Partial Charge Model Research Articles

Earth Mover's Charge Transfer Distance: A General and Robust Approach for Describing Excited State Locality.

A novel approach for assessing the extent of electron displacement in optical transitions is proposed by implementing the Earth Mover's Distance (EMD) method, which quantifies the spatial dissimilarity between ground and excited state electron density distributions. In contrast to previous descriptors, this index provides a representative and intuitively understandable distance under a robust and computationally efficient scheme for all possible forms of locality, even in the most difficult to dissect topological cases. The theoretical differences among the existing indices and our method are first illustrated with the help of a simplified model system, followed by a benchmarking of several partial atomic charge models using experimentally relevant push-pull compounds with diverse symmetries. These same molecules are finally employed to further demonstrate the principal advantages of the EMD index and its capabilities in rationalizing charge transfer phenomena.

Atomic partial charge model in chemistry: chemical accuracy of theoretical approaches for diatomic molecules

Abstract Atomic partial charges cannot be physically measured but they play a significant role in many chemical theories and theoretical models. Therefore, they are, evaluated from experimentally acquired properties or calculated by quantum chemistry computational methods. This study is focused on determining chemical accuracy of various theoretical methods of computing atomic partial charges based on quantum chemistry. Values of gas-phase atomic partial charges were acquired by Mulliken (MUL) population analysis, natural bond analysis (NBO), Merz-Singh-Kollman (MSK) scheme, and atomic polar tensor (APT) charges computed considering Density Functional Theory and ab initio Møller-Plesset up to the second order levels. Correlations between the calculated values were determined by principal component analysis (PCA) and further confirmed by linear regression. The best agreement between experimentally evaluated atomic partial charges and theoretical values was obtained with the MSK scheme.

Combined 3D-QSAR, molecular docking and dynamics simulations studies to model and design TTK inhibitors.

Tyrosine threonine kinase (TTK) is the key component of the spindle assembly checkpoint (SAC) that ensures correct attachment of chromosomes to the mitotic spindle and thereby their precise segregation into daughter cells by phosphorylating specific substrate proteins. The overexpression of TTK has been associated with various human malignancies, including breast, colorectal and thyroid carcinomas. TTK has been validated as a target for drug development, and several TTK inhibitors have been discovered. In this study, ligand and structure-based alignment as well as various partial charge models were used to perform 3D-QSAR modelling on 1H-Pyrrolo[3,2-c] pyridine core containing reported inhibitors of TTK protein using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches to design better active compounds. Different statistical methods i.e., correlation coefficient of non-cross validation (r2), correlation coefficient of leave-one-out cross-validation (q2), Fisher's test (F) and bootstrapping were used to validate the developed models. Out of several charge models and alignment-based approaches, Merck Molecular Force Field (MMFF94) charges using structure-based alignment yielded highly predictive CoMFA (q2 = 0.583, Predr2 = 0.751) and CoMSIA (q2 = 0.690, Predr2 = 0.767) models. The models exhibited that electrostatic, steric, HBA, HBD, and hydrophobic fields play a key role in structure activity relationship of these compounds. Using the contour maps information of the best predictive model, new compounds were designed and docked at the TTK active site to predict their plausible binding modes. The structural stability of the TTK complexes with new compounds was confirmed using MD simulations. The simulation studies revealed that all compounds formed stable complexes. Similarly, MM/PBSA method based free energy calculations showed that these compounds bind with reasonably good affinity to the TTK protein. Overall molecular modelling results suggest that newly designed compounds can act as lead compounds for the optimization of TTK inhibitors.

Influence of Temperature and Pressure on the Lattice Constant of SrTiO3 Perovskite by the Statistical Moment Method with Improved Interatomic Potential

Temperature and pressure dependence of lattice constants of a cubic Strontium Titanate (SrTiO3) has been investigated using the statistical moment method. The lattice constants at various temperatures is derived in closed analytic form by including the anharmonic effects of the lattice vibrations explicitly. The potential with the partial charge model and Morse function is used. The numerical lattice constants at high temperatures by the statistical moment method are in good and reasonable agreement with the other theories and the experimental data. Variations of the lattice parameter of SrTiO3 with the temperature are obtained at 1 atm, 8.2 GPa, and 15.2 GPa. Increasing of the lattice constants with increasing temperature is due to enhancing atomic anharmonic fluctuations in SrTiO3 lattice crystal at higher temperature. A decrease of the lattice constants with increasing pressure can be demonstrated by the reduction of atomic vibrations in SrTiO3 crystal lattice at higher pressures.

Adsorption behavior of phosphate on 2-L ferrihydrite adsorbent predicted by partial charge model under varying pH conditions

Adsorption behavior of phosphate on 2-L ferrihydrite adsorbent predicted by partial charge model under varying pH conditions

Study of the thermodynamic properties of SrTiO3 perovskite under pressure by the statistical moment method with the improved interatomic potential

The pressure dependence of the thermodynamic quantities of cubic SrTiO3 perovskite has been going based on the statistical moment method. We obtain analytic formulas of free energy, lattice parameter, thermal lattice expansion coefficient, heat capacity Cv, and Cp at various pressure. The potential with the partial charge model and functions of Demontis and Pedone is used, it allows calculating the numerical thermodynamic quantities of SrTiO3 at specific pressure and temperature. The numerical quantities of SrTiO3 have been calculated up to 18 GPa and agreed well with the previous experimental and theoretical results. It has a good potential to develop the statistical moment method for investigating the pressure effects on the thermodynamic quantities of the perovskite–structure materials.

Study of the thermodynamic properties of SrTiO3 perovskite by the statistical moment method with improved interatomic potential

We study the thermodynamic properties of cubic SrTiO3 perovskite going beyond the statistical moment method within approximation up to the fourth-order of the power moments of the atomic displacements. The analytic expressions of the thermodynamic quantities, such as the free energy, thermal expansion coefficients, and heat capacity at the constant volume and constant pressure of SrTiO3, are obtained. The potential with the partial charge model and functions of Demontis and Pedone is used to calculate the numerical thermodynamic quantities of SrTiO3 from room temperature up to high temperature. The numerical results of the thermodynamic quantities of SrTiO3 by the statistical moment method are in good agreement with the previous theoretical and experimental results for a wide temperature range. Our research also shows that the anharmonic effects of the lattice fluctuations affect the thermodynamic properties of SrTiO3 dominantly. It has a good potential to develop the statistical moment method for investigating the temperature effects on the thermodynamic quantities of the perovskite–structure materials.

Phase modulation kinetics in TiO2 by manipulating pH: A dynamic of photoactivity at different combination of phase and pH

A fundamental understanding of dynamism of charge-transfer characteristic at different phase and pH combination play an significant role for the development of highly efficient light harvesting photocatalyst. Herein, we describe the phase modulation at different pH and its relationship with the photocatalytic activities is emphasized. The pH of the precursor solution allows to control phase and size of TiO2 nanoparticles at constant temperature. The phase modulation at different pH proceeds through hydrolysis and polycondensation based on partial charge model. Rutile phase were formed at pH 3 of precursor solution. Anatase phase were formed at pH 9 while the mixed phase Anatase/Rutile formed at pH 5. A complementary role of phases on the catalytic activity of TiO2 under UV and visible irradiance was established using pseudo first order kinetics. This study was supported by XRD, HR-TEM, UV-DRS, XPS and FTIR analysis. This result gives a new strategy for controlled phase transition offset and size of TiO2 nanoparticles by manipulating pH.

End-to-end differentiable construction of molecular mechanics force fields.

Molecular mechanics (MM) potentials have long been a workhorse of computational chemistry. Leveraging accuracy and speed, these functional forms find use in a wide variety of applications in biomolecular modeling and drug discovery, from rapid virtual screening to detailed free energy calculations. Traditionally, MM potentials have relied on human-curated, inflexible, and poorly extensible discrete chemical perception rules (atom types) for applying parameters to small molecules or biopolymers, making it difficult to optimize both types and parameters to fit quantum chemical or physical property data. Here, we propose an alternative approach that uses graph neural networks to perceive chemical environments, producing continuous atom embeddings from which valence and nonbonded parameters can be predicted using invariance-preserving layers. Since all stages are built from smooth neural functions, the entire process-spanning chemical perception to parameter assignment-is modular and end-to-end differentiable with respect to model parameters, allowing new force fields to be easily constructed, extended, and applied to arbitrary molecules. We show that this approach is not only sufficiently expressive to reproduce legacy atom types, but that it can learn to accurately reproduce and extend existing molecular mechanics force fields. Trained with arbitrary loss functions, it can construct entirely new force fields self-consistently applicable to both biopolymers and small molecules directly from quantum chemical calculations, with superior fidelity than traditional atom or parameter typing schemes. When adapted to simultaneously fit partial charge models, espaloma delivers high-quality partial atomic charges orders of magnitude faster than current best-practices with low inaccuracy. When trained on the same quantum chemical small molecule dataset used to parameterize the Open Force Field ("Parsley") openff-1.2.0 small molecule force field augmented with a peptide dataset, the resulting espaloma model shows superior accuracy vis-á-vis experiments in computing relative alchemical free energy calculations for a popular benchmark. This approach is implemented in the free and open source package espaloma, available at https://github.com/choderalab/espaloma.

Effect of the mixture composition of C4mimBF4/acetonitrile on the charge transfer in Coumarin 153: DFT and TD-DFT analysis

In this work, we studied by means of density functional theory (DFT) and time-dependent DFT(TD-DFT) using the effect of the mixture composition C4mimBF4/acetonitrile on the charge transfer in Coumarin 153(C153) after photoexcitation. The mixture composition was characterize by their corresponding static dielectric constant εm. The PBE0 and M06-2X functionals combined with linear response (LR) and state specific (SS) solvation schemes were used to obtain various electronic properties of C153 in both ground and excited states. Our results show that the calculated fluorescence Stoke shift, using the state specific solvation scheme correlates well with the corresponding experimental data obtained for C153 dissolved in other solvents have the same static dielectric constant as of the C4mimBF4/acetonitrile mixture. The charge transfer was quantified using descriptors such as charge qCT, distance dCT, and the dipole moment μCT between the ground and the excited state. These descriptors were calculated based on four different partial atomic charge models, namely Mulliken, Natural Populations Analysis, Hirshfeld, and Merz–Kollman. The charge transfer also was quantified using descriptors based on the electrostatic surface potential namely the polarity index. Both PBE0 and M06-2X functionals combined with the Linear Response solvation scheme result in a systematic increase of the qCT, dCT, and μCT with increasing εm, while they decrease for most of the partial atomic charge models when the State Specific solvation scheme is used. This later result points out that this solvation scheme is not suitable for the description of the excited state of C153 in this mixture. Our results show that the extent of change of these descriptors is small and indicates that the effect of the mixture composition on the charge transfer in C153 is weak.

Why Lithium Ions Stick to Some Anions and Not Others.

Designing battery electrolytes for lithium-ion batteries has been a topic of extensive research for decades. The ideal electrolyte must have a large conductivity as well as high Li+ transference number. The conductivity is very sensitive to the nature of the anions and dynamical correlations between ions. For example, lithium bis(trifluoromethane)sulfonimide (LiTFSI) has a large conductivity, but the chemically similar lithium trifluoromethanesulfonate (LiOTf) shows poor conductivity. In this work, we study the binding of Li+ to these anions in an ethylene carbonate (EC) solvent using enhanced sampling metadynamics. The evaluated free energies display a large dissociation barrier for LiOTf compared to LiTFSI, suggesting long-lived ion-pair formation in the former but not the latter. We probe these observations via unbiased molecular dynamics simulations and metadynamics simulations of TFSI with a hypothetical OTF-like partial charge model indicating an electrostatic origin for those differences. Our results highlight the deleterious impact of sulfonate groups in lithium-ion battery electrolytes and provide a new basis for the assessment of electrolyte designs.

SAMPL7: Host-guest binding prediction by molecular dynamics and quantum mechanics.

Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges provide routes to compare chemical quantities determined using computational chemistry approaches to experimental measurements that are shared after the competition. For this effort, several computational methods have been used to calculate the binding energies of Octa Acid (OA) and exo-Octa Acid (exoOA) host-guest systems for SAMPL7. The initial poses for molecular dynamics (MD) were generated by molecular docking. Binding free energy calculations were performed using molecular mechanics combined with Poisson-Boltzmann or generalized Born surface area solvation (MMPBSA/MMGBSA) approaches. The factors that affect the utility of the MMPBSA/MMGBSA approaches including solvation, partial charge, and solute entropy models were also analyzed. In addition to MD calculations, quantum mechanics (QM) calculations were performed using several different density functional theory (DFT) approaches. From SAMPL6 results, B3PW91-D3 was found to overestimate binding energies though it was effective for geometry optimizations, so it was considered for the DFT geometry optimizations in the current study, with single-point energy calculations carried out with B2PLYP-D3 with double-, triple-, and quadruple-ζ level basis sets. Accounting for dispersion effects, and solvation models was deemed essential for the predictions. MMGBSA and MMPBSA correlated better to experiment when used in conjunction with an empirical/linear correction.

Heat and moisture resistance of divalent metals substituted La-Hexaaluminates prepared by reverse microemulsion

Lanthanum hexaaluminates (LHAs) substituted with divalent metals (Mg, Zn) were successfully prepared by the reverse microemulsion (RM) method and high-temperature treatment. Phase composition, microstructure, porosity characteristics, and their thermal evolution were investigated using X-ray diffractometry, scanning electron microscopy, N2 isothermal sorption and thermogravimetry-differential scanning calorimetry, respectively. The thermal stability of substituted hexaaluminates was also evaluated in both dry and moisture atmosphere at 1200-1600 °C. Experimental results showed that the RM method promoted the formation of pure and well crystallized magnetoplumbite hexaaluminates with high specific surface areas at temperatures 1100-1200 °C. For both obtained hexaaluminates, their phase composition and nanometer-sized crystallites were retained at temperature as high as 1600 °C in dry air. However, LaMgAl11O19 presented severe deterioration in flowing water vapor at 1300 °C including about 50% weight loss and the remarkable crystalline structure change, whereas the substitution of Zn enabled the LaZnAl11O19 to possess superior moisture resistance. According to the partial charge model of cations in aqueous media, a “hydrolysis-corrosion” mechanism was proposed to describe the degradation of hexaaluminates in high-temperature water vapor. It was revealed that the high-temperature moisture resistance of substituted LHAs was inversely proportional to the hydrolysis tendency of substituted metal cations.

Influence of partial charge on the material removal rate during chemical polishing

AbstractA partial charge‐based chemical polishing model has been developed, which can serve as metric for describing the relative polishing material removal rate for different combinations of slurries and workpieces. A series of controlled polishing experiments utilizing a variety of colloidal polishing slurries (SiO2, CeO2, ZrO2, MgO, Sb2O5) and optical materials [single crystals of Al2O3 (sapphire), SiC, Y3Al5O12 (YAG), CaF2, and LiB3O5 (LBO); a SiO2‐Al2O3‐P2O5‐Li2O glass ceramic (Zerodur); and glasses of SiO2:TiO2 (ULE), SiO2 (fused silica), and P2O5‐Al2O3‐K2O‐BaO (Phosphate)] was performed and its material removal rate was measured. As previously proposed by Cook (J Non‐Cryst Solids. 1990;120:152), for many polishing systems, the removal rate is governed by a series of chemical reactions which include the formation of a surface hydroxide, followed by condensation of that hydroxyl moiety with the polishing particle, and a subsequent hydrolysis reaction. The rate of condensation can often be the rate limiting step, thus it can determine the polishing material removal rate. By largely keeping the numerous other factors that influence material removal rate fixed (such as due to particle size distributions, interface interactions, pad topography, kinematics, and applied pressure), the material removal rate is shown to scale exponentially with the partial charge difference (δwp‐s) between the workpiece and polishing slurry particle for many of the slurry‐workpiece combinations indicating that condensation rate is the rate limiting step. The partial charge (δ) describes the equilibrium distribution of electron density between chemically bonded atoms and is related to the electronegativity of the atoms chemically bonded to one another. This partial charge model also explains the age‐old experimental finding of why cerium oxide is the most effective polishing slurry for chemical removal of many workpieces. Some of the slurry‐workpiece combinations that did not follow the partial charge dependence offer insight to other removal mechanisms or rate limiting reaction pathways.

Evaluation of calculated negative mode ion mobilities of small molecules in air.

Ion mobility spectrometry is a well-known technique employed for the detection and analysis of gaseous substances. In pharmaceutical applications, it is furthermore used for structural analysis of compounds, especially in combination with mass spectrometry. In this field, the comparison of calculated collision cross sections and ion mobilities of theoretic model compounds with experimental values measured with ion mobility spectrometers helps to determine the compound's structure. For positive mode ion mobility spectrometry, the calculated mobilities using the Trajectory Method show in general a deviation of 10% or less from experimental values. In this article, it was analyzed how well the calculated values reproduce the experimental values obtained with negative mode ion mobility spectrometry including symmetric and asymmetric analyte clusters. Furthermore, the influence of four different partial charge models on the results was investigated.

Assessing Ion-Water Interactions in the AMOEBA Force Field Using Energy Decomposition Analysis of Electronic Structure Calculations.

AMOEBA is a molecular mechanics force field that addresses some of the shortcomings of a fixed partial charge model, by including permanent atomic point multipoles through quadrupoles, as well as many-body polarization through the use of point inducible dipoles. In this work, we investigate how well AMOEBA formulates its non-bonded interactions, and how it implicitly incorporates quantum mechanical effects such as charge penetration (CP) and charge transfer (CT), for water-water and water-ion interactions. We find that AMOEBA's total interaction energies, as a function of distance and over angular scans for the water dimer and for a range of water-monovalent cations, agree well with an advanced density functional theory (DFT) model, whereas the water-halides and water-divalent cations show significant disagreement with the DFT result, especially in the compressed region when the two fragments overlap. We use a second-generation energy decomposition analysis (EDA) scheme based on absolutely localized molecular orbitals (ALMOs) to show that in the best cases AMOEBA relies on cancellation of errors by softening of the van der Waals (vdW) wall to balance permanent electrostatics that are too unfavorable, thereby compensating for the missing CP effect. CT, as another important stabilizing effect not explicitly taken into account in AMOEBA, is also found to be incorporated by the softened vdW interaction. For the water-halides and water-divalent cations, this compensatory approach is not as well executed by AMOEBA over all distances and angles, wherein permanent electrostatics remains too unfavorable and polarization is overdamped in the former while overestimated in the latter. We conclude that the DFT-based EDA approach can help refine a next-generation AMOEBA model that either realizes a better cancellation of errors for problematic cases like those illustrated here, or serves to guide the parametrization of explicit functional forms for short-range contributions from CP and/or CT.

Solidification and immobilization of MSWI fly ash through aluminate geopolymerization: Based on partial charge model analysis

This study presents an integrated synopsis of the solidification and immobilization mechanisms of fly ash-based geopolymers. A rational analysis of the ion reactions involved in geopolymerization was conducted using the partial charge model (PCM). The following conclusions were obtained: (1) heavy metal cations cannot be immobilized as counter cations through exchange with Na+; (2) isomorphous substitution of heavy metals in the geopolymer can be expected from the condensation reaction between the hydrolyzed heavy metal species and aluminosilicate; (3) the hydrolyzed species condensation could result in solidification and immobilization and be promoted by aluminates; and (4) a geopolymer with the highest immobilization and solidification efficiency can be obtained at an intermediate pH value. The partial charges on the framework of Si, Al, and O in the primary building blocks of aluminosilicate and heavy metal-doped aluminosilicate were confirmed through XPS and 29Si NMR spectroscopy analyses. The effects of activator dosage and types on fly ash-based geopolymers were also investigated, and the results verify the PCM analysis. A geopolymer with the highest strength was produced at an intermediate alkaline dosage. Silicate or aluminate introduced into the activator improved the strength and immobilization efficiency, and aluminate exhibited better performance. Heavy metals bound to the exchangeable or acid-soluble fraction were transformed into aluminosilicate species during geopolymerization.

Prediction of 13C NMR chemical shifts by artificial neural network. I. Partial charge model as atomic descriptor

Mulliken population analysis (MPA), Hirshfeld population analysis (HPA), Charge Model 5 (CM5) and Hu Lu Yang charge fitting method (HLY) were considered in order to reveal influence of atomic partial charges on the 13C NMR chemical shifts. The test set included seven classes of organic molecules. Partial charges of carbon atoms were obtained from quantum-chemical calculations at DFT/HISS level. Linear regressions were constructed as estimators of accuracy of each model. The best approach was shown by multivariate regression with MPA, HPA, and CM5 charges as predictors in a linear model with mean value of R2=0.8917.

A Test of Various Partial Atomic Charge Models for Computations on Diheteroaryl Ketones and Thioketones

The effective use of partial atomic charge models is essential for such purposes in molecular computations as a simplified representation of global charge distribution in a molecule and predicting its conformational behavior. In this work, ten of the most popular models of partial atomic charge are taken into consideration, and these models operate on the molecular wave functions/electron densities of five diheteroaryl ketones and their thiocarbonyl analogs. The ten models are tested in order to assess their usefulness in achieving the aforementioned purposes for the compounds in title. Therefore, the following criteria are used in the test: (1) how accurately these models reproduce the molecular dipole moments of the conformers of the investigated compounds; (2) whether these models are able to correctly determine the preferred conformer as well as the ordering of higher-energy conformers for each compound. The results of the test indicate that the Merz-Kollman-Singh (MKS) and Hu-Lu-Yang (HLY) models approximate the magnitude of the molecular dipole moments with the greatest accuracy. The natural partial atomic charges perform best in determining the conformational behavior of the investigated compounds. These findings may constitute important support for the effective computations of electrostatic effects occurring within and between the molecules of the compounds in question as well as similar compounds.

Conformational Interconversions of Amino Acid Derivatives.

Exhaustive conformational interconversions including transition structure analyses of N-acetyl-l-glycine-N-methylamide as well as its alanine, serine, and cysteine analogues have been investigated at the MP2/6-31G** level, yielding a total of 142 transition states. Improved estimates of relative energies were obtained by separately extrapolating the Hartree-Fock and MP2 energies to the basis set limit and adding the difference between CCSD(T) and MP2 results with the cc-pVDZ basis set to the extrapolated MP2 results. The performance of eight empirical force fields (AMBER94, AMBER14SB, MM2, MM3, MMFFs, CHARMM22_CMAP, OPLS_2005, and AMOEBAPRO13) in reproducing ab initio energies of transition states was tested. Our results indicate that commonly used class I force fields employing a fixed partial charge model for the electrostatic interaction provide mean errors in the ∼10 kJ/mol range for energies of conformational transition states for amino acid conformers. Modern reparametrized versions, such as CHARMM22_CMAP, and polarizable force fields, such as AMOEBAPRO13, have slightly lower mean errors, but maximal errors are still in the 35 kJ/mol range. There are differences between the force fields in their ability for reproducing conformational transitions classified according to backbone/side-chain or regions in the Ramachandran angles, but the data set is likely too small to draw any general conclusions. Errors in conformational interconversion barriers by ∼10 kJ/mol suggest that the commonly used force field may bias certain types of transitions by several orders of magnitude in rate and thus lead to incorrect dynamics in simulations. It is therefore suggested that information for conformational transition states should be included in parametrizations of new force fields.