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A chemistry module has been implemented in Geant4-DNA since Geant4 version 10.1 to simulate the radiolysis of water after irradiation. It has been used in a number of applications, including the calculation of G-values and early DNA damage, allowing the comparison with experimental data. Since the first version, numerous modifications have been made to the module to improve the computational efficiency and extend the simulation to homogeneous kinetics in bulk solution. With these new developments, new applications have been proposed and released as Geant4 examples, showing how to use chemical processes and models. This work reviews the models implemented and application developments for modeling water radiolysis in Geant4-DNA as reported in the ESA BioRad III Project., (© 2024 American Association of Physicists in Medicine.)

In this study, we use machine learning algorithms with QM-derived COSMO-RS descriptors, along with Morgan fingerprints, to predict the absolute solubility of drug-like compounds. The QM-derived descriptors account for the molecular properties of the solute, i.e., the solute-solute interactions in an artificial-liquid-state (super-cooled liquid), and the solute-solvent interactions in solution. We employ two main approaches to predict solubility: (i) a hypothetical pathway that involves melting the solute at room temperature T = T¯ ([Formula: see text]) and mixing the artificially liquid solute into the solvent ([Formula: see text]). In this approach [Formula: see text] is predicted using machine learning models, and the [Formula: see text] is obtained from COSMO-RS calculations; (ii) direct solubility prediction using machine learning algorithms. The models were trained on a large number of Bayer in-house compounds for which water solubility data is available at physiological pH of 6.5 and ambient temperature. We also evaluated our models using external datasets from a solubility challenge. Our models present great improvements compared to the absolute solubility prediction with the QSAR model for the artificial liquid state as implemented in the COSMOtherm software, for both in-house and external datasets. We are furthermore able to demonstrate the superiority of QM-derived descriptors compared to cheminformatics descriptors. We finally present low-cost alternative models using fragment-based COSMOquick calculations with only marginal reduction in the quality of predicted solubility., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The octanol/air partition coefficient K oa is important for assessing the bioconcentration of airborne xenobiotics in foliage and in air-breathing organisms. Moreover, K oa informs about compound partitioning to aerosols and indoor dust, and complements the octanol/water partition coefficient K ow and the air/water partition coefficient K aw for multimedia fate modeling. Experimental log  K oa at 25 °C has been collected from literature for 2161 compounds with molecular weights from 16 to 959 Da. The curated data set covers 18.2 log units (from -1.0 to 17.2). A newly developed fragment model for predicting log  K oa from molecular structure outperforms COSMOtherm, EPI-Suite KOAWIN, OPERA, and linear solvation energy relationships (LSERs) regarding the root-mean-squared error (rms) and the maximum negative and positive errors (mne and mpe) (rms: 0.57 vs 0.86 vs 1.09 vs 1.19 vs 1.05-1.53, mne: -2.55 vs -3.95 vs -7.51 vs -7.54 vs (-5.63) - (-7.34), mpe: 2.91 vs 5.97 vs 7.54 vs 4.24 vs 6.89-10.2 log units). The prediction capability, statistical robustness, and sound mechanistic basis are demonstrated through initial separation into a training and prediction set (80:20%), mutual leave-50%-out validation, and target value scrambling in terms of temporarily wrong compound- K oa allocations. The new general-purpose model is implemented in a fully automatized form in the ChemProp software available to the public. Regarding K oa indirectly determined through K ow and K aw , a new approach is developed to convert from wet to dry octanol, enabling higher consistency in experimental (and thus also predicted) K oa .

Blind predictions of octanol/water partition coefficients and pKa at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. Octanol/water partition coefficients were predicted from solvation free energies computed using electronic structure calculations with the SM12, SM8 and SMD solvation models. Within these calculations we compared the use of gas- and solution-phase optimized geometries of the solute. Based on these calculations we found that in general the use of solution phase-optimized geometries increases the affinity of the solutes for water as compared to octanol, with the use of gas-phase optimized geometries resulting in the better agreement with experiment. The pKa is computed using the direct approach, scaled solvent-accessible surface model, and the inclusion of an explicit water molecule, where the latter two methods have previously been shown to offer improved predictions as compared to the direct approach. We find that the use of an explicit water molecule provides superior predictions, and that the predicted macroscopic pKa is sensitive to the employed microstates., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

We have quantum chemically investigated how solvation influences the competition between the S N 2 and E2 pathways of the model F - + C 2 H 5 Cl reaction. The system is solvated in a stepwise manner by going from the gas phase, then via microsolvation of one to three explicit solvent molecules, then last to bulk solvation using relativistic density functional theory at (COSMO)-ZORA-OLYP/QZ4P. We explain how and why the mechanistic pathway of the system shifts from E2 in the gas phase to S N 2 upon strong solvation of the Lewis base (i.e., nucleophile/protophile). The E2 pathway is preferred under weak solvation of the system by dichloromethane, whereas a switch in reactivity from E2 to S N 2 is observed under strong solvation by water. Our activation strain and Kohn-Sham molecular orbital analyses reveal that solvation of the Lewis base has a significant impact on the strength of the Lewis base. We show how strong solvation furnishes a weaker Lewis base that is unable to overcome the high characteristic distortivity associated with the E2 pathway, and thus the S N 2 pathway becomes viable.

Blind predictions of octanol/water partition coefficients at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. The octanol/water partition coefficients were predicted using solvation free energies computed using molecular dynamics simulations, wherein we considered the use of both pure and water-saturated 1-octanol to model the octanol-rich phase. Water and 1-octanol were modeled using TIP4P and TrAPPE-UA, respectively, which have been shown to well reproduce the experimental mutual solubility, and the solutes were modeled using GAFF. After the close of the SAMPL7 challenge, we additionally made predictions using TIP4P/2005 water. We found that the predictions were sensitive to the choice of water force field. However, the effect of water in the octanol-rich phase was found to be even more significant and non-negligible. The effect of inclusion of water was additionally sensitive to the chemical structure of the solute., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The reaction between carbon monoxide and water was studied occurring in an aerosol medium rich in methanol. This environment is plausible for the primitive and prebiotic Earth atmosphere. The chemical environment is expressed in terms of dielectric constant (ε) and the chemical system was modeled employing the polarizable continuum model (PCM). The main results were acquired from calculations employing the M06-2X density functional for the electronic structure calculations and the canonical variational theory with small curvature tunneling for the chemical kinetic calculations. The rise of ε affects both the thermochemistry and the kinetics of the reaction, increasing the barrier height and decreasing the rate constant for the reaction occurring at room temperature. For example, the rate constant at 300 K is 5-10× 10 - 53 cm 3 ⋅molecule - 1 ⋅s - 1 for low dielectric constant (ε < 3) and around 2-4× 10 - 53 cm 3 ⋅molecule - 1 ⋅s - 1 for ε between 7 and 40. Our results indicate that the ε variation allows a fine tuning to the rate of the reaction., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Water oxidation occurring in the first steps of natural oxygenic photosynthesis is catalyzed by the pigment/protein complex Photosystem II. This process takes place on the Mn 4 Ca cluster located in the core of Photosystem II and proceeds along the five steps (S 0 -S 4 ) of the so-called Kok-Joliot cycle until the release of molecular oxygen. The catalytic cycle can therefore be started afresh through insertion of a new water molecule. Here, combining quantum mechanics/molecular mechanics simulations and minimum energy path calculations, we characterized on different spin surfaces the events occurring in the last sector of the catalytic cycle from structural, electronic, and thermodynamic points of view. We found that the process of oxygen evolution and water insertion can be described well by a two-step mechanism, with oxygen release being the rate-limiting step of the process. Moreover, our results allow us to identify the upcoming water molecule required to regenerate the initial structure of the Mn 4 Ca cluster in the S 0 state. The insertion of the water molecule was found to be coupled with the transfer of a proton to a neighboring hydroxide ion, thus resulting in the reconstitution of the most widely accepted model of the S 0 state.

Stress testing of active pharmaceutical ingredients (API) is an important tool used to gauge chemical stability and identify potential degradation products. While different flavors of API stress testing systems have been used in experimental investigations for decades, the detailed kinetics of such systems as well as the chemical composition of prominent reactive species, specifically reactive oxygen species, are unknown. As a first step toward understanding and modeling API oxidation in stress testing, we investigated a typical radical "soup" solution an API is subject to during stress testing. Here we applied ab initio electronic structure calculations to automatically generate and refine a detailed chemical kinetics model, taking a fresh look at API oxidation. We generated a detailed kinetic model for a representative azobis(isobutyronitrile) (AIBN)/H 2 O/CH 3 OH stress-testing system with a varied cosolvent ratio (50%/50%-99.5%/0.5% vol water/methanol) for 5.0 mM AIBN and representative pH values of 4-10 at 40 °C that was stirred and open to the atmosphere. At acidic conditions, hydroxymethyl alkoxyl is the dominant alkoxyl radical, and at basic conditions, for most studied initial methanol concentrations, cyanoisopropyl alkoxyl becomes the dominant alkoxyl radical, albeit at an overall lower concentration. At acidic conditions, the levels of cyanoisopropyl peroxyl, hydroxymethyl peroxyl, and hydroperoxyl radicals are relatively high and comparable, while, at both neutral and basic pH conditions, superoxide becomes the prominent radical in the system. The present work reveals the prominent species in a common model API stress testing system at various cosolvent and pH conditions, sets the stage for an in-depth quantitative API kinetic study, and demonstrates the usage of novel software tools for automated chemical kinetic model generation and ab initio refinement.

Inspired by the successful application of the embedded cluster reference interaction site model (EC-RISM), a combination of quantum-mechanical calculations with three-dimensional RISM theory to predict Gibbs energies of species in solution within the SAMPL6.1 (acidity constants, pK a ) and SAMPL6.2 (octanol-water partition coefficients, log P) the methodology was applied to the recent SAMPL7 physical property challenge on aqueous pK a and octanol-water log P values. Not part of the challenge but provided by the organizers, we also computed distribution coefficients log D 7.4 from predicted pK a and log P data. While macroscopic pK a predictions compared very favorably with experimental data (root mean square error, RMSE 0.72 pK units), the performance of the log P model (RMSE 1.84) fell behind expectations from the SAMPL6.2 challenge, leading to reasonable log D 7.4 predictions (RMSE 1.69) from combining the independent calculations. In the post-submission phase, conformations generated by different methodology yielded results that did not significantly improve the original predictions. While overall satisfactory compared to previous log D challenges, the predicted data suggest that further effort is needed for optimizing the robustness of the partition coefficient model within EC-RISM calculations and for shaping the agreement between experimental conditions and the corresponding model description., (© 2021. The Author(s).)

A multiple linear regression model called MLR-3 is used for predicting the experimental n-octanol/water partition coefficient (log P N ) of 22 N-sulfonamides proposed by the organizers of the SAMPL7 blind challenge. The MLR-3 method was trained with 82 molecules including drug-like sulfonamides and small organic molecules, which resembled the main functional groups present in the challenge dataset. Our model, submitted as "TFE-MLR", presented a root-mean-square error of 0.58 and mean absolute error of 0.41 in log P units, accomplishing the highest accuracy, among empirical methods and also in all submissions based on the ranked ones. Overall, the results support the appropriateness of multiple linear regression approach MLR-3 for computing the n-octanol/water partition coefficient in sulfonamide-bearing compounds. In this context, the outstanding performance of empirical methodologies, where 75% of the ranked submissions achieved root-mean-square errors < 1 log P units, support the suitability of these strategies for obtaining accurate and fast predictions of physicochemical properties as partition coefficients of bioorganic compounds., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Theophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally studied binary systems, the one containing DMSO with water in unimolar proportions was found to be the most effective in theophylline dissolution. Likewise, for NADES, the addition of water (0.2 molar fraction) resulted in increased solubility compared to pure eutectics, with the highest solubilisation potential offered by the composition of choline chloride with glycerol. The ensemble of Statistica Automated Neural Networks (SANNs) developed using intermolecular interactions in pure systems has been found to be a very accurate model for solubility computations. This machine learning protocol was also applied as an extensive screening for potential solvents with higher solubility of theophylline. Such solvents were identified in all three subgroups, including neat solvents, binary mixtures and ternary NADES systems. Some methodological considerations of SANNs applications for future modelling were also provided. Although the developed protocol is focused exclusively on theophylline solubility, it also has general importance and can be used for the development of predictive models adequate for solvent screening of other compounds in a variety of systems. Formulation of such a model offers rational guidance for the selection of proper candidates as solubilisers in the designed solvents screening.

We applied the COSMO-RS method to predict the partition coefficient logP between water and 1-octanol for 22 small drug like molecules within the framework of the SAMPL7 blind challenge. We carefully collected a set of thermodynamically meaningful microstates, including tautomeric forms of the neutral species, and calculated the logP using the current COSMOtherm implementation on the most accurate level. With this approach, COSMO-RS was ranked as the 6st most accurate method (Measured by the mean absolute error (MAE) of 0.57) over all 17 ranked submissions. We achieved a root mean square deviation (RMSD) of 0.78. The largest deviations from experimental values are exhibited by five SAMPL molecules (SM), which seem to be shifted in most SAMPL7 contributions. In context with previous SAMPL challenges, COSMO-RS demonstrates a wide range of applicability and one of the best in class reliability and accuracy among the physical methods., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Partition coefficients quantify a molecule's distribution between two immiscible liquid phases. While there are many methods to compute them, there is not yet a method based on the free energy of each system in terms of energy and entropy, where entropy depends on the probability distribution of all quantum states of the system. Here we test a method in this class called Energy Entropy Multiscale Cell Correlation (EE-MCC) for the calculation of octanol-water logP values for 22 N-acyl sulfonamides in the SAMPL7 Physical Properties Challenge (Statistical Assessment of the Modelling of Proteins and Ligands). EE-MCC logP values have a mean error of 1.8 logP units versus experiment and a standard error of the mean of 1.0 logP units for three separate calculations. These errors are primarily due to getting sufficiently converged energies to give accurate differences of large numbers, particularly for the large-molecule solvent octanol. However, this is also an issue for entropy, and approximations in the force field and MCC theory also contribute to the error. Unique to MCC is that it explains the entropy contributions over all the degrees of freedom of all molecules in the system. A gain in orientational entropy of water is the main favourable entropic contribution, supported by small gains in solute vibrational and orientational entropy but offset by unfavourable changes in the orientational entropy of octanol, the vibrational entropy of both solvents, and the positional and conformational entropy of the solute., (© 2021. The Author(s).)

The prediction of [Formula: see text] values is one part of the statistical assessment of the modeling of proteins and ligands (SAMPL) blind challenges. Here, we use a molecular graph representation method called Geometric Scattering for Graphs (GSG) to transform atomic attributes to molecular features. The atomic attributes used here are parameters from classical molecular force fields including partial charges and Lennard-Jones interaction parameters. The molecular features from GSG are used as inputs to neural networks that are trained using a "master" dataset comprised of over 41,000 unique [Formula: see text] values. The specific molecular targets in the SAMPL7 [Formula: see text] prediction challenge were unique in that they all contained a sulfonyl moeity. This motivated a set of ClassicalGSG submissions where predictors were trained on different subsets of the master dataset that are filtered according to chemical types and/or the presence of the sulfonyl moeity. We find that our ranked prediction obtained 5th place with an RMSE of 0.77 [Formula: see text] units and an MAE of 0.62, while one of our non-ranked predictions achieved first place among all submissions with an RMSE of 0.55 and an MAE of 0.44. After the conclusion of the challenge we also examined the performance of open-source force field parameters that allow for an end-to-end [Formula: see text] predictor model: General AMBER Force Field (GAFF), Universal Force Field (UFF), Merck Molecular Force Field 94 (MMFF94) and Ghemical. We find that ClassicalGSG models trained with atomic attributes from MMFF94 can yield more accurate predictions compared to those trained with CGenFF atomic attributes., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Permeability characteristics of compacted loess is always an important topic in soil mechanics and geotechnical engineering. This study explored the permeability characteristics of compacted loess under different dry densities and wetting-drying cycles, and found that as the dry density increases, the compacted loess surface became denser, the saturation permeability coefficient and saturation infiltration rate decreased. However, the wetting-drying cycle presented the opposite result. Meanwhile, the evolution of the microstructure was investigated by Scanning Electron Microscope (SEM) and Nuclear Magnetic Resonance (NMR) to explain the change of its permeability characteristics. The size of compacted loess aggregates was quantitatively analyzed by Image-Pro Plus (IPP) software. It showed that the size of compacted loess aggregates for different dry densities were concentrated from 10-100 μm, occupying 65.0%, 58.19%, and 51.64% of the total aggregates area respectively. And the interesting finding was that the area occupied by 10-50 μm aggregates remained basically unchanged with the number of wetting-drying cycles increasing. Therefore, the size of 10-50 μm aggregates represented the transition zone of compacted loess. NMR analyses revealed that with increasing dry density, the volume of macropores in the compacted loess rapidly decreased, the volume of mesopores and small pores increased. Meanwhile, the change in micropores was relatively small. The pore volume of the compacted loess after three wetting-drying cycles increased by 8.56%, 8.61%, and 6.15%, respectively. The proportion of macropores in the total pore volume shows the most drastic change. Variations in aggregate size and connection relationships made it easier to form overhead structures between aggregates, and the increased of macropore volume will form more water channels. Therefore, the change in permeability characteristics of compacted loess is determined by aggregate size, loess surface morphology, and the total pore volume occupied by macropores., Competing Interests: Xiang-fei Lü is employed by CCCC First Highway Consultants Co., LTD. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the Plos ONE policies on sharing data and materials.

Quantum-mechanical methods are used for understanding molecular interactions throughout the natural sciences. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] are state-of-the-art trusted wavefunction methods that have been shown to yield accurate interaction energies for small organic molecules. These methods provide valuable reference information for widely-used semi-empirical and machine learning potentials, especially where experimental information is scarce. However, agreement for systems beyond small molecules is a crucial remaining milestone for cementing the benchmark accuracy of these methods. We show that CCSD(T) and DMC interaction energies are not consistent for a set of polarizable supramolecules. Whilst there is agreement for some of the complexes, in a few key systems disagreements of up to 8 kcal mol -1 remain. These findings thus indicate that more caution is required when aiming at reproducible non-covalent interactions between extended molecules.

The rheological properties parameters of paddy soil affect the interaction between the tillage tools and soil, thus influencing the operation quality and power consumption. In order to study the effects of tillage methods and moisture content on the rheological properties parameters of paddy soil in the middle and lower reaches of the Yangtze River, uniaxial compression creep tests of paddy soils with four moisture contents under no tillage (moisture contents: 26.71%, 24.52%, 23.26%, 21.28%) and plough tillage (moisture contents: 26.77%, 25.55%, 23.40%, 20.56%) were carried out using a TMS-PRO texture analyzer. The creep properties curves obtained from the tests, and the rheological constitutive equation of paddy soil under compression was established by Burgers viscoelastic model. Respectively, the quantitative change rules of creep properties of paddy soil with different moisture contents under different tillage methods and the correlation between these parameters were explored. The results showed that the moisture content under the three-year plough tillage and no tillage methods had significant influence on the rheological properties parameters of paddy soil (P < 0.05). The instantaneous elastic modulus, delay elastic modulus, and viscosity coefficient of the two paddy soils (no tillage and plough tillage soils) decreased with the increase of moisture content. However, the variation rules of relaxation time and delay viscosity coefficient with moisture content differed between these two paddy soils. Specifically, the strain rate of the two paddy soils decreased as moisture content decreased, where the total strain combines elastic strain, viscous strain, and viscoelastic strain. The initial strain rate and steady strain rate of the plough tillage paddy soils were lower than that of the no tillage paddy soils. The established creep model equation could be used to obtain viscoelastic rheological parameters of paddy soil in a wide range. The fitting equations between rheological parameters and moisture content were introduced into Burgers model, and the coupling equations between creep deformation and moisture content and time were derived, which could be used to predict the creep properties and deformation behavior of paddy soil in a certain range of no tillage and ploughed field. Overall, this study has a certain theoretical significance for the development and improvement of paddy soil rheology theory, and can also provide theoretical basis and technical support for the research of agricultural machinery design optimization, field water, soil conservation, soil tillage and compaction related simulation analysis in the middle and lower reaches of the Yangtze River., Competing Interests: The authors have declared that no competing interests exist.

A major part of chemical conversions is carried out in the fluid phase, where an accurate modeling of the involved reactions requires to also take into account solvation effects. Implicit solvation models often cover these effects with sufficient accuracy but can fail drastically when specific solvent-solute interactions are important. In those cases, microsolvation, i.e., the explicit inclusion of one or more solvent molecules, is a commonly used strategy. Nevertheless, microsolvation also introduces new challenges-a consistent workflow as well as strategies how to systematically improve prediction performance are not evident. For the COSMO and COSMO-RS solvation models, this work proposes a simple protocol to decide if microsolvation is needed and how the corresponding molecular model has to look like. To demonstrate the improved accuracy of the approach, specific application examples are presented and discussed, i.e., the computation of aqueous pK a values and a mechanistic study of the methanol mediated Morita-Baylis-Hillman reaction.

Protein conformational fluctuations are highly complex and exhibit long-term correlations. Here, molecular dynamics simulations of small proteins demonstrate that these conformational fluctuations directly affect the protein's instantaneous diffusivity D&#95;{I}. We find that the radius of gyration R&#95;{g} of the proteins exhibits 1/f fluctuations that are synchronous with the fluctuations of D&#95;{I}. Our analysis demonstrates the validity of the local Stokes-Einstein-type relation D&#95;{I}∝1/(R&#95;{g}+R&#95;{0}), where R&#95;{0}∼0.3  nm is assumed to be a hydration layer around the protein. From the analysis of different protein types with both strong and weak conformational fluctuations, the validity of the Stokes-Einstein-type relation appears to be a general property.

We use the quantum-classical path integral (QCPI) methodology to investigate the relaxation dynamics of an excess proton that has been inserted in a water dimer embedded in the gramicidin A channel at room temperature. We obtain one-dimensional potential slices for the quantum degree of freedom through a proper transformation to internal coordinates. Our results indicate that the proton transfer is driven by the oscillation of the oxygen pair, and that the transfer occurs primarily at single-well or nearby low-barrier configurations. Yet, we find that tunneling and zero-point energy lead to a significant acceleration of the proton transfer dynamics.

The development of the freeze-drying processes through the use of a combination of targeted experiments and the application of multidimensional computational models is applied increasingly in pharmaceutical practice, especially for scale-up purposes. This study deals with the analysis of uncertainties in the data on material properties and model parameters, and their influence on the results delivered by advanced computational models of lyophilisation. As a means of uncertainty analysis, the Stochastic Collocation Method is applied, allowing the use of existing reliable deterministic models as black boxes in the stochastic computations. As a deterministic model, the lyophilisation model is used, based on the axisymmetric approximation of a vial, and the Boundary Element Method as a solver. Five parameters, covering material properties, process conditions and model constants, are selected for the sensitivity analysis simulation of the lyophilisation of an aqueous mannitol solution. The results show that during the initial stage of the primary drying heat transfer from the shelf is crucial, and that the uncertainties in the contact surface area and material properties of the vial play a more important role than the thermal properties of the drying material. When the temperature of the material reaches its distinct primary drying stage level the mass transfer through the porous cake becomes the most important, with great sensitivity to the Knudsen diffusivity in the porous cake. We observed uncertainties in the results for the primary drying time in the order of ±6%, and uncertainties in the results for temperatures of ±0.6°C in the frozen material and ±3°C in the porous cake. The uncertainty analysis proved to be a great help in determining the critical parameters in the heat and mass transfer during the important primary drying step, which led to a better definition of the numerical model for use in the context of design space determination., (Copyright © 2020 Elsevier B.V. All rights reserved.)

FFLUX is a biomolecular force field under construction, based on Quantum Chemical Topology (QCT) and machine learning (kriging), with a minimalistic and physically motivated design. A detailed analysis of the forces within the kriging models as treated in FFLUX is presented, taking as a test example a liquid water model. The energies of topological atoms are modeled as 3N atoms -6 dimensional potential energy surfaces, using atomic local frames to represent the internal degrees of freedom. As a result, the forces within the kriging models in FFLUX are inherently N-body in nature where N refers to N atoms . This provides a fuller picture that is closer to a true quantum mechanical representation of interactions between atoms. The presented computational example quantitatively showcases the non-negligible (as much as 9%) three-body nature of bonded forces and angular forces in a water molecule. We discuss the practical impact on the pressure calculation with N-body forces and periodic boundary conditions (PBC) in molecular dynamics, as opposed to classical force fields with two-body forces. The equivalence between the PBC-related correction terms in the general virial equation is shown mathematically., (© 2020 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.)

Aim of Study: The shape effects of nanoparticles are very significant in fluid flow and heat transfer. In this paper, we discuss the effects of nanoparticles shape in nanofluid flow between divergent-convergent channels theoretically. In this present study, various shapes of nanoparticles, namely sphere, column and lamina in zinc oxide-water nanofluid are used. The effect of the magnetic field and joule dissipation are also considered., Research Methodology: The system of nonlinear partial differential equations (PDEs) is converted into ordinary differential equations (ODES). The analytical solutions are successfully obtained and compared with numerical solutions. The Homotopy perturbation method and NDsolve method are used to compare analytical and numerical results respectively., Conclusion: The results show that the lamina shape nanoparticles have higher performance in temperature disturbance and rate of heat transfer as compared to other shapes of nanoparticles., Competing Interests: The authors have declared that no competing interests exist.

The hierarchical self-assembling kinetics of the porphyrin 5,10,15,20- tetrakis (4-sulfonatophenyl)porphyrin (H 2 TPPS 4 4- ) into J-aggregates at high ionic strength under acidic conditions and eventually in the presence of an added chiral templating agent (tartrate) were investigated through UV/Vis spectroscopy, resonance light scattering, and circular dichroism (CD). The effect of changing the mixing order of the various components in the solution on the kinetic parameters and the expression of chirality on the final J-aggregates was evaluated. In this latter case, only when the chiral tartrate anion is premixed with the porphyrin, the resulting nano-architectures exhibit CD spectra that reflect the handedness of the chiral inducer. We discuss a general mechanistic scheme, with the involvement of ion pairs or dimers that offer an alternative pathway to the aggregation process.

Aspartic acid (Asp) residues are prone to nonenzymatic isomerization via a succinimide (Suc) intermediate. The formation of isomerized Asp residues is considered to be associated with various age-related diseases, such as cataracts and Alzheimer's disease. In the present paper, we describe the reaction pathway of Suc residue formation from Asp residues catalyzed by two water molecules using the B3LYP/6-31+G(d,p) level of theory. Single-point energies were calculated using the MP2/6-311+G(d,p) level of theory. For these calculations, we used a model compound in which an Asp residue was capped with acetyl and methylamino groups on the N - and C -termini, respectively. In the aqueous phase, Suc residue formation from an Asp residue was roughly divided into three steps, namely, iminolization, cyclization, and dehydration, with the activation energy estimated to be 109 kJ mol -1 . Some optimized geometries and reaction modes in the aqueous phase were observed that differed from those in the gas phase.

The LFER model of Abraham is applied to the retention of the neutral and ionic forms of 94 solutes in a C18 column and 40% v/v acetonitrile/water mobile phase. The results show that polarizability and cavity formation interactions increase retention, whereas dipole and hydrogen bonding interactions favours partition to the mobile phase and thus, they decrease retention. The coefficients of the ionic descriptors measure the effect of the electrostatic interactions and their contribution to partition of the cation or anion between the two mobile and stationary chromatographic phases. A new LFER model for application to the retention of partially dissociated acids and bases is derived averaging the descriptors of the neutral and ionic forms according to their degrees of ionization in the mobile phase. This new LFER model is satisfactorily compared to other literature modified Abraham models for a set of 498 retention data of partially dissociated acids and bases. All tested models require the calculation of the ionization degrees of the compounds at the measuring pH. Calculation of the ionization degrees in the chromatographic mobile phase (i.e. from pH and pK a in the eluent) give good correlations for all tested models. However, estimation of these ionization degrees from pH - pK a data in pure water gives biased estimations of the retention of the partially ionized solutes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier B.V.)

The capability of liquid chromatography with microemulsions (MEs) as mobile phases was studied for the analysis of four parabens (butylparaben, ethylparaben, methylparaben, and propylparaben) and seven β-adrenoceptor antagonists (acebutolol, atenolol, carteolol, metoprolol, oxprenolol, propranolol, and timolol). MEs were formed by mixing aqueous solutions of the anionic surfactant sodium dodecyl sulphate, the alcohol 1-butanol that played the role of co-surfactant, and octane as oil. In order to guarantee the formation of stable MEs, a preliminary study was carried out to determine the appropriate ranges of concentrations of the three components. For this purpose, mixtures of variable composition were prepared, and the possible separation of two phases (formation of an emulsion) was visually detected. The advantage offered by the addition of octane to micellar mobile phases, inside the concentration range that allows the formation of stable MEs, was evaluated by comparing the retention behaviour, peak profile and resolution of mixtures of the probe compounds, in the presence and absence of octane. The final aim of this work was the proposal of a mathematical equation to model the retention behaviour in microemulsion liquid chromatography. The derived global model that considered the three factors (surfactant, alcohol and oil) allowed the prediction of retention times at diverse mobile phase compositions with satisfactory accuracy (in the 1.1‒2.5% range). The behaviour was compared with that found with mobile phases without octane. The model also yielded information about the retention mechanism and revealed that octane, when inserted inside the micelle, modifies the interaction between solutes and micelles., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

For the selectivity evaluation of core-shell silica, siloxane-bonded reversed-phase columns by the solvation parameter model a minimal set of thirty-five calibration compounds were identified for applications with mobile phases containing from 20-70 % (v/v) methanol- or acetonitrile-water. The Kennard-Stone uniform mapping algorithm was employed to select the calibration compounds from a larger database of compounds with known retention properties used previously for column selectivity evaluation. The number and identity of the calibration compounds was optimized by considering the statistical quality of the calibration models, the absolute value for the standard deviation of the individual system constants, and the closeness of the estimated system constants for the calibration models to the values for the full data set on seven core-shell columns with different morphology for mobile phases containing 50 % (v/v) methanol- or acetonitrile-water. The predictive capability of the calibration models was evaluated for an external test set for 50 % (v/v) methanol-water for the same columns with a typical root mean square error of prediction (log k) of 0.028 for the thirty-five calibration compounds (n = 35) models. For all columns and mobile phase compositions the calibration models with n = 35 had a range for the coefficient of determination from 0.999 to 0.970 with < 5 % smaller than 0.99 (84 models) and a standard error of the estimate from 0.011 to 0.057 with 75 % < 0.030. System constants determined at 10 % (v/v) increments of organic solvent were utilized for the construction of system maps and correlation diagrams on Kinetex columns with octadecylsiloxane-bonded (C18 and EVO C18), diisobutyloctadecylsiloxane-bonded (XB-C18) octylsiloxane-bonded (C8), biphenylsiloxane-bonded (Biphenyl), phenylhexylsiloxane-bonded (Phenyl-Hexyl) and pentafluorophenylpropylsiloxane-bonded (F5) silica stationary phases for 20-70 % (v/v) methanol- and acetonitrile-water mobile phases. System maps for the Kinetex Phenyl-Hexyl column and correlation diagrams for columns of similar selectivity (Kinetex C8 and Phenyl-Hexyl) and dissimilar selectivity (Kinetex EVO C18 and Biphenyl) is used to illustrate the general approach to selectivity evaluation., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest in connection with this study, (Copyright © 2020 Elsevier B.V. All rights reserved.)

Many theories of the origin of life focus on only one primitive polymer as an archetype of a world paradigm. However, life would have emerged within more complex scenarios where a variety of molecules and diverse polymers interconnected by a few similar chemical reactions. Previous work suggested that the ancestors of all major biopolymers would have arisen from abiotic template independent replication processes. They would have been organized in two closed sets of polymerization cycles: polysaccharides, polyribonucleotides and polyphosphates on one site; and peptides, fatty acids and polyhydroxyalkanoates on the other site. Then, these polymerization reaction cycles integrated into a minimal organization closure. Here, the purpose was to explore which kind of reactions could have supported the chemical networks that led to the early (bio)polymers. As a result, the proposed overview suggests that phosphorylation and acylation transfer reactions would have arisen independently and forged two distinct chemical systems that provided the phosphorylated and carboxylated intermediates used for the synthesis of the corresponding polymers. In this sense, modern metabolism may still reflect its dual nature, probably relying on these two reaction networks from the beginnings., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Recognition and binding of ice by proteins, crystals, and other surfaces is key for their control of the nucleation and growth of ice. Docking is the state-of-the-art computational method to identify ice-binding surfaces (IBS). However, docking methods require a priori knowledge of the ice plane to which the molecules bind and either neglect the competition of ice and water for the IBS or are computationally expensive. Here we present and validate a robust methodology for the identification of the IBS of molecules and crystals that is easy to implement and a hundred times computationally more efficient than the most advanced ice-docking approaches. The methodology is based on biased sampling with an order parameter that drives the formation of ice. We validate the method using all-atom and coarse-grained models of organic crystals and proteins. To our knowledge, this approach is the first to simultaneously identify the ice-binding surface as well as the plane of ice to which it binds, without the use of structure search algorithms. We show that biased simulations even identify surfaces that are too small or too weak to heterogeneously nucleate ice. The biasing simulations can be used to identify of IBS of antifreeze and ice nucleating proteins and to equilibrate ice seeds bound to an IBS for the calculation of heterogeneous ice nucleation rates using classical nucleation theory.

In an attempt to understand the possibility of applications of the fullerene-based systems for transporting various polar compounds like hexamethonium through the blood-brain barrier, we studied the influence of a series of derivatives of fullerene C 60 in the form of salts with hexamethonium bis-anion, namely the adducts of fullerenols with 6-aminohexanoic acid (IEM-2197), and two bis-adduct malonic acid derivatives of fullerene with addents bound in two hemispheres (IEM-2143) and in equatorial positions (IEM-2144), on model membranes. We showed that IEM-2197 induced the disintegration of the bilayers composed of DOPC at the concentrations more than 2 mg/ml. IEM-2144 and IEM-2143-induced ion-permeable pores at concentrations of 0.3 and 0.02 mg/ml, respectively; herewith, IEM-2143 was characterized by the greater efficiency than IEM-2144. IEM-2197 did not significantly affect the phase behavior of DPPC, while the melting temperature significantly decreased with addition of IEM-2144 and IEM-2143. The increase in the half-width of the main transition peaks by more than 2.0 °C in the presence of IEM-2144 and IEM-2143 was observed, along with the pronounced peak deconvolution. We proposed that the immersion of IEM-2144 and IEM-2143 into the polar region of the DOPC or DPPC bilayers led to an increase in the relative mobility of tails and formation of ion-permeable defects. IEM-2197 demonstrated the more pronounced effects on the melting and ion permeability of PG- and PS-containing bilayers compared to PC-enriched membranes. These results indicated that IEM-2197 preferentially interacts with the negatively charged lipids compared to neutral species., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Solute-solvent interactions are proxies for understanding how the electronic density of a chromophore interacts with the environment in a more exhaustive way. The subtle balance between polarization, electrostatic, and non-bonded interactions need to be accurately described to obtain good agreement between simulations and experiments. First principles approaches providing accurate configurational sampling through molecular dynamics may be a suitable choice to describe solvent effects on solute chemical-physical properties and spectroscopic features, such as optical absorption of dyes. In this context, accurate energy potentials, obtained by hybrid implicit/explicit solvation methods along with employing nonperiodic boundary conditions, are required to represent bulk solvent around a large solute-solvent cluster. In this work, a novel strategy to simulate methanol solutions is proposed combining ab initio molecular dynamics, a hybrid implicit/explicit flexible solvent model, nonperiodic boundary conditions, and time dependent density functional theory. As case study, the robustness of the proposed protocol has been gauged by investigating the microsolvation and electronic absorption of the anionic green fluorescent protein chromophore in methanol and aqueous solution. Satisfactory results are obtained, reproducing the microsolvation layout of the chromophore and, as a consequence, the experimental trends shown by the optical absorption in different solvents., (© 2020 Wiley Periodicals LLC.)

Liquid water is considered to be a peculiar example of glass forming materials because of the possibility of giving rise to amorphous phases with different densities and of the thermodynamic anomalies that characterize its supercooled liquid phase. In the present work, literature data on the density of bulk liquid water are analyzed in a wide temperature-pressure range, also including the glass phases. A careful data analysis, which was performed on different density isobars, made in terms of thermodynamic response functions, like the thermal expansion αP and the specific heat differences CP-CV, proves, exclusively from the experimental data, the thermodynamic consistence of the liquid-liquid transition hypothesis. The study confirms that supercooled bulk water is a mixture of two liquid "phases", namely the high density (HDL) and the low density (LDL) liquids that characterize different regions of the water phase diagram. Furthermore, the CP-CV isobars behaviors clearly support the existence of both a liquid-liquid transition and of a liquid-liquid critical point.

The increasing application of new ionic liquids (IL) creates the need of liquid-liquid equilibria data for both miscible and quasi-immiscible systems. In this study, equilibrium concentrations at different temperatures for ionic liquid+water two-phase systems were modeled using a Quantitative-Structure-Property Relationship (QSPR) method. Data on equilibrium concentrations were taken from the ILThermo Ionic Liquids database, curated and used to make models that predict the weight fraction of water in ionic liquid rich phase and ionic liquid in the aqueous phase as two separate properties. The major modeling challenge stems from the fact that each single IL is characterized by several data points, since equilibrium concentrations are temperature dependent. Thus, new approaches for the detection of potential data point outliers, testing set selection, and quality prediction have been developed. Training set comprised equilibrium concentration data for 67 and 68 ILs in case of water in IL and IL in water modeling, respectively. SiRMS, MOLMAPS, Rcdk and Chemaxon descriptors were used to build Random Forest models for both properties. Models were subjected to the Y-scrambling test for robustness assessment. The best models have also been validated using an external test set that is not part of the ILThermo database. A two-phase equilibrium diagram for one of the external test set IL is presented for better visualization of the results and potential derivation of tie lines., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

In the biological proteins, aspartic acid (Asp) residues are prone to nonenzymatic isomerization via a succinimide (Suc) intermediate. Asp-residue isomerization causes the aggregation and the insolubilization of proteins, and is considered to be involved in various age-related diseases. Although Suc intermediate was considered to be formed by nucleophilic attack of the main-chain amide nitrogen of N-terminal side adjacent residue to the side-chain carboxyl carbon of Asp residue, previous studies have shown that the nucleophilic attack is more likely to proceed via iminol tautomer when the water molecules act as catalysts. However, the full pathway to Suc-intermediate formation has not been investigated, and the experimental analyses for the Asp-residue isomerization mechanism at atomic and molecular levels, such as the analysis of the transition state geometry, are difficult. In the present study, we computationally explored the full pathways for Suc-intermediate formation from Asp residues. The calculations were performed two types of reactant complexes, and all energy minima and TS geometries were optimized using B3LYP density functional methods. As a result, the SI-intermediate formation was divided into three processes, i.e., iminolization, cyclization, and dehydration processes, and the activation energies were calculated to be 26.1 or 28.4 kcal mol -1 . These values reproduce the experimental data. The computational results show that abundant water molecules in living organisms are effective catalysts for the Asp-residue isomerization., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Life as we know it would not exist without water. However, water molecules not only serve as a solvent and reactant but can also promote hydrolysis, which counteracts the formation of essential organic molecules. This conundrum constitutes one of the central issues in origin of life. Hydrolysis is an important part of energy metabolism for all living organisms but only because, inside cells, it is a controlled reaction. How could hydrolysis have been regulated under prebiotic settings? Lower water activities possibly provide an answer: geochemical sites with less free and more bound water can supply the necessary conditions for protometabolic reactions. Such conditions occur in serpentinising systems, hydrothermal sites that synthesise hydrogen gas via rock-water interactions. Here, we summarise the parallels between biotic and abiotic means of controlling hydrolysis in order to narrow the gap between biochemical and geochemical reactions and briefly outline how hydrolysis could even have played a constructive role at the origin of molecular self-organisation., (© 2020 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Despite its role in spin density functional theory and it being the basic observable for describing and understanding magnetic phenomena, few studies have appeared on the electron spin density subtleties thus far. A systematic full topological analysis of this function is lacking, seemingly in contrast to the blossoming in the last 20 years of many studies on the topological features of other scalar fields of chemical interest. We aim to fill this gap by unveiling the kind of information hidden in the spin density distribution that only its topology can disclose. The significance of the spin density critical points, the 18 different ways in which they can be realized and the peculiar topological constraints on their number and kind, arising from the presence of positive and negative spin density regions, is addressed. The notion of molecular spin graphs, spin maxima (minima) joining paths, spin basins and of their valence is introduced. We show that two kinds of structures are associated with a spin-polarized molecule: the usual one, defined through the electron density gradient, and the magnetic structure, defined through the spin density gradient and composed in general by at least two independent spin graphs, related to spin density maxima and minima. Several descriptors, such as the spin polarization index, are introduced to characterize the properties of spin density critical points and basins. The study on the general features of the spin density topology is followed by the specific example of the water molecule in the 3 B 1 triplet state, using spin density distributions of increasing accuracy.

New particle formation (NPF) involving amines in the atmosphere is considered an aggregation process, during which stable molecular clusters are formed from amines and sulfuric acid via hydrogen bond interaction. In this work, ab initio dynamics simulations of ammonium bisulfate formation from a series of amines, SO 3 , and H 2 O molecules were carried out in the gas phase and at the air-water interface. The results show that reactions between amines and hydrated SO 3 molecules in the gas phase are barrierless or nearly barrierless processes. The reaction rate is related to the basicity of gas-phase amines-the stronger the basicity, the faster the reaction. Furthermore, SO 3 hydrolysis catalyzed by amines occurs simultaneously with H 2 SO 4 -amine cluster formation. At the air-water interface, reactions between amines and SO 3 involve multiple water molecules. The reaction center's ring structure (amine-SO 3 -nH 2 O) promotes the transfer of protons in the water molecules. The formed ammonium cation (-RNH 3 + ) and the bisulfate anion (HSO 4 - ) are present and stable by means of hydrogen bond interaction. The cluster formation mechanism provides new insights into NPF involving amines, which may play an important role in the formation of aerosols in some heavily polluted areas - e.g., those with a high amine concentration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier Ltd.)

Polycyclic aromatic hydrocarbons (PAHs) formation and inhibition from supercritical water gasification (SCWG) of cyanobacterial biomass were investigated. High reaction temperature, long residence time, and low feedstock concentration favoured higher molecular weight (HMW) PAH formation. The total PAH yield reached 34.80 μg g -1 at 500 °C, 22.5 MPa, and 10 min. The main PAHs formed in the liquid phase and the solid residue were 3-ring and 4-ring PAHs, which were generated from the cycloaddition reaction of lower molecular weight (LMW) PAHs. In addition, 2-ring PAHs were produced from the Diels-Alder reaction of phenols and unsaturated hydrocarbons. The possible control methods for PAH formation during the SCWG of cyanobacterial biomass were proposed. H 2 O 2 addition effectively inhibited the reaction pathways underlying PAH formation, and the addition at more than 1.0% concentration suppressed H 2 production. The work revealed that the inhibition of PAHs was achieved in terms of improving the oxidisation condition during the SCWG process for converting wet biomass or organic wastes to energy sources., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The behavior of molecules confined to small spaces is fascinating chemistry and lies at the heart of signaling processes in biology. Our approach to confinement is through reversible encapsulation of small molecules in synthetic containers. We show that confinement leads to amplified reactivities in bimolecular reactions, stabilization of otherwise reactive species, and limitation in motions that create new stereochemical arrangements. The isolation of molecules from solvent makes for manageable computations and has stimulated theorist to examine reaction details in the limited space. Transition states for reactions and rearrangements can be calculated, the effects of (de)solvation can be evaluated and the magnetic properties of the containers can be compared with experimental observations. Finally, we outline several potential applications, including entanglement chemistry and the use of isomers in data storage.

Continuous reaction networks, which do not rely on purification or timely additions of reagents, serve as models for chemical evolution and have been demonstrated for compounds thought to have played important roles for the origins of life such as amino acids, hydroxy acids, and sugars. Step-by-step chemical protocols for ribonucleotide synthesis are known, but demonstrating their synthesis in the context of continuous reaction networks remains a major challenge. Herein, compounds proposed to be important for prebiotic RNA synthesis, including glycolaldehyde, cyanamide, 2-aminooxazole, and 2-aminoimidazole, are generated from a continuous reaction network, starting from an aqueous mixture of NaCl, NH 4 Cl, phosphate, and HCN as the only carbon source. No well-timed addition of any other reagents is required. The reaction network is driven by a combination of γ radiolysis and dry-down. γ Radiolysis results in a complex mixture of organics, including the glycolaldehyde-derived glyceronitrile and cyanamide. This mixture is then dried down, generating free glycolaldehyde that then reacts with cyanamide/NH 3 to furnish a combination of 2-aminooxazole and 2-aminoimidazole. This continuous reaction network models how precursors for generating RNA and other classes of compounds may arise spontaneously from a complex mixture that originates from simple reagents., Competing Interests: The authors declare no competing interest.

Predicting the effects of organic compounds on environments and biological systems is an important objective for environmental chemistry and human health. The logarithm (to base 10) of the n-octanoll-water partition coefficient has been widely used to predict the mentioned properties. However, the suitability of this parameter for the purpose has been questioned, since the environments relating to the properties may be quite different from that of bulk n-octanol. In this study, we used a theoretical derivation approach to develop a model for predicting the partition coefficients of solutes between water and an organic solvent that may be similar to n-octanol or quite different from it. Our model relies on solute descriptors that can be calculated based on solute structures. It was used to predict the n-octanoll-water, hexadecanel-water and chloroforml-water partition coefficients of solutes. The calculated values of the examined parameters agreed well with their experimental counterparts. The model can find application in the accurate prediction of the effects of organic compounds on environments and the physicochemical properties of organic compounds by a full in-silico approach and can provide useful guidance for improving some properties of organic compounds., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Effective representation of a molecule is required to develop useful quantitative structure-property relationships (QSPR) for accurate prediction of chemical properties. The octanol-water partition coefficient logP, a measure of lipophilicity, is an important property for pharmacological and toxicological endpoints used in the pharmaceutical and regulatory spheres. We compare physicochemical descriptors, structural keys, and circular fingerprints in their ability to effectively represent a chemical space and characterise molecular features to correlate with lipophilicity. Exploratory landscape continuity analyses revealed that whole-molecule physicochemical descriptors could map together compounds that were similar in both molecular features and logP, indicating higher potential for use in logP QSPRs compared to the substructural approach of structural keys and circular fingerprints. Indeed, logP QSPR models parameterised by physicochemical descriptors consistently performed with the lowest error. Our best performing model was a stochastic gradient descent-optimised multilinear regression with 1438 descriptors, returning an internal benchmark RMSE of 1.03 log units. This corroborates the well-established notion that lipophilicity is an additive, whole-molecule property. We externally tested the model by participating in the 2019 SAMPL6 logP Prediction Challenge and blindly predicting for 11 protein kinase inhibitor fragment-like molecules. Our model returned an RMSE of 0.49 log units, placing eighth overall and third in the empirical methods category (submission ID 'hdpuj'). Permutation feature importance analyses revealed that physicochemical descriptors could characterise predictive molecular features highly relevant to the kinase inhibitor fragment-like molecules.

The Z-scheme MIL-100(Fe)/PANI composite photocatalysts were facilely prepared from MIL-100(Fe) and polyaniline (PANI) by ball-milling, and were characterized by powder X-ray diffraction (PXRD), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), UV-visible diffuse-reflectance spectrometry (UV-vis DRS), X-ray photoelectron spectroscopy (XPS) and photoluminescence emission spectrometry (PL). The photocatalytic activities of MIL-100(Fe)/PANI composites were investigated via tetracycline degradation and hexavalent chromium reduction in aqueous solution under the irradiation of white light. The results revealed that the MIL-100(Fe)/PANI composite photocatalysts exhibited outstanding photocatalytic activities toward Cr(VI) reduction and tetracycline decomposition. The effects of pH and coexisting ions on the photocatalytic Cr(VI) reduction were investigated. As well, the primary active species were identified via electron spin resonance (ESR) determination. A possible Z-scheme photocatalyst mechanism was proposed and verified. Finally, MIL-100(Fe)/PANI composites demonstrated good reusability and stability in water solution, implying potentially practical applications for real wastewater treatment., Competing Interests: Declaration of competing interest On behalf of all authors, I declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work entitled “Polyaniline modified MIL-100(Fe) for enhanced photocatalytic Cr(VI) reduction and tetracycline degradation under white light”., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The octanol-air partition coefficient (K OA ) is useful to assess the fate of organic chemicals in the environment. Very recently, an interesting comparison of current methods to predict this property (Chemosphere 148 (2016) 118-125) highlighted a newly introduced Quantitative Structure-Property Relationship (QSPR), as a group-contribution (GC) method and a quantum chemical solvation model were reported to yield significantly less accurate results. Based on the observation that the so-called GC method investigated in this earlier study was inconsistent with the temperature dependence of K OA , the previously recommended QSPR is presently compared to the geometrical fragment (GF) additivity scheme. In addition to providing some improvement in terms of accuracy, this fragment-based procedure exhibits many advantages in terms of simplicity, interpretability, applicability and availability., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Application of a small radius of the hydrogen atom in molecular-mechanical models of hydrogen bonding improves the estimate of the solvation free energy of organic substances. At the same time, the density and evaporation heat of the bulk water vary slightly and are close to experimental values. Blind testing drug candidates in the SAMPL6 simulation competition showed that using the same Lennard-Jones hydrogen parameters for the hydroxyl, hydroxycarbonyl, amino, and amide groups is enough to predict log P octanol-water with MAE 0.67 and RMSD 0.75.

Within the framework of the 6th physical property blind challenge (SAMPL6) the authors have participated in predicting the octanol-water partition coefficients (logP) for several small drug like molecules. Those logP values where experimentally known by the organizers but only revealed after the submissions of the predictions. Two different sets of predictions were submitted by the authors, both based on the COSMOtherm implementation of COSMO-RS theory. COSMOtherm predictions using the FINE parametrization level (hmz0n) obtained the highest accuracy among all submissions as measured by the root mean squared error. COSMOquick predictions using a fast algorithm to estimate σ-profiles and an a posterio machine learning correction on top of the COSMOtherm results (3vqbi) scored 3rd out of 91 submissions. Both results underline the high quality of COSMO-RS derived molecular free energies in solution.

The SAMPL Challenges aim to focus the biomolecular and physical modeling community on issues that limit the accuracy of predictive modeling of protein-ligand binding for rational drug design. In the SAMPL5 log D Challenge, designed to benchmark the accuracy of methods for predicting drug-like small molecule transfer free energies from aqueous to nonpolar phases, participants found it difficult to make accurate predictions due to the complexity of protonation state issues. In the SAMPL6 log P Challenge, we asked participants to make blind predictions of the octanol-water partition coefficients of neutral species of 11 compounds and assessed how well these methods performed absent the complication of protonation state effects. This challenge builds on the SAMPL6 p[Formula: see text] Challenge, which asked participants to predict p[Formula: see text] values of a superset of the compounds considered in this log P challenge. Blind prediction sets of 91 prediction methods were collected from 27 research groups, spanning a variety of quantum mechanics (QM) or molecular mechanics (MM)-based physical methods, knowledge-based empirical methods, and mixed approaches. There was a 50% increase in the number of participating groups and a 20% increase in the number of submissions compared to the SAMPL5 log D Challenge. Overall, the accuracy of octanol-water log P predictions in SAMPL6 Challenge was higher than cyclohexane-water log D predictions in SAMPL5, likely because modeling only the neutral species was necessary for log P and several categories of method benefited from the vast amounts of experimental octanol-water log P data. There were many highly accurate methods: 10 diverse methods achieved RMSE less than 0.5 log P units. These included QM-based methods, empirical methods, and mixed methods with physical modeling supported with empirical corrections. A comparison of physical modeling methods showed that QM-based methods outperformed MM-based methods. The average RMSE of the most accurate five MM-based, QM-based, empirical, and mixed approach methods based on RMSE were 0.92 ± 0.13, 0.48 ± 0.06, 0.47 ± 0.05, and 0.50 ± 0.06, respectively.

Partition coefficients describe the equilibrium partitioning of a single, defined charge state of a solute between two liquid phases in contact, typically a neutral solute. Octanol-water partition coefficients ([Formula: see text]), or their logarithms (log P), are frequently used as a measure of lipophilicity in drug discovery. The partition coefficient is a physicochemical property that captures the thermodynamics of relative solvation between aqueous and nonpolar phases, and therefore provides an excellent test for physics-based computational models that predict properties of pharmaceutical relevance such as protein-ligand binding affinities or hydration/solvation free energies. The SAMPL6 Part II octanol-water partition coefficient prediction challenge used a subset of kinase inhibitor fragment-like compounds from the SAMPL6 [Formula: see text] prediction challenge in a blind experimental benchmark. Following experimental data collection, the partition coefficient dataset was kept blinded until all predictions were collected from participating computational chemistry groups. A total of 91 submissions were received from 27 participating research groups. This paper presents the octanol-water log P dataset for this SAMPL6 Part II partition coefficient challenge, which consisted of 11 compounds (six 4-aminoquinazolines, two benzimidazole, one pyrazolo[3,4-d]pyrimidine, one pyridine, one 2-oxoquinoline substructure containing compounds) with log P values in the range of 1.95-4.09. We describe the potentiometric log P measurement protocol used to collect this dataset using a Sirius T3, discuss the limitations of this experimental approach, and share suggestions for future log P data collection efforts for the evaluation of computational methods.