Proton Transfer in Liquid Water II; A Semiempirical Method to Describe Chemical Reactions

Abstract

A new semiempirical method is developed to deal with the proton transfer in liquid water. In the previous work, we have shown that two- and three-body charge transfer interactions and electrostatic interactions are the most important factors to describe the potential energy surfaces (PES) of the proton transfer in liquid water [Chemical Physics 180, 239–269, 1994], In order to take account of these factors, we develop a semiempirical method imposing the principle of electronegativity equalization to the Atoms in Molecule (AIM) method. The method is free from the well-known discrepancy of the traditional AIM methods, that is, the fractional molecular charges at large molecular separation, and thus can be applied to the charge transfer reactions. Intra- and intermolecular physical quantities, such as total energies, force vectors, dipole moment vectors and intermolecular charge transfer, obtained by the present method are found to be in good agreement with those by ab initio calculation.     

On the Implementation of Friedman Boundary Conditions in Liquid Water Simulations

Abstract

We have applied the image approximation to the reaction field as suggested by H.L. Friedman [Mol. Phys., 29, 1533 (1975)] by investigating appropriate cavity sizes and system parameters for use in molecular simulations. The energy of and the structure around a central simple point charge (SPC) water molecule in a dielectric cavity was found to be in good agreement with the properties of a liquid sample. To confine the water molecules within the cavity, we introduced a short-range repulsion between a real charge and its image as the Lennard-Jones repulsive potential between oxygen atoms of the SPC potential. For a system of 65 water molecules a cavity radius of 10.45 Å is appropriate; this radius is altered to 12.00 Å for a cavity surrounding 113 molecules. The effect of the boundary is restricted to the outer-most water layer which is in contact with the dielectric continuum.     

3D‐liquid chromatography as a complex mixture characterization tool for knowledge‐based downstream process development

Knowledge‐based development of chromatographic separation processes requires efficient techniques to determine the physicochemical properties of the product and the impurities to be removed. These characterization techniques are usually divided into approaches that determine molecular properties, such as charge, hydrophobicity and size, or molecular interactions with auxiliary materials, commonly in the form of adsorption isotherms. In this study we demonstrate the application of a three‐dimensional liquid chromatography approach to a clarified cell homogenate containing a therapeutic enzyme. Each separation dimension determines a molecular property relevant to the chromatographic behavior of each component. Matching of the peaks across the different separation dimensions and against a high‐resolution reference chromatogram allows to assign the determined parameters to pseudo‐components, allowing to determine the most promising technique for the removal of each impurity. More detailed process design using mechanistic models requires isotherm parameters. For this purpose, the second dimension consists of multiple linear gradient separations on columns in a high‐throughput screening compatible format, that allow regression of isotherm parameters with an average standard error of 8%. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1283–1291, 2016     

Molecular Dynamics Study of BaB2O4 in Crystalline and Molten States

Abstract

Structural aspects of BaB₂O₄ liquids have been investigated by the molecular dynamics simulation including the determination on the parameters of the interatomic potential applicable to BaB₂O₄ in both crystalline and molten states. The structure and physical properties of BaB₂O₄ crystals were successfully reproduced by the MD simulation for both α and β phases. The simulated interference function in the liquid state was also in good agreement with the experimental one. Several interesting features on the relaxation phenomena just after melting were reproduced by the simulation that the structure factors of simulated liquid maintain the characteristic features of the original crystal structure for more than 40ps after melting, and the variation of the number of rings formed by B-O bondings was found to increase after melting.     

Networks of Water Molecules in a Proflavine Deoxydinucleoside Phosphate Complex

Abstract

Using previously reported ab-initio atom-atom potentials for the interactions of a water molecule with phosphates, sugars and bases and newly computed ab-initio atom-atom potentials for the interaction between a proflavine ion and water, we have analyzed with the Monte-Carlo Metropolis method networks of water molecules hydrating a 2:2 complex of proflavine and deoxycytidylyl-3′,5′-guanosine, recently studied with X-ray crystallography. From our simulations we have i) verified the quality of our atom-atom potentials by obtaining patterns of oxygen atoms in very good agreement with the X-ray patterns for the minor groove and in reasonable agreement in the major groove, ii) predicted the water's hydrogen atoms positions and iii) preliminarily predicted the number of water molecules not reported in the X-ray study but present in the major groove. The above data, even if preliminary, and the analyses on the energetics of the water-water, water-proflavine and water-dCpG interactions indicate that very detailed accounts on the water filaments in the above crystal can be obtained optimally by merging computer and X-ray experiments.     

Molecular properties of a bent-core nematic liquid crystal A131 by multi-level theory simulations

ABSTRACT

Multi-level theory simulations have been performed to model a number of important molecular properties of a bent-core nematic liquid crystal (LC) A131. These important properties include molecular conformations, molecular Raman spectra, differential polarisability ratios, molecular crystals packing, atomic LC structures, order parameters, and Raman depolarisation spectra. The simulations contain four theory levels, involving molecular quantum chemistry, molecular crystal packing, super cell density functional based tight binding optimisation, and super cell molecular dynamics calculations. To heat initial optimised super cell structures, molecular dynamics simulations reveal phase transitions to uniaxial and biaxial nematic phases from molecular crystals. LC atomic structures result in direct calculations on order parameters, which can be further applied to computations on Raman depolarisation spectra with differential polarisability ratios, obtained in the molecular quantum chemistry theory level. The good agreement of simulated Raman depolarisation spectra with the experiment provides a detailed analysis on the unusually low values of experimental uniaxial order parameters.     

A classical molecular approach to computer simulation of biological sorting

Steinberg's theory of sorting is modified by replacing the free energy minimization principle with dynamical equations of a molecular nature. Correct cellular sorting then follows in all cases where the mixture is in a liquid or a near-liquid state. Computer examples are described and discussed, primarily for two dimensional, but also for three dimensional, interactions.     

A Robust Water Potential Parameterisation

Abstract

We compare molecular dynamics simulation results for the properties of liquid water predicted by four novel water potential models. These models are designed as a combination of parameters taken from the dedicated but brittle TIP3P water potential, and the more flexible but less accurate parameterisations such as the Dreiding and Universal force fields. We find that a hybrid of Dreiding and TIP3P delivers the best results, yielding a density, diffusion coefficient and radial distribution function in good agreement with experiment, performing in some respects even better than the dedicated reference TIP3P model. Another Dreiding based force field predicts semi-quantitative results for the water structure and dynamics while the Universal force field based models are incapable of simulating a condensed phase of water at all, continuing to expand indefinitely. These observations are useful for selecting and designing robust water force field parameterisations that can be used for general simulation purposes.     

Molecular modeling studies,synthesis and biological evaluation of dabigatran analogues as thrombin inhibitors

In this work, 48 thrombin inhibitors based on the structural scaffold of dabigatran were analyzed using a combination of molecular modeling techniques. We generated three-dimensional quantitative structure–activity relationship (3D-QSAR) models based on three alignments for both comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) to highlight the structural requirements for thrombin protein inhibition. In addition to the 3D-QSAR study, Topomer CoMFA model also was established with a higher leave-one-out cross-validation q² and a non-cross-validation r², which suggest that the three models have good predictive ability. The results indicated that the steric, hydrophobic and electrostatic fields play key roles in QSAR model. Furthermore, we employed molecular docking and re-docking simulation explored the binding relationship of the ligand and the receptor protein in detail. Molecular docking simulations identified several key interactions that were also indicated through 3D-QSAR analysis. On the basis of the obtained results, two compounds were designed and predicted by three models, the biological evaluation in vitro (IC₅₀) demonstrated that these molecular models were effective for the development of novel potent thrombin inhibitors.     

A Study of Conformational Equilibria in Chain Molecules. I. Liquid n-Butane

Abstract

We have performed molecular dynamics simulations for liquid n-butane in order to understand liquid structures in terms of both inter- and intra-molecular interactions. Each n-butane molecule consists of four sites interacting with LJ potential and only a dihedral angle is taken into account as the internal degree of freedom. The population of gauche conformations with respect to the ideal gas state is found to increase in the liquid state. To investigate how the intermolecular interaction affects the dihedral angle distribution, we also adopt the repulsive LJ potential (RLJ) model. It is found that the nearest neighbor packing of the methyl and/or methylene groups can be approximately represented by using only the repulsive interaction. From the dihedral angle distribution, however, the rate of the shift of RLJ model to gauche is larger than that of LJ model and the attractive force also plays a significant role in the conformational equilibrium.     

Thermodynamics of the Trp‐cage miniprotein unfolding in urea

The thermodynamic properties of unfolding of the Trp‐cage mini protein in the presence of various concentrations of urea have been characterized using temperature‐induced unfolding monitored by far‐UV circular dichroism spectroscopy. Analysis of the data using a two‐state model allowed the calculation of the Gibbs energy of unfolding at 25°C as a function of urea concentration. This in turn was analyzed by the linear extrapolation model that yielded the dependence of Gibbs energy on urea concentration, i.e. the m‐value for Trp‐cage unfolding. The m‐value obtained from the experimental data, as well as the experimental heat capacity change upon unfolding, were correlated with the structural parameters derived from the three dimensional structure of Trp‐cage. It is shown that the m‐value can be predicted well using a transfer model, while the heat capacity changes are in very good agreement with the empirical models based on model compounds studies. These results provide direct evidence that Trp‐cage, despite its small size, is an excellent model for studies of protein unfolding and provide thermodynamic data that can be used to compare with atomistic computer simulations. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

In Silico Models for Dynamic Connected Cell Cultures Mimicking Hepatocyte-Endothelial Cell-Adipocyte Interaction Circle

The biochemistry of a system made up of three kinds of cell is virtually impossible to work out without the use of in silico models. Here, we deal with homeostatic balance phenomena from a metabolic point of view and we present a new computational model merging three single-cell models, already available from our research group: the first model reproduced the metabolic behaviour of a hepatocyte, the second one represented an endothelial cell, and the third one described an adipocyte. Multiple interconnections were created among these three models in order to mimic the main physiological interactions that are known for the examined cell phenotypes. The ultimate aim was to recreate the accomplishment of the homeostatic balance as it was observed for an in vitro connected three-culture system concerning glucose and lipid metabolism in the presence of the medium flow. The whole model was based on a modular approach and on a set of nonlinear differential equations implemented in Simulink, applying Michaelis-Menten kinetic laws and some energy balance considerations to the studied metabolic pathways. Our in silico model was then validated against experimental datasets coming from literature about the cited in vitro model. The agreement between simulated and experimental results was good and the behaviour of the connected culture system was reproduced through an adequate parameter evaluation. The developed model may help other researchers to investigate further about integrated metabolism and the regulation mechanisms underlying the physiological homeostasis.     

A machine learning-based framework for delivery error prediction in proton pencil beam scanning using irradiation log-files

PurposeThis study aims to investigate the use of machine learning models for delivery error prediction in proton pencil beam scanning (PBS) delivery.MethodsA dataset of planned and delivered PBS spot parameters was generated from a set of 20 prostate patient treatments. Planned spot parameters (spot position, MU and energy) were extracted from the treatment planning system (TPS) for each beam. Delivered spot parameters were extracted from irradiation log-files for each beam delivery following treatment. The dataset was used as a training dataset for three machine learning models which were trained to predict delivered spot parameters based on planned parameters. K-fold cross validation was employed for hyper-parameter tuning and model selection where the mean absolute error (MAE) was used as the model evaluation metric. The model with lowest MAE was then selected to generate a predicted dose distribution for a test prostate patient within a commercial TPS.ResultsAnalysis of the spot position delivery error between planned and delivered values resulted in standard deviations of 0.39 mm and 0.44 mm for x and y spot positions respectively. Prediction error standard deviation values of spot positions using the selected model were 0.22 mm and 0.11 mm for x and y spot positions respectively. Finally, a three-way comparison of dose distributions and DVH values for select OARs indicates that the random-forest-predicted dose distribution within the test prostate patient was in closer agreement to the delivered dose distribution than the planned distribution.ConclusionsPBS delivery error can be accurately predicted using machine learning techniques.     

3D-QSAR study of bis-azaaromatic quaternary ammonium analogs at the blood-brain barrier choline transporter

Previously, we have developed 3D-QSAR models of the blood-brain barrier (BBB) choline transporter, a transport system that may have utility as a vector for central nervous system drug delivery. In this study, we extended the model by evaluating five bis-azaaromatic quaternary ammonium compounds for their affinity for the choline binding site on the BBB-choline transporter. The compounds, and their affinities for the transporter, were then incorporated into our existing molecular model, in order to update our knowledge on the molecular recognition factors associated with interaction of ligands at the choline binding site. The current compounds are structurally related to previous substrates that we have evaluated, but offer additional three dimensional aspects compared to the series of compounds previously utilized to define the original models. The compounds showed good affinity for the BBB-choline transporter, exhibiting inhibition constants ranging from 10 to 68 microM, as determined by the in situ rat brain perfusion method. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods were used to build the new 3D QSAR models. When the new bis-azaaromatic quaternary ammonium compounds were included in the model, the best cross-validated CoMFA q2 was found to be 0.536 and the non-cross-validated r2 was 0.818. CoMSIA hydrophobic cross-validated q2 was 0.506 and the non-cross-validated r2 was 0.804. This new model was able to better predict BBB-choline transporter affinity of hemicholinium-3 (predicted 65 microM, actual 54 microM), when compared to an earlier model (predicted 316 microM).     

The Rheology of 6-Propyl Duodecane and 5-Dibutyl Nonane by Non-Equilibrium Molecular Dynamics Simulations

Abstract

In recent papers, we reported non-equilibrium molecular dynamics (NEMD) simulations of planar Couette flow for liquid n- and i-butane, and liquid n-decane and 4-propyl heptane, using two collapsed atom models and an atomistically detailed model. It was found that the collapsed atom models predict the viscosities of the n-butane and n-decane quite well, and that the atomistically detailed model does not yield quantitative agreement with the viscosity of the n-alkanes or the branched alkanes, but it does have the one positive feature that the calculated viscosities of the branched alkanes are higher than these of the n-alkanes. In the present paper, we report results of NEMD simulations of planar Couette flow for liquid 6-propyl duodecane and 5-dibutyl nonane at 296 K and 0.782 g/cc, using an expanded collapsed atom model for simplicity. The strain rate dependent viscosity shows three different regions—two shear thinning ones and a Newtonian one. The slopes of the log-log plot for the branched-chain alkanes at high strain rate are different from those at intermediate strain rate, which is characterized as a rheological behavior of branched-chain alkanes. The Newtonian viscosity of the branched-chain alkanes can be extrapolated from the plateau value of the strain rate dependent viscosity at low strain rate as for straight-chain alkanes [J. Chem. Phys., 105, 1214 (1996)]. The results indicate that more-branched alkanes have a larger viscosity than less-branched C₁₇ alkanes.     

Phase Equilibria of Quadrupolar Fluids by Simulation in the Gibbs Ensemble

Abstract

Vapour-liquid phase diagrams for pure fluids and mixtures of molecules with Lennard-Jones plus quadrupole-quadrupole interaction potentials were determined by Monte Carlo simulation in the Gibbs ensemble [1]. This is the first reported application of the method to molecular fluids. We have demonstrated that the Gibbs method works reliably for strongly interacting molecular fluids at liquid densities. Pure fluid calculations were performed for reduced quadrupole strengths, Q* = Q/(εσ⁵)^1/2 equal to 1 and √2, typical of molecules like C₂H₂ and C₂H₄. It was found that the critical temperature of the quadrupolar fluid increased rapidly with increasing quadrupolar strength, in good agreement with previous computer simulation and theoretical results. A single mixture with components characterized by identical Lennard-Jones parameters and Q*₁ = + 1, Q*₂ = - 1 was studied at three temperatures. A negative azeotrope was observed at the lowest temperature studied, as seen experimentally in the CO₂/C₂H₂ mixture. The perturbation theory calculations are in good agreement with the simulation results for all properties except coexisting liquid densities. The results illustrate some of the strengths and limitations of perturbation theories based on the Padé approximant for the free energy of polar fluids.     

Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions

Background

Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals.

Results

Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall.

Conclusions

The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions.

     

Binding affinity of hydroxamate inhibitors of matrix metalloproteinase-2

Here we report molecular dynamics (MD) and free energy perturbation (FEP) simulations applied to hydroxamate-matrix metalloproteinase-2 (MMP-2) complex systems. We have developed some new force field parameters for the hydroxamate functional group that were not included in the AMBER94 force field but were necessary in our simulations. For the representation of the active zinc center, a bonded model was adopted in which restrained electrostatic potential fitting (RESP) charges were used as the electrostatic representation of this model. Using the resulted bonded model, FEP simulations predict the relative binding free energy in good agreement with the experimental value. By analyzing the molecular dynamics (MD) trajectories of the two complex systems, we can provide an explanation of why one of the two inhibitors is favored over the other. The results provide a chemical insight into the interactions between inhibitor and enzyme, and can indicate changes in the inhibitor that would enhance inhibitor–enzyme interactions.Figure The scheme of the binding site     

Evaluation and Calibration of In Silico Models of Thrombin Generation Using Experimental Data from Healthy and Haemophilic Subjects

The coagulation cascade comprises numerous chemical reactions between many proteins, that finally lead to the formation of a clot to stop bleeding. Many numerical models have attempted to translate understanding of this cascade into mathematical equations that simulate the chain reactions. However, their predictions have not been validated against clinical data stemming from patients. In this paper, we propose an extensive validation of five available models, by comparing in healthy and haemophilic subjects, thrombin generation measured in vitro to thrombin generation predicted by the models in silico. In order to render the models more predictive, we calibrated the models to have an acceptable agreement between the experimental and estimated data. Optimization processes based on genetic algorithms were developed to search for those calibrated kinetic parameters. Our results show that the thrombin generation kinetics are so complex that they cannot be predicted by a unique set of kinetic parameters for all patients: the calibration of only three parameters in a subject-specific way allows reaching good model estimations for different experimental conditions realized on the same patient.