Force Field Parameters Research Articles

AutoParams: An Automated Web-Based Tool To Generate Force Field Parameters for Molecular Dynamics Simulations.

Many research questions benefit from molecular dynamics simulations to observe the motions and conformations of molecules over time, which rely on force fields that describe sets of common molecules by category. With the increase of importance for large data sets used in machine learning and growing computational efficiency, the ability to rapidly create large numbers of force field inputs is of high importance. Unusual molecules, such as nucleotide analogues, functionalized carbohydrates, and modified amino acids, are difficult to describe consistently using standard force fields, requiring the development of custom parameters for each unique molecule. While these parameters may be created by individual users, the process can become time-consuming or may introduce errors that may not be immediately apparent. We present an open-source automated parameter generation service, AutoParams, which requires minimal input from the user and creates useful Amber force field parameter sets for most molecules, particularly those that combine molecular types (e.g., a carbohydrate functionalized with a benzene). We include hierarchical atom-typing logic that makes it straightforward to expand with additional force fields and settings, and options for creating monomers in polymers, such as functionalized amino acids. It can be straightforwardly linked to any charge generation program and currently has interfaces to Psi4, PsiRESP, and TeraChem. It is open source and is available via GitHub. It includes error checking and testing protocols to ensure the parameters will be sufficient for subsequent molecular dynamics simulations and streamlines the creation of force field databases.

Atomistic molecular simulations of Aβ-Zn conformational ensembles.

The amyloid-forming Aβ peptide is able to interact with metal cations to form very stable complexes that influence fibril formation and contribute to the onset of Alzheimer's disease. Multiple structures of peptides derived from Aβ in complex with different metals have been resolved experimentally to provide an atomic-level description of the metal-protein interactions. However, Aβ is intrinsically disordered, and hence more amenable to an ensemble description. Molecular dynamics simulations can now reach the timescales needed to generate ensembles for these type of complexes. However, this requires accurate force fields both for the protein and the protein-metal interactions. Here we use state-of-the-art methods to generate force field parameters for the Zn(II) cations in a set of complexes formed by different Aβ variants and combine them with the Amber99SB*-ILDN optimized force field. Upon comparison of NMR experiments with the simulation results, further optimized with a Bayesian/Maximum entropy approach, we provide an accurate description of the molecular ensembles for most Aβ-metal complexes. We find that the resulting conformational ensembles are more heterogeneous than the NMR models deposited in the Protein Data Bank.

Interfacial heat and mass transfer at silica/binary molten salt interface from deep potential molecular dynamics

Interfacial heat and mass transfer properties at molten salt/solid interfaces are crucial for the study of heat storage/transfer properties of molten salt nanocomposite materials as well as the microscopic mechanism of thermophysical property enhancement, but accurate force field parameters for describing molten salt-solid interactions are still lacking. This study has utilized a workflow that could meet the demand of high accuracy and efficiency in molecular dynamics (MD) simulations of molten salt/solid interface with the deep potentials (DPs) trained by deep learning (DL), using SiO2/LiCl-KCl interface as a model system. In terms of the short-ranged polarizability and long-ranged correlations of ions, DPs can give accurate description of potential energy surface over wide temperature range at the level of ab initio calculations. Further analysis on interfacial thermal resistance (ITR) and thermal conductivity shows that the slowing down of heat transfer is related to the disordered microstructure of molten salt ions near the SiO2 surfaces, which also leads to larger ITR. For the mass transfer of molten salt ions on the SiO2 surfaces, the more active ionic diffusion and permeation through the solid can be observed due to the weaker adsorption between them, which is ascribed primarily to the high temperature. The workflow, of which the feasibility has been verified for molten salt/solid interfaces in this work with rigorous modeling, will be used for building accurate interatomic interaction models and calculating thermophysical properties for various complex interfacial systems containing molten salts. The influence of interfacial microstructure on heat and mass transfer will provide theoretical support for the application of molten salts in energy industry.

Upgrading of the general AMBER force field 2 for fluorinated alcohol biosolvents: A validation for water solutions and melittin solvation.

The standard GAFF2 force field parameterization has been refined for the fluorinated alcohols 2,2,2-trifluoroethanol (TFE), 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP), and 1,1,1,3,3,3-hexafluoropropan-2-one (HFA), which are commonly used to study proteins and peptides in biomimetic media. The structural and dynamic properties of both proteins and peptides are significantly influenced by the biomimetic environment created by the presence of these cosolvents in aqueous solutions. Quantum mechanical calculations on stable conformers were used to parameterize the atomic charges. Different systems, such as pure liquids, aqueous solutions, and systems formed by melittin protein and cosolvent/water solutions, have been used to validate the new models. The calculated macroscopic and structural properties are in agreement with experimental findings, supporting the validity of the newly proposed models.

Chitosan Polysaccharides from a Polarizable Multiscale Approach.

We report simulations of chitosan polysaccharides in the aqueous phase, at infinite dilute conditions and zero ionic strength. Those simulations are performed by means of a polarizable multiscale modeling scheme that relies on a polarizable all atom force field to model solutes and on a polarizable solvent coarse grained approach. Force field parameters are assigned only from quantum chemistry ab initio data. We simulate chitosan monomer units, dimers and 50-long chains. Regarding the 50-long chains we simulate three sets of ten randomly built chain replica at three different pH conditions (corresponding to different chain protonation states, the chain degree of deacetylation is 85%). Our simulations show the persistence length of 50-long chitosan chains at strong acidic conditions (pH <5) to be 24 ± 2 nm (at weak/negligible ionic strength conditions), and to be 1 order of magnitude shorter at usual pH conditions. Our simulation data support the most recent simulation and experimental studies devoted to chitosan polysaccharides in the aqueous phase.

Machine Learning-Guided Adaptive Parametrization for Coupling Terms in a Mixed United-Atom/Coarse-Grained Model for Diphenylalanine Self-Assembly in Aqueous Ionic Liquids.

Precise regulation of the peptide self-assembly into ordered nanostructures with intriguing properties has attracted intense attention. However, predicting peptide assembly at atomic resolution is a challenge due to both the structural flexibility of peptides and the associated huge computational costs. A machine learning-guided adaptive parametrization method was proposed for developing a mixed atomic and coarse-grained (CG) model through a multiobjective optimization strategy. Our model incorporates the united-atom (UA) model for diphenylalanine (P) and the polarizable electrostatic-variable coarse-grained (VaCG) model for aqueous ionic liquid [BMIM]+[BF4]- solution. In this mixed model, the coupling van der Waals (vdW) interaction is addressed by introducing virtual sites (VS) in the UA model to interact with solvent CG beads. The coupling parameters, including the electrostatic parameter and vdW parameters, are automatically optimized through ML-guided adaptive parametrization. The performance of this model was tested by some microstructural properties, e.g., the average number of P-P intermolecular hydrogen bonds (HBs) and radius distribution functions (RDFs) between P and different fragments of IL, in comparison with all-atom (AA) simulations. The computational cost is significantly reduced using such a parametrization scheme, which could search tens of thousands of force-field parameter sets, while needing only a small fraction of them to be assessed with molecular dynamics (MD) simulations. We used such a mixed resolution model to investigate the self-assembly in IL-water mixtures with variants of IL concentration (X). The long-range-ordered fibril structure is formed in a pure water system (X = 0). With an increase of IL concentrations, the formation of an ordered self-assembly nanostructure is prohibited, instead forming branched fibril at X = 2 mol % or amorphous aggregates when X > 10 mol %, resulting from the interplay between π-stacking and HB interactions between P and IL. The qualitative agreement between the simulated structures and the observed morphologies in experiments indicates the applicability of ML-guided parametrization strategy in the study of complex systems, such as polymers, lipid bilayers, and polysaccharides.

Density functional and force field modeling of multi-walled WS2 nanotubes

A technique for constructing force fields based on the use of genetic algorithms is proposed. It is used to generate a force field designed to simulate multi-walled WS2 nanotubes, which is beyond the capabilities of ab initio methods. The resulting force field parameterization was successfully tested on single, double, and triple-walled nanotubes, which structure was determined using density functional calculations. The developed force field was applied to model the structure and stability of chiral and achiral multi-walled WS2 nanotubes. The interwall distances found by simulation are in good agreement with the results of recent measurements of these parameters for synthesized nanotubes. An analysis was made of the deviation of the shape of nanotubes from the cylindrical pattern.

Exploring the Barriers in the Aggregation of a Hexadecameric Human Prion Peptide through the Markov State Model.

The prefibrillar aggregation kinetics of prion peptides are still an enigma. In this perspective, we employ atomistic molecular dynamics (MD) simulations of the shortest human prion peptide (HPP) (127GYMLGS132) at various temperatures and peptide concentrations and apply the Markov state model to determine the various intermediates and lag phases. Our results reveal that the natural mechanism of prion peptide self-assembly in the aqueous phase is impeded by two significant kinetic barriers with oligomer sizes of 6-9 and 12-13 peptides, respectively. The first one is the aggregation of unstructured lower-order oligomers, and the second is fibril nucleation, which impedes the further growth of prion aggregates. Among these two activation barriers, the second one is found to be dominant irrespective of the increase in temperature and peptide concentration. These lag phases are captured in all three different force-field parameters, namely, GROMOS-54a7, AMBER-99SB-ILDN, and CHARMMS 36m, at different concentrations. The GROMOS-54a7 and AMBER-99SB-ILDN force fields showed a comparatively higher percentage of β-sheet formation in the metastable aggregate that evolved during the aggregation process. In contrast, the CHARMM-36m force field showed mostly coil or turn conformations. The addition of a novel catecholamine derivative (naphthoquinone dopamine (NQDA)) arrests the aggregation process between the lag phases by increasing the activation barrier for the Lag1 and Lag2 phases in all of the force fields, which further validates the existence of these lag phases. The preferential binding of NQDA with the peptides increases the hydration of peptides and eventually disrupts the organized morphology of prefibrillar aggregates. It reduces the dimer dissociation energy by -24.34 kJ/mol.

Force Field Parameters for Ammonium Perchlorate Validated Using Surface Energies and Applied to Interactions with Polymer Binder

Force Field Parameters for Ammonium Perchlorate Validated Using Surface Energies and Applied to Interactions with Polymer Binder

Distribution and Transport of CO2 in Hyperbranched Poly(ethylenimine)-Loaded MCM-41: A Molecular Dynamics Simulation Approach.

Fossil fuel use is accelerating climate change, driving the need for efficient CO2 capture technologies. Solid adsorption-based direct air capture (DAC) of CO2 has emerged as a promising mode for CO2 removal from the atmosphere due to its potential for scalability. Sorbents based on porous supports incorporating oligomeric amines in their pore spaces are widely studied. In this study, we investigate the intermolecular interactions and adsorption of CO2 and H2O molecules in hyperbranched poly(ethylenimine) (HB-PEI) functionalized MCM-41 systems to understand the distribution and transport of CO2 and H2O molecules. Density Functional Theory (DFT) is employed to compute the binding energies of CO2 and H2O molecules with HB-PEI and MCM-41 and to develop force field parameters for molecular dynamics (MD) simulations. The MD simulations are performed to examine the distribution and transport of CO2 and H2O molecules as a function of the HB-PEI content. The study finds that an HB-PEI content of approximately 34 wt % is thermodynamically favorable, with an upper limit of HB-PEI loading between 45 and 50 wt %. The distribution of CO2 and H2O molecules is primarily determined by their adsorptive binding energies, for which H2O molecules dominate the occupation of binding sites due to their strong affinity with silanol groups on MCM-41 and amine groups of HB-PEI. The HB-PEI content has a considerable impact on the diffusion of CO2 and H2O molecules. Furthermore, a larger number of water molecules (higher relative humidity) reduces the correlation of CO2 with the MCM-41 pore surface while enhancing the correlation of CO2 with the amine groups of the HB-PEI. Overall, the presence of H2O molecules increases the CO2 correlation with the amine groups and also the CO2 transport within HB-PEI-loaded MCM-41, meaning that the presence of H2O enhances the CO2 capture in the HB-PEI-loaded MCM-41. These findings are consistent with experimental observations of the impact of increasing humidity on CO2 capture while providing new, molecular-level explanations for the macroscopic experimental findings.

Accurate Calculation of Solvation Properties of Lithium Ions in Nonaqueous Solutions.

We perform all-atom molecular dynamics simulations of lithium triflate in 1,2-dimethoxyethane using six different literature force fields. This system is representative of many experimental studies of lithium salts in solvents and polymers. We show that multiple historically common force fields for lithium ions give qualitatively incorrect results when compared with those from experiments and quantum chemistry calculations. We illustrate the importance of correctly selecting force field parameters and give recommendations on the force field choice for lithium electrolyte applications.

Development of the reactive force field and silicon dry/wet oxidation process modeling

We developed the Si/O/H reactive force field parameter set and applied to silicon dry/wet oxidation process to understand the underlying physics of the thermal oxidation of the Si(100) surface. Through a systematic development of the Si/O parameter using the experimental data of the volumes of the SiO2 crystal as a reference, we reproduced the same result over the temperature range of 300–1300 K. With strategic tunings of parameters related to Si/O/H system, we carried out the simulation comparing the wet-and dry processes. A significant acceleration of the oxide film growth seen in the ‘in-situ-steam-generation (ISSG)’ is successfully represented. These properties of our model imply its applicability in wider scope. We compare our results with those obtained by using parameter set recently developed by other authors. Investigating the configuration of atoms near the interface of the SiO2 film, our model is found to be able to study the role of hydrogen atoms for the ISSG acceleration.

A Comparative Analysis of Force Fields of Drug-Like Molecules: Omeprazole, Favipiravir and Amoxicillin by using Bonded and Non-Bonded Potential Distributions

This research aims to compare and analyze the force field parameters of drug-like compounds generated by the online servers CGenFF, SwissParam, and LigParGen. CHARMM27, OPLS-AA, and CHARMM36 force fields of amoxicillin, favipiravir, and omeprazole have been examined by bonded and non-bonded energy distributions of the potential function. The local terms of the force field function are bond length, bond angle, and dihedral potentials, while the non-local terms are van der Waals and pairwise electrostatic interactions. The parabolic curves of bond length potential appear to internally bend because of the larger values of force constants. The bond length and angle energies are lowest at reference values for each of the corresponding atom pairs in the molecules. The higher values of the bending force constant positively deflect the sinusoidal curve from the equilibrium position according to the dihedral angle energy distribution. The Lennard-Jones interaction exhibits the same repellent nature at closer ranges and the same attracting nature at farther ranges whereas a mildly differentiated interaction is seen at the intermediate state as a result of changing well-depth parameters. Depending on the size of the optimized partial charges, it is discovered in electrostatic interaction that the distributions of end-to-end lengths of identical atom pairs are more exponentially skewed from one another. The main cause of inconsistency in the results of MD simulations for the same protein-ligand system is due to the shifted topology and parameters.

Calculations of Absolute Solvation Free Energies with Transformato─Application to the FreeSolv Database Using the CGenFF Force Field.

We recently introduced transformato, an open-source Python package for the automated setup of large-scale calculations of relative solvation and binding free energy differences. Here, we extend the capabilities of transformato to the calculation of absolute solvation free energy differences. After careful validation against the literature results and reference calculations with the PERT module of CHARMM, we used transformato to compute absolute solvation free energies for most molecules in the FreeSolv database (621 out of 642). The force field parameters were obtained with the program cgenff (v2.5.1), which derives missing parameters from the CHARMM general force field (CGenFF v4.6). A long-range correction for the Lennard-Jones interactions was added to all computed solvation free energies. The mean absolute error compared to the experimental data is 1.12 kcal/mol. Our results allow a detailed comparison between the AMBER and CHARMM general force fields and provide a more in-depth understanding of the capabilities and limitations of the CGenFF small molecule parameters.

Vanadium complex as a potential modulator of the autophagic mechanism through proteins PI3K and ULK1: development, validation and biological implications of a specific force field for [VO(bpy)2Cl]

The modulation of autophagy has been presented as a very useful strategy in anticancer treatments. In this sense, the vanadium complex (VC) bis(2,2'-bipyridine)chlorooxovanadium(IV), [VO(bpy)2Cl], is known for its ability to induce autophagy in triple-negative breast cancer cells (TNBC). An excellent resource to investigate the role of VC in the induction of autophagy is to make use of Molecular Dynamics (MD) simulations. However, until now, the scarcity of force field parameters for the VC prevented a reliable analysis. The autophagy signaling pathway starts with the PI3K protein and ends with ULK1. Therefore, in the first stage of this work, we developed a new AMBER force field for the VC (VCFF) from a quantum structure, obtained by DFT calculations. In the second stage, the VCFF was validated through structural analyses. From this, it was possible to investigate, through docking and MD (200 ns), the performance of the PI3K-VC and ULK1-VC systems (third stage). The analyses of this last stage involved RMSD, hydrogen bonds, RMSF and two pathways for the modulation of autophagy. In general, this work fills in the absence of force field parameters (FF) for VC by proposing an efficient and new FF, in addition to investigating, at the molecular level, how VC is able to induce autophagy in TNBC cells. This study encourages new parameterizations of metallic complexes and contributes to the understanding of the duality of autophagic processes. Communicated by Ramaswamy H. Sarma

Development, Validation, and Applications of Nonbonded Interaction Parameters between Coarse-Grained Amino Acid and Water Models.

Interactions between amino acids and water play an important role in determining the stability and folding/unfolding, in aqueous solution, of many biological macromolecules, which affects their function. Thus, understanding the molecular-level interactions between water and amino acids is crucial to tune their function in aqueous solutions. Herein, we have developed nonbonded interaction parameters between the coarse-grained (CG) models of 20 amino acids and the one-site CG water model. The nonbonded parameters, represented using the 12-6 Lennard Jones (LJ) potential form, have been optimized using an artificial neural network (ANN)-assisted particle swarm optimization (PSO) (ANN-assisted PSO) method. All-atom (AA) molecular dynamics (MD) simulations of dipeptides in TIP3P water molecules were performed to calculate the Gibbs hydration free energies. The nonbonded force-field (FF) parameters between CG amino acids and the one-site CG water model were developed to accurately reproduce these energies. Furthermore, to test the transferability of these newly developed parameters, we calculated the hydration free energies of the analogues of the amino acid side chains, which showed good agreement with reported experimental data. Additionally, we show the applicability of these models by performing self-assembly simulations of peptide amphiphiles. Overall, these models are transferable and can be used to study the self-assembly of various biomaterials and biomolecules to develop a mechanistic understanding of these processes.

Optimizing molecular potential models by imposing kinetic constraints with path reweighting.

Empirical force fields employed in molecular dynamics simulations of complex systems are often optimized to reproduce experimentally determined structural and thermodynamic properties. In contrast, experimental knowledge about the interconversion rates between metastable states in such systems is hardly ever incorporated in a force field due to a lack of an efficient approach. Here, we introduce such a framework based on the relationship between dynamical observables, such as rate constants, and the underlying molecular model parameters using the statistical mechanics of trajectories. Given a prior ensemble of molecular dynamics trajectories produced with imperfect force field parameters, the approach allows for the optimal adaption of these parameters such that the imposed constraint of equally predicted and experimental rate constant is obeyed. To do so, the method combines the continuum path ensemble maximum caliber approach with path reweighting methods for stochastic dynamics. When multiple solutions are found, the method selects automatically the combination that corresponds to the smallest perturbation of the entire path ensemble, as required by the maximum entropy principle. To show the validity of the approach, we illustrate the method on simple test systems undergoing rare event dynamics. Next to simple 2D potentials, we explore particle models representing molecular isomerization reactions and protein-ligand unbinding. Besides optimal interaction parameters, the methodology gives physical insights into what parts of the model are most sensitive to the kinetics. We discuss the generality and broad implications of the methodology.

Atomic mechanisms of long-term pyrolysis and gas production in cellulose-oil composite for transformer insulation

Cellulose-oil composite (COC) insulating materials are widely used in the transformer owing to their excellent physical and chemical properties. However, long-term thermal instability of these materials severely threatens the stable operation of transformer and power system. To reveal the atomic-level mechanisms responsible for pyrolysis and gas production in COCs, reactive molecular dynamics (RMD) simulations are performed, and calculation results are compared with data from dissolved and evolved gas tests of thermally decomposed materials. First, force field parameters and a molecular model optimization method based on the experimental data-driven strategy are introduced. It is verified that this method and force field offer significant advantages over the classical forms in the simulation of COC pyrolysis. Then, the new parameters and model are used to investigate the long-term pyrolysis and gas production processes in the COC. By constructing the molecular pathways for characteristic gases, namely, CH4, C2H4, and C2H2, it is found that the recombination of CH3•, •CH2•, and H• radicals, which decomposed from the COC, contributes to the formation of CH4 and C2H2, whereas C2H4 can be directly produced via COC decomposition. A higher pyrolysis temperature inhibits the recombination process of radicals and reduces the volume percentages (VPs) of CH4 and C2H2 but promotes the decomposition process and improves the VP of C2H4. This study not only provides insight into the gas production of COCs in transformer but also paves a way to understand long-term pyrolysis of any other materials using MD simulations.

Host Dynamics under General-Purpose Force Fields.

Macrocyclic hosts as prototypical receptors to gaseous and drug-like guests are crucial components in pharmaceutical research. The external guests are often coordinated at the center of these macromolecular containers. The formation of host-guest coordination is accompanied by the broken of host-water and host-ion interactions and sometimes also involves some conformational rearrangements of the host. A balanced description of various components of interacting terms is indispensable. However, up to now, the modeling community still lacks a general yet detailed understanding of commonly employed general-purpose force fields and the host dynamics produced by these popular selections. To fill this critical gap, in this paper, we profile the energetics and dynamics of four types of popular macrocycles, including cucurbiturils, pillararenes, cyclodextrins, and octa acids. The presented investigations of force field definitions, refitting, and evaluations are unprecedently detailed. Based on the valuable observations and insightful explanations, we finally summarize some general guidelines on force field parametrization and selection in host-guest modeling.

Molecular Modeling of Water-in-Salt Electrolytes: A Comprehensive Analysis of Polarization Effects and Force Field Parameters in Molecular Dynamics Simulations.

Accurate modeling of highly concentrated aqueous solutions, such as water-in-salt (WiS) electrolytes in battery applications, requires proper consideration of polarization contributions to atomic interactions. Within the force field molecular dynamics (MD) simulations, the atomic polarization can be accounted for at various levels. Nonpolarizable force fields implicitly account for polarization effects by incorporating them into their van der Waals interaction parameters. They can additionally mimic electron polarization within a mean-field approximation through ionic charge scaling. Alternatively, explicit polarization description methods, such as the Drude oscillator model, can be selectively applied to either a subset of polarizable atoms or all polarizable atoms to enhance simulation accuracy. The trade-off between simulation accuracy and computational efficiency highlights the importance of determining an optimal level of accounting for atomic polarization. In this study, we analyze different approaches to include polarization effects in MD simulations of WiS electrolytes, with an example of a Na-OTF solution. These approaches range from a nonpolarizable to a fully polarizable force field. After careful examination of computational costs, simulation stability, and feasibility of controlling the electrolyte properties, we identify an efficient combination of force fields: the Drude polarizable force field for salt ions and non-polarizable models for water. This cost-effective combination is sufficiently flexible to reproduce a broad range of electrolyte properties, while ensuring simulation stability over a relatively wide range of force field parameters. Furthermore, we conduct a thorough evaluation of the influence of various force field parameters on both the simulation results and technical requirements, with the aim of establishing a general framework for force field optimization and facilitating parametrization of similar systems.