcal/mol and a Pearson R of 0.9, representing a significant improvement over the additive GAFF force field in our previous study, where an average error of ∼2 kcal/mol was obtained. Such an improvement is consistent with the ability of the polarizable Drude model to more accurately model interactions in different environments. The effort provides a roadmap for the global optimization of force field parameters using experimental data. It is hoped that the present effort will further the application of the Drude polarizable force field in molecular simulations including drug design and discovery.

Development and Benchmarking of Open Force Field v1.0.0-the Parsley Small-Molecule Force Field.

We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 small-molecule force field, codenamed Parsley. Rather than using traditional atom typing, our approach is built on the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of the specification. Parameters are optimized with the ForceBalance tool, based on reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These quantum reference data are computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. In this initial application of the method, we present essentially a full optimization of all valence parameters and report tests of the resulting force field against compounds and data types outside the training set. These tests show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields, as is accuracy on binding free energies. We find that this initial Parsley force field affords accuracy similar to that of other general force fields when used to calculate relative binding free energies spanning 199 protein-ligand systems. Additionally, the resulting infrastructure allows us to rapidly optimize an entirely new force field with minimal human intervention.

A Reduced Generalized Force Field for Biological Halogen Bonds.

The halogen bond (or X-bond) is a noncovalent interaction that is increasingly recognized as an important design tool for engineering protein-ligand interactions and controlling the structures of proteins and nucleic acids. In the past decade, there have been significant efforts to characterize the structure-energy relationships of this interaction in macromolecules. Progress in the computational modeling of X-bonds in biological molecules, however, has lagged behind these experimental studies, with most molecular mechanics/dynamics-based simulation methods not properly treating the properties of the X-bond. We had previously derived a force field for biological X-bonds (ffBXB) based on a set of potential energy functions that describe the anisotropic electrostatic and shape properties of halogens participating in X-bonds. Although fairly accurate for reproducing the energies within biomolecular systems, including X-bonds engineered into a DNA junction, the ffBXB with its seven variable parameters was considered to be too unwieldy for general applications. In the current study, we have generalized the ffBXB by reducing the number of variables to just one for each halogen type and show that this remaining electrostatic variable can be estimated for any new halogenated molecule through a standard restricted electrostatic potential calculation of atomic charges. In addition, we have generalized the ffBXB for both nucleic acids and proteins. As a proof of principle, we have parameterized this reduced and more general ffBXB against the AMBER force field. The resulting parameter set was shown to accurately recapitulate the quantum mechanical landscape and experimental interaction energies of X-bonds incorporated into DNA junction and T4 lysozyme model systems. Thus, this reduced and generalized ffBXB is more readily adaptable for incorporation into classical molecular mechanics/dynamics algorithms, including those commonly used to design inhibitors against therapeutic targets in medicinal chemistry and materials in biomolecular engineering.

Optimized Halogen Atomic Radii for PBSA Calculations Using Off-Center Point Charges.

In force-field methods, the usage of off-center point charges, also called extra points (EPs), is a common strategy to tackle the anisotropy of the electrostatic potential of covalently bonded halogens (X), thus allowing the description of halogen bonds (XBs) at the molecular mechanics/molecular dynamics (MM/MD) level. Diverse EP implementations exist in the literature differing on the charge sets and/or the X-EP distances. Poisson-Boltzmann and surface area (PBSA) calculations can be used to obtain solvation free energies (ΔGsolv) of small molecules, often to compute binding free energies (ΔGbind) at the MM-PBSA level. This method depends, among other parameters, on the empirical assignment of atomic radii (PB radii). Given the multiplicity of off-center point-charge models and the lack of specific PB radii for halogens compatible with such implementations, in this work, we assessed the performance of PBSA calculations for the estimation of ΔGsolv values in water (ΔGhyd), also conducting an optimization of the halogen PB radii (Cl, Br, and I) for each EP model. We not only expand the usage of EP models in the scope of the general AMBER force field (GAFF) but also provide the first optimized halogen PB radii in the context of the CHARMM general force field (CGenFF), thus contributing to improving the description of halogenated compounds in PBSA calculations.

Robust and Efficient Implicit Solvation Model for Fast Semiempirical Methods.

We present a robust and efficient method to implicitly account for solvation effects in modern semiempirical quantum mechanics and force fields. A computationally efficient yet accurate solvation model based on the analytical linearized Poisson-Boltzmann (ALPB) model is parameterized for the extended tight binding (xTB) and density functional tight binding (DFTB) methods as well as for the recently proposed GFN-FF general force field. The proposed methods perform well over a broad range of systems and applications, from conformational energies over transition-metal complexes to large supramolecular association reactions of charged species. For hydration free energies of small molecules, GFN1-xTB(ALPB) is reaching the accuracy of sophisticated explicitly solvated approaches, with a mean absolute deviation of only 1.4 kcal/mol compared to the experiment. Logarithmic octanol-water partition coefficients (log Kow) are computed with a mean absolute deviation of about 0.65 using GFN2-xTB(ALPB) compared to experimental values indicating a consistent description of differential solvent effects. Overall, more than twenty solvents for each of the six semiempirical methods are parameterized and tested. They are readily available in the xtb and dftb+ programs for diverse computational applications.

Additive CHARMM36 Force Field for Nonstandard Amino Acids.

Nonstandard amino acids are both abundant in nature, where they play a key role in various cellular processes, and can be synthesized in laboratories, for example, for the manufacture of a range of pharmaceutical agents. In this work, we have extended the additive all-atom CHARMM36 and CHARMM General force field (CGenFF) to a large set of 333 nonstandard amino acids. These include both amino acids with nonstandard side chains, such as post-translationally modified and artificial amino acids, as well as amino acids with modified backbone groups, such as chromophores composed of several amino acids. Model compounds representative of the nonstandard amino acids were parametrized for protonation states that are likely at the physiological pH of 7 and, for some more common residues, in both d- and l-stereoisomers. Considering all protonation, tautomeric, and stereoisomeric forms, a total of 406 nonstandard amino acids were parametrized. Emphasis was placed on the quality of both intra- and intermolecular parameters. Partial charges were derived using quantum mechanical (QM) data on model compound dipole moments, electrostatic potentials, and interactions with water. Optimization of all intramolecular parameters, including torsion angle parameters, was performed against information from QM adiabatic potential energy surface (PES) scans. Special emphasis was put on the quality of terms corresponding to PES around rotatable dihedral angles. Validation of the force field was based on molecular dynamics simulations of 20 protein complexes containing different nonstandard amino acids. Overall, the presented parameters will allow for computational studies of a wide range of proteins containing nonstandard amino acids, including natural and artificial residues.

A replica exchange umbrella sampling (REUS) approach to predict host\u2013guest binding free energies in SAMPL8 challenge

In this study, we report binding free energy calculations of various drugs-of-abuse to Cucurbit-[8]-uril as part of the SAMPL8 blind challenge. Force-field parameters were obtained from force-matching with different quantum mechanical levels of theory. The Replica Exchange Umbrella Sampling (REUS) approach was used with a cylindrical restraint to enhance the sampling of host–guest binding. Binding free energy was calculated by pulling the guest molecule from one side of the symmetric and cylindrical host, then into and through the host, and out the other side (bidirectional) as compared to pulling only to the bound pose inside the cylindrical host (unidirectional). The initial results with force-matched MP2 parameter set led to RMSE of 4.68 {text{kcal}}/{text{mol}} from experimental values. However, the follow-up study with CHARMM generalized force field parameters and force-matched PM6-D3H4 parameters resulted in RMSEs from experiment of 2.65 and 1.72 {text{kcal}}/{text{mol}}, respectively, which demonstrates the potential of REUS for accurate binding free energy calculation given a more suitable description of energetics. Moreover, we compared the free energies for the so called bidirectional and unidirectional free energy approach and found that the binding free energies were highly similar. However, one issue in the bidirectional approach is the asymmetry of profile on the two sides of the host. This is mainly due to the insufficient sampling for these larger systems and can be avoided by longer sampling simulations. Overall REUS shows great promise for binding free energy calculations.

A general RNA force field: comprehensive analysis of energy minima of molecular fragments of RNA.

Force fields are actively used to study RNA. Development of accurate force fields relies on a knowledge of how the variation of properties of molecules depends on their structure. Detailed scrutiny of RNA's conformational preferences is needed to guide such development. Towards this end, minimum energy structures for each of a set of 16 small RNA-derived molecules were obtained by geometry optimization at the HF/6-31G(d,p), B3LYP/apc-1, and MP2/cc-pVDZ levels of theory. The number of minima computed for a given fragment was found to be related to both its size and flexibility. Atomic electrostatic multipole moments of atoms occurring in the [HO-P(O3)-CH2-] fragment of 30 sugar-phosphate-sugar geometries were calculated at the HF/6-31G(d,p) and B3LYP/apc-1 levels of theory, and the transferability of these properties between different conformations was investigated. The atomic multipole moments were found to be highly transferable between different conformations with small standard deviations. These results indicate necessary elements of the development of accurate RNA force fields.

Molecular simulations of the adsorption and separation of hydrogen sulfide, carbon dioxide, methane, and nitrogen and their binary mixtures (H2S/CH4), (CO2/CH4) on NUM-3a metal-organic frameworks.

In this work, the adsorptions of carbon dioxide, methane, nitrogen, and hydrogen sulfide and the separation of their binary mixtures into NUM-3a Metal-Organic Framework (MOF) were studied through Grand Canonical Monte Carlo (GCMC) simulation method. The simulated pure gas uptakes using three generic force fields (UFF, Dreiding, and OPLS) at 298K were compared with the experimental values. The accuracy of the applied force fields for each gas was compared with the experimental isotherms and discussed. Our results show that OPLS has the best accuracy in the case of methane while Dreiding was the best for CO2 and N2. Simulated gas uptakes indicated that H2S was more adsorbed by NUM-3a than CO2, CH4, and N2. The calculated adsorption selectivity of NUM-3a for the binary mixtures of CH4 with H2S is larger than that of CO2. NUM-3a possess more affinity for H2S and CO2 than for CH4, where it may be a promising adsorbent material for separating carbon dioxide and hydrogen sulfide from methane. Furthermore, the most probable sites for the adsorption of the studied gases on the NUM-3a were investigated. The heats of adsorptions, as well as Henry's law constants, were also calculated, and it was in line with the observed gas adsorptions. The most preferred sites for the adsorption of carbon dioxide and hydrogen sulfide are the carboxyl groups and inside the channels and around the metal centers. However, methane and nitrogen are mainly accumulating in the channels' s apexes of NUM-3a around the metal center.

ClassicalGSG: Prediction of log P using classical molecular force fields and geometric scattering for graphs.

This work examines methods for predicting the partition coefficient (log P) for a dataset of small molecules. Here, we use atomic attributes such as radius and partial charge, which are typically used as force field parameters in classical molecular dynamics simulations. These atomic attributes are transformed into index-invariant molecular features using a recently developed method called geometric scattering for graphs (GSG). We call this approach "ClassicalGSG" and examine its performance under a broad range of conditions and hyperparameters. We train ClassicalGSG log P predictors with neural networks using 10,722 molecules from the OpenChem dataset and apply them to predict the log P values from four independent test sets. The ClassicalGSG method's performance is compared to a baseline model that employs graph convolutional networks. Our results show that the best prediction accuracies are obtained using atomic attributes generated with the CHARMM generalized force field and 2D molecular structures.

Martini 3: a general purpose force field for coarse-grained molecular dynamics.

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Deep Learning Based Optimization of Lennard-Jones Parameters for the Drude General Force Field (DGenFF)

The CHARMM Drude polarizable force field (FF) incorporates induced polarization effects in molecular dynamics (MD) simulations based on the classical Drude oscillator model. Implementation of this model improves simulation of electrostatic interactions in MD simulations. The Drude polarizable FF currently extends to proteins, nucleic acids, lipids, carbohydrates; however, it has a limited set of drug-like (organic) molecules. This study focuses on extending CHARMM Drude polarizable FF to a complete set of small molecules to release Drude General Force Field (DGenFF). Parametrization of DGenFF requires introduction of 49 new atom types for a complete expansion comparable to its additive counterpart - CHARMM General Force Field (CGenFF). Introduction of new atom types involves optimization of Lennard-Jones (LJ) parameters targeting model compounds specifically selected for various atom types. The optimization targets experimental thermodynamic properties, like enthalpy of vaporization (ΔHvap) molecular volume (VMol), dielectric constant, and viscosity, among others. To perform LJ parametrization while accounting for correlation and high dimensionality of parameters we harness the predictive ability of Deep Learning (DL) by combining it with an initial design algorithm, Latin Hypercube Design (LHD). LHD extensively explores the multidimensional LJ parameter space for multiple atom types simultaneously to identify a subset of distributed parameter sets. ΔHvap and VMol are then calculated via MD simulations for the LJ parameter sets for selected model compounds creating training for the DL model. The trained DL model then identifies optimal sets of parameters closer to the target experimental data, which are refined and ranked based on QM interactions with rare gases, water and other experimental observables. The developed DL-based parametrization framework represents a high-throughput method of LJ parameter optimization based on experimental and QM properties, whose application to several new atom types will be presented.

In silico design of a new Zn-triazole based metal-organic framework for CO2 and H2O adsorption.

In search for future good adsorbents for CO2 capture, a nitrogen-rich triazole-type Metal-Organic Framework (MOF) is proposed based on the rational design and theoretical molecular simulations. The structure of the proposed MOF, named Zinc Triazolate based Framework (ZTF), is obtained by replacing the amine-organic linker of MAF-66 by a triazole, and its structural parameters are deduced. We used grand-canonical Monte Carlo (GCMC) simulations based on generic classical force fields to correctly predict the adsorption isotherms of CO2 and H2O. For water adsorption in MAF-66 and ZTF, simulations revealed that the strong hydrogen bonding interactions of water with the N atoms of triazole rings of the frameworks are the main driving forces for the high adsorption uptake of water. We also show that the proposed ZTF porous material exhibits exceptional high CO2 uptake capacity at low pressure, better than MAF-66. Moreover, the nature of the interactions between CO2 and the MAF-66 and ZTF surface cavities was examined at the microscopic level. Computations show that the interactions occur at two different sites, consisting of Lewis acid-Lewis base interactions and hydrogen bonding, together with obvious electrostatic interactions. In addition, we investigated the influence of the presence of H2O molecules on the CO2 adsorption on the ZTF MOF. GCMC simulations reveal that the addition of H2O molecules leads to an enhancement of the CO2 adsorption at very low pressures but a reduction of this CO2 adsorption at higher pressures.

Multiscale polarizable coarse-graining water models on cluster-level electrostatic dipoles.

The development of a coarse-grained (CG) water model is increasingly important in CG studies of biological processes. In this work, we developed a generic CG force field of liquid water on cluster-level electrostatic dipoles. An exponential term is introduced in the non-bonded potential to adjust the well depth. The whole force field is parametrized on the AMOEBA simulation and then refined on the experimental density, dielectric permittivity and isothermal compressibility. The new CG water force field is suitable for the construction of multi-resolution water models and here the NC = 4/5/10 systems are taken as examples. The results show that the NC = 4/5/10 models can correctly reproduce the density and relative dielectric permittivity. The models can well predict the pressure-density/density-temperature relationships close to the all-atom or experiment results. However, the new models behave differently from other CG models in several water properties such as the air-water surface tension. Through dipole distributions, two representative polarizable configurations are captured after the NC = 4/5/10 systems are dynamically equilibrated. Besides, the NC = 4 model is coupled with the Martini Na+/Cl- models to predict ion-relevant radial distribution functions in comparison to the Martini result. Lastly, CPU tests suggest that the new CG models can enhance simulation efficiency by factors of 20-42, compared to the TIP3P force field. The newly proposed polarizable water force field is practical and transferable and can be flexibly extended to higher coarse-graining of liquid water.

A generic force field for simulating native protein structures using dissipative particle dynamics.

A coarse-grained force field for molecular dynamics simulations of the native structures of proteins in a dissipative particle dynamics (DPD) framework is developed. The parameters for bonded interactions are derived by mapping the bonds and angles for 20 amino acids onto target distributions obtained from fully atomistic simulations in explicit solvent. A dual-basin potential is introduced for stabilizing backbone angles, to cover a wide spectrum of protein secondary structures. The backbone dihedral potential enables folding of the protein from an unfolded initial state to the folded native structure. The proposed force field is validated by evaluating the structural properties of several model peptides and proteins including the SARS-CoV-2 fusion peptide, consisting of α-helices, β-sheets, loops and turns. Detailed comparisons with fully atomistic simulations are carried out to assess the ability of the proposed force field to stabilize the different secondary structures present in proteins. The compact conformations of the native states were evident from the radius of gyration and the high intensity peaks of the root mean square deviation histograms, which were found to be within 0.4 nm. The Ramachandran-like energy landscape on the phase space of backbone angles (θ) and dihedrals (ϕ) effectively captured the conformational phase space of α-helices at ∼(ϕ = 50°,θ = 90°) and β-strands at ∼(ϕ = ±180°,θ = 90-120°). Furthermore, the residue-residue native contacts were also well reproduced by the proposed DPD model. The applicability of the model to multidomain complexes was assessed using lysozyme and a large α-helical bacterial pore-forming toxin, cytolysin A. Our study illustrates that the proposed force field is generic, and can potentially be extended for efficient in silico investigations of membrane bound polypeptides and proteins using DPD simulations.

Benchmarking Force Field and the ANI Neural Network Potentials for the Torsional Potential Energy Surface of Biaryl Drug Fragments.

Many drug molecules contain biaryl fragments, resulting in a torsional barrier corresponding to rotation around the bond linking the aryls. The potential energy surfaces of these torsions vary significantly because of steric and electronic effects, ultimately affecting the relative stability of the molecular conformations in the protein-bound and solution states. Simulations of protein-ligand binding require accurate computational models to represent the intramolecular interactions to provide accurate predictions of the structure and dynamics of binding. In this article, we compare four force fields [generalized AMBER force field (GAFF), open force field (OpenFF), CHARMM general force field (CGenFF), optimized potentials for liquid simulations (OPLS)] and two neural network potentials (ANI-2x and ANI-1ccx) for their ability to predict the torsional potential energy surfaces of 88 biaryls extracted from drug fragments. The root mean square deviation (rmsd) over the full potential energy surface and the mean absolute deviation of the torsion rotational barrier height (MADB) relative to high-level ab initio reference data (CCSD(T1)*) were used as the measure of accuracy. Uncertainties in these metrics due to the composition of the data set were estimated using bootstrap analysis. In comparison to high-level ab initio data, ANI-1ccx was most accurate for predicting the barrier height (rmsd: 0.5 ± 0.0 kcal/mol, MADB: 0.8 ± 0.1 kcal/mol), followed closely by ANI-2x (rmsd: 0.5 ± 0.0 kcal/mol, MADB: 1.0 ± 0.2 kcal/mol), then CGenFF (rmsd: 0.8 ± 0.1 kcal/mol, MADB: 1.3 ± 0.1 kcal/mol) and OpenFF (rmsd: 0.7 ± 0.1 kcal/mol, MADB: 1.3 ± 0.1 kcal/mol), then GAFF (rmsd: 1.2 ± 0.2 kcal/mol, MADB: 2.6 ± 0.5 kcal/mol), and finally OPLS (rmsd: 3.6 ± 0.3 kcal/mol, MADB: 3.6 ± 0.3 kcal/mol). Significantly, the neural network potentials (NNPs) are systematically more accurate and more reliable than any of the force fields. As a practical example, the NNP/molecular mechanics method was used to simulate the isomerization of ozanimod, a drug used for multiple sclerosis. Multinanosecond molecular dynamics (MD) simulations in an explicit aqueous solvent were performed, as well as umbrella sampling and adaptive biasing force-enhanced sampling techniques. The rate constant for this isomerization calculated using transition state theory was 4.30 × 10-1 ns-1, which is consistent with direct MD simulations.

Conformational and intermolecular structure of stereoregular isomers of poly(acrylic acid) (PAA) and Na+-poly(acrylate) polyelectrolyte (Na+-PAA) in dilute aqueous solution: a molecular dynamics simulation study

ABSTRACT Polyelectrolytes are useful in a variety of applications such as detergents, consumer care, electrochemical devices, solid-state reference electrode, water treatment, paper production, contact lenses, drug delivery systems, tissue engineering and biosensors. The behaviour of polyelectrolytes in solution is influenced by stereochemistry. The influence of tacticity on conformations of carboxylate anionic polyelectrolytes isotactic poly(acrylic acid) (i-PAA) and syndiotactic poly(acrylic acid) (s-PAA) in water was investigated by explicit solvent atomistic molecular dynamics (MD) simulations using different generic force-fields (CHARMM27, GROMOS 53a6) and water models (SPC-E and TIP4P). Simulations with uniformly distributed charges were performed using 20, 30, and 60 repeat unit chains of i-PAA and s-PAA. CHARMM27 FF with SPC/E water model correctly depict the helical conformational structure of the i-PAA (tg + = 76%) in comparison with experimental data (tg + = 72%). Simulation results show i-PAA to be helical as compared to s-PAA which is extended (trans), in qualitative agreement with experimental data on i-PAA and s-PMA. Counter-ion condensation is stronger for i-PAA which may be partly responsible for its helical conformation. The novelty of the present work is the origin of the conformational behaviour of the anionic polyelectrolyte with such information having potential biological applications such as gene therapy. Abbreviations: i-PAA: isotactic-poly(acrylic acid); s-PAA: syndiotactic-poly(acrylic acid); s-PMA: syndiotactic-poly(methacrylic acid); PEA: Poly(ethacrylic acid); SPC: Simple Point Charge; SPC/E: Extended Simple Point Charge; ST2: Based on the Ben-Naim and Stillinger model; TIPS: A Set of Transferable Intermolecular Potential function; TIP3P: Three-point Transferable Intermolecular Potential; TIP4P, TIP4P-Ew, TIP4P/Ice, TIP4P/2005: Four-point Transferable Intermolecular Potential, for Ewald technique, for Ice, reparametrised original TIP4P model, respectively; TIP5P: Five-point Transferable Intermolecular Potential; R g: Radius-of-gyration; R: End-to-end distance; RDF: Radial Distribution Function; RB: Ryckaert-Bellemans; COM: Centre-of-Mass; CHARMM: Chemistry at HARward Macromolecular Mechanics; GROMOS: GROningen MOlecular Simulation; GROMACS: GROningen MAchine for Chemical Simulations; MD: Molecular Dynamics; PME: Particle Mesh Ewald; LINCS: LINear Constraint Solver; VR: Velocity Rescaling; NPT: Constant Number of particle, Pressure, and Temperature; NVT: Constant Number of particle, Volume, and Temperature; L-J: Lennard-Jones; vdW: van der Waals; FF, FF1, FF2: Force-Field, Force-Field 1, Force-Field 2 respectively; f Charge fraction or charge density or degree-of-ionisation; ACF: Autocorrelation Function.

Refined Force Field for Liquid Sulfolane with Particular Emphasis to Its Transport Characteristics.

An all-atom force field dedicated to capturing the properties of multifunctional sulfolane is necessary. In addition to being an excellent solvent and extractor, sulfolane is also a frequently investigated component for battery electrolytes in recent times. Given this, theoretically capturing its transport properties is essential. However, given the rather high shear viscosity of liquid sulfolane and its polar aprotic nature, formulating an appropriate non-polarizable force field for this compound remains a challenge. Starting from a generic force field, we report a refined force field for sulfolane which quantitatively captures its bulk properties, resulting in significantly improved estimates for self-diffusion constant and shear viscosity of sulfolane in comparison to force fields reported hitherto. Density, self-diffusion constant, and shear viscosity were determined between temperatures (303 and 398) K and at 1 bar pressure. All properties determined from the refined force field are in good agreement with experiments. The refined model employs atomic site charges obtained from the density-derived electrostatic and chemical (DDEC6) method for liquid sulfolane modeled using quantum density functional theory. Lennard-Jones parameters were refined using quantum potential energy scans. Despite possessing a large dipole moment, the large molecular size of sulfolane partially disrupts intermolecular dipolar ordering in liquid sulfolane. Molecular dipoles of near neighbor sulfolane, however, retain a partial preference for antiparallel orientation even at the highest temperatures investigated here.

Experimentally Verified Alcohol Adsorption Isotherms in Nanoporous Materials from Literature Meta-Analysis

Systematic collection of replicate experimental data via literature meta-analysis is a powerful approach for assessing the reproducibility of physical properties data. In this paper, we use meta-analysis to examine the adsorption equilibrium of alcohols in porous materials using a collection of more than 500 alcohol isotherm measurements. We report consensus isotherms (after rejecting outliers) using experimentally measured replicates for 11 systems with methanol, ethanol, 1-propanol, or 2-methylpropan-1-ol adsorption as well as assess experimental reproducibility for another 50 systems with these adsorbates, 1-butanol or 2-phenylethan-1-ol. Our analysis indicates that ∼20% of reported adsorption isotherms for alcohols are outliers, an observation that is similar to earlier analyses of CO2 adsorption experiments. We compare a variety of replicate experiments using metal–organic framework adsorbents with predictions from molecular simulations using generic force fields in order to examine the ability of these simulations to predict alcohol adsorption in these materials.