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In this paper, a combined approach based on a k-means algorithm and statistical analysis has been applied successfully to classify 500 cytotoxic agents using 21 molecular descriptors. The k-means algorithm applied on the first two principal components split the observations into homogeneous clusters, in order to examine similarities and dissimilarities between molecules within and between clusters. Three clusters are clearly distinguished and the percentage of molecules in each cluster is 50%, 24.88%, and 25.12% for cluster 1, cluster 2, and cluster 3, respectively. Silhouette analysis is used as a cluster validation method, confirming that all the molecules are very well clustered. The silhouette indices obtained for each cluster are 0.53 for cluster 1, 0.60 for cluster 2, and 0.57 for cluster 3. Therefore, the average silhouette index obtained is 0.56. The value of the Hopkins statistic obtained is 0.922 confirming that the dataset is highly clusterable. In addition, the paragons of each cluster have been identified. The test statistic was performed to characterize each cluster by a subset of molecular descriptors. Moreover, in silico screening of pharmacological properties ADME and evaluation of drug-likeness of molecules showed that cluster 1 molecules have the best ADME profile and drug-likeness. The quantitative analysis of molecular electrostatic potential (MEP) on van der Waals surface was performed to identify the nucleophilic and electrophilic sites in the paragons molecules. Finally, molecular docking was performed for the paragon molecules on six different targets. Docking studies support the results observed in the MEP analysis showing that the favorable reactive sites of molecules are involved in strong hydrogen interactions with the functional residues of receptors.

The generally greater degree of thermal motion of guest molecule(s) relative to the host often impedes their accurate modelling in crystal structures. We propose a 'rule-of-thumb' for estimating the maximum number of guest molecules that can be accommodated in a given amount of accessible space in an adequately modelled host structure. A survey of the Cambridge Structural Database was carried out to evaluate the fractional occupancy θ of the accessible space for almost 40 000 solvates involving 20 common solvents. Using widely accessible software tools, the volume of a guest is estimated as its van der Waals surface, while the guest-occupiable space of a potentially porous host is determined as that available to a virtual spherical probe. We propose terminology more appropriate to the supramolecular interpretation of surface typology: the probe-traversable and probe-accessible boundaries as traced out by the locus and surface of a spherical probe, respectively. High-throughput analysis using commercial and free software packages yielded a mean θ = 51.1(4)%, ranging from 45.3(6)% for hexane to 60(1)% for acetic acid.

In the present work, a combined approach based on conceptual-DFT formalism and molecular docking simulations were performed to investigate the chemical reactivity of six Benzodiazepine analogs. Chemical reactivity descriptors derived from the conceptual DFT were determined and discussed to explain the global and local reactivity of the six studied analogs. Also, long-range interactions were studied using the quantitative analyses of molecular electrostatic potential (MEP) on van der Waals surface to identify the nucleophilic and electrophilic sites. Moreover, a statistical analysis was performed to assess the robustness of atomic charges to the basis set. The results revealed that Hirshfeld population analysis (HPA) was the most efficient for this purpose. Molecular docking simulations were performed to predict the binding affinities of the issued molecules and estimate the binding poses into four binding sites, three of them were recently discovered, located in GABAA receptor. DOI: http://dx.doi.org/10.17807/orbital.v13i4.1607

Aim and Objective:A Quantitative Structure-Activity Relationship (QSAR) has been widely developed to derive a correlation between chemical structures of molecules to their known activities. In the present investigation, QSAR models have been carried out on 76 Camptothecin (CPT) derivatives as anticancer drugs to develop a robust model for the prediction of physicochemical properties.Materials and Methods:A training set of 60 structurally diverse CPT derivatives was used to construct QSAR models for the prediction of physiochemical parameters such as Van der Waals surface area (SvdW), Van der Waals Volume (VvdW), Molar Refractivity (MR) and Polarizability (α). The QSAR models were optimized using Multiple Linear Regression (MLR) analysis. A test set of 16 compounds was evaluated using the defined models.:The Genetic Algorithm And Multiple Linear Regression Analysis (GA-MLR) were used to select the descriptors derived from the Dragon software to generate the correlation models that relate the structural features to the studied properties.Results:QSAR models were used to delineate the important descriptors responsible for the properties of the CPT derivatives. The statistically significant QSAR models derived by GA-MLR analysis were validated by Leave-One-Out Cross-Validation (LOOCV) and test set validation methods. The multicollinearity and autocorrelation properties of the descriptors contributed in the models were tested by calculating the Variance Inflation Factor (VIF) and the Durbin–Watson (DW) statistics.Conclusion:The predictive ability of the models was found to be satisfactory. Thus, QSAR models derived from this study may be helpful for modeling and designing some new CPT derivatives and for predicting their activity.

The mechanism by which the absorption wavelength of a molecule is modified by a protein is known as spectral tuning. Spectral tuning is often achieved by electrostatic interactions that stabilize/destabilize or modify the shape of the excited and ground-state potential energy surfaces of the chromophore. We present a protocol for the construction of three-dimensional "electrostatic spectral tuning maps" that describe how vertical excitation energies in a chromophore are influenced by nearby charges. The maps are built by moving a charge on the van der Waals surface of the chromophore and calculating the change in its excitation energy. The maps are useful guides for protein engineering of color variants, for interpreting spectra of chromophores that act as probes of their environment, and as starting points for further quantum mechanical/molecular mechanical studies. The maps are semiquantitative and can approximate the magnitude of the spectral shift induced by a point charge at a given position with respect to the chromophore. We generate and discuss electrostatic spectral tuning maps for model chromophores of photoreceptor proteins, fluorescent proteins, and aromatic amino acids. Such maps may be extended to other properties such as oscillator strengths, absolute energies (stability), ionization energies, and electron affinities.

The presence of a surface preferably attracting one component of a polymer mixture by the long-range van der Waals surface potential while the mixture undergoes phase separation by spinodal decomposition is called long-range surface-directed spinodal decomposition (SDSD). The morphology achieved under SDSD is an enrichment layer(s) close to the wall surface and a droplet-type structure in the bulk. In the current study of the long-range surface-directed polymerization-induced phase separation, the surface-directed spinodal decomposition of a monomer&ndash, solvent mixture undergoing self-condensation polymerization was theoretically simulated. The nonlinear Cahn&ndash, Hilliard and Flory&ndash, Huggins free energy theories were applied to investigate the phase separation phenomenon. The long-range surface potential led to the formation of a wetting layer on the surface. The thickness of the wetting layer was found proportional to time t*1/5 and surface potential parameter h11/5. A larger diffusion coefficient led to the formation of smaller droplets in the bulk and a thinner depletion layer, while it did not affect the thickness of the enrichment layer close to the wall. A temperature gradient imposed in the same direction of long-range surface potential led to the formation of a stripe morphology near the wall, while imposing it in the opposite direction of surface potential led to the formation of large particles at the high-temperature side, the opposite side of the interacting wall.

A Si(111):GaSe van der Waals surface is prepared using sequential deposition of Ga and Se at elevated temperature on a Si(111)-7��7 surface. Surface properties were investigated by soft x-ray photoelectron spectroscopy and low-energy electron diffraction. The Si(111)-1��1:GaSe surface remains with electronic surface potentials near flatband condition.

The computational modeling of molecules under high pressure is a growing research area that augments experimental high-pressure chemistry. Here, a new electronic structure method for modeling atoms and molecules under pressure, the Gaussians On Surace Tesserae Simulate HYdrostatic Pressure (GOSTSHYP) approach, is introduced. In this method, a set of Gaussian potentials is distributed evenly on the van der Waals surface of the investigated chemical system, leading to a compression of the electron density and the atomic scaffold. Since no parameters other than the pressure need to be specified, GOSTSHYP allows straightforward geometry optimizations and ab initio Molecular Dynamics simulations of chemical systems under pressure for non-expert users. Calculated energies, bond lengths and dipole moments under pressure fall within the range of established computational methods for high-pressure chemistry. A Diels-Alder reaction and the cyclotrimerization of acetylene showcase the ability of GOSTSHYP to model pressure-induced chemical reactions. The connection to mechanochemistry is pointed out.

Nanodiamond (ND)-reinforced polymer composites attract a great deal of attention; however, insufficient understanding of their reinforced behavior is greatly limiting their further design and application. In this paper, a microscopic investigation of the stretched processes of aminated ND and resin composites is undertaken to elucidate the reinforcement mechanism of ND in the polymer matrix by employing molecular dynamics and semi-empirical quantum chemistry simulations. The stretching process and reinforcement behavior are observed on the nanoscale, and the nano-pinning effect of ND on the resin matrix is clarified. Further analyses indicate that due to the increase of system volume, the interactions between the ND and resin molecules increase with stretching; this facilitates the combination of ND and resin molecules and thus recovers the breakage of the resin matrix. This recovery process is regarded as the origin of the ND reinforcement of the polymer. The strong interaction between the ND and resin molecules is quantitatively assessed by the interpenetration of the van der Waals surface and the reduced density gradient analysis of electrons using quantum chemistry calculations. The high stability of their noncovalent combination is also revealed. This investigation provides an excellent approach for revealing the origin of ND reinforcement behavior and thus facilitates further optimization of the performance of the ND-polymer composites.

The current study comprises a systematic investigation to assess retention properties and selectivity of a mixed-mode reversed-phase/weak-anion-exchange (RP/WAX) stationary phase to aid method development. Retention was investigated for different compound classes which vary in hydrophobicity, van der Waals surface area, and charge as function of organic content, pH, and ionic strength of the mobile phase. The linear-solvent-strength model was successfully applied for aromatic hydrocarbons to obtain retention-time predictions based on log P values and van der Waals surface area values. For phenols, predictions were based on log P values and data from a single scouting run performed in isocratic mode to estimate the S parameter; the deviations between experimental and predicted retention times were smaller than 6%. To describe the mixed-mode (RP/WAX) retention behavior of singly and doubly negatively-charged aromatic acids, a novel model combining the linear-solvent-strength and the empirical stoichiometric-displacement-net-charge models is proposed and validated. Using combinations of three scouting runs that are not linearly dependent, the maximum prediction error was 11% and changes in selectivity were correctly forecasted when altering the mobile-phase composition, i.e., either organic modifier content or ionic strength. When using nine scouting runs in combination with a least-squares regression approach to determine the model parameters, the maximum prediction error was 6%.

Motivation Bivalent ligands are increasingly important such as for targeting G protein-coupled receptor (GPCR) dimers or proteolysis targeting chimeras (PROTACs). They contain two pharmacophoric units that simultaneously bind in their corresponding binding sites, connected with a spacer chain. Here, we report a molecular modelling tool that links the pharmacophore units via the shortest pathway along the receptors van der Waals surface and then scores the solutions providing prioritization for the design of new bivalent ligands. Results Bivalent ligands of known dimers of GPCRs, PROTACs and a model bivalent antibody/antigen system were analysed. The tool could rapidly assess the preferred linker length for the different systems and recapitulated the best reported results. In the case of GPCR dimers the results suggest that in some cases these ligands might bind to a secondary binding site at the extracellular entrance (vestibule or allosteric site) instead of the orthosteric binding site. Availability and implementation Freely accessible from the Molecular Operating Environment svl exchange server (https://svl.chemcomp.com/). Supplementary information Supplementary data are available at Bioinformatics online.

Graphical Abstract A guide for the selection of predictive models is provided, which considers various solute and solvent properties, such as molecular mass, functional group diversity and hydrophobia/hydrophilia Unlabelled image, The assumptions and models for solubility modelling or prediction in systems using non-polar solvents, or water and complex triterpene and other active pharmaceutical ingredients as solutes aren't well studied. Furthermore, the assumptions concerning heat capacity effects (negligibility, experimental values or approximations) are explored, using non-polar solvents (benzene), or water as reference solvents, for systems with solute melting points in the range of 306–528 K and molecular weights in the range of 90–442 g/mol. New empirical estimation methods for the ΔfusCpi of APIs are presented which correlate the solute molecular masses and van der Waals surface areas with ΔfusCpi. Separate empirical parameters were required for oxygenated and non-oxygenated solutes. Subsequently, the predictive capabilities of the various approaches to solubility modelling for complex pharmaceuticals, for which data is limited, are analysed. The solute selection is based on a principal component analysis, considering molecular weights, fusion temperatures, and solubilities in a non-polar solvent, alcohol, and water, where data was available. New NRTL-SAC parameters were determined for selected steroids, by regression. The original UNIFAC, modified UNIFAC (Dortmund), COSMO-RS (OL), and COSMO-SAC activity coefficient predictions are then conducted, based on the availability of group constants and sigma profiles. These are undertaken to assess the predictive capabilities of these models when each assumption concerning heat capacity is employed. The predictive qualities of the models are assessed, based on the mean square deviation and provide guidelines for model selection, and assumptions concerning phase equilibrium, when designing solid–liquid separators for the pharmaceutical industry on process simulation software. The most suitable assumption regarding ΔfusCpi was found to be system specific, with modified UNIFAC (Dortmund) performing well in benzene as a solvent system, while original UNIFAC performs better in aqueous systems. Original UNIFAC outperforms other predictive models tested in the triterpene/steroidal systems, with no significant influence from the assumptions regarding ΔfusCpi.

Originally, the Carnot cycle is a theoretical thermodynamic cycle that provides an upper limit on the efficiency that any classical thermodynamic engine can achieve during the conversion of heat into work, or conversely, the efficiency of a refrigeration system in creating a temperature difference by the application of work to the system. The aim of this paper is to introduce and study the economic Carnot cycles into a Roegenian economy, using our Thermodynamic-Economic Dictionary. Of course, the most difficult questions are: what is the economic significance of such a cycle? Roegenian economics is acceptable or not, in terms of practical applications? Our answer is yes for both questions., Bicentennial of the University Politehnica of Bucharest 1818-2018 Centenary of Romanian Great Union 1818-2018

The information of the acute oral toxicity for most polycyclic aromatic hydrocarbons (PAHs) in mammals are lacking due to limited experimental resources, leading to a need to develop reliable in silico methods to evaluate the toxicity endpoint. In this study, we developed the quantitative structure-activity relationship (QSAR) models by genetic algorithm (GA) and multiple linear regression (MLR) for the rat acute oral toxicity (LD50) of PAHs following the strict validation principles of QSAR modeling recommended by OECD. The best QSAR model comprised eight simple 2D descriptors with definite physicochemical meaning, which showed that maximum atom-type electrotopological state, van der Waals surface area, mean atomic van der Waals volume, and total number of bonds are main influencing factors for the toxicity endpoint. A true external set (554 compounds) without rat acute oral toxicity values, and 22 limit test compounds, were firstly predicted along with reliability assessment. We also compared our proposed model with the OPERA predictions and recently published literature to prove the prediction reliability. Furthermore, the interspecies toxicity (iST) models of PAHs between rat and mouse were also established, validated and employed for filling data gap. Overall, our developed models should be applicable to new or untested or not yet synthesized PAHs falling within the applicability domain (AD) of the models for rapid acute oral toxicity prediction, thus being important for environmental or personal exposure risk assessment under regulatory frameworks.

Voxel-based 3D convolutional neural networks (CNNs) have been applied to predict protein-ligand binding affinity. However, the memory usage and computation cost of these voxel-based approaches increase cubically with respect to spatial resolution and sometimes make volumetric CNNs intractable at higher resolutions. Therefore, it is necessary to develop memory-efficient alternatives that can accelerate the convolutional operation on 3D volumetric representations of the protein-ligand interaction. In this study, we implement a novel volumetric representation, OctSurf, to characterize the 3D molecular surface of protein binding pockets and bound ligands. The OctSurf surface representation is built based on the octree data structure, which has been widely used in computer graphics to efficiently represent and store 3D object data. Vanilla 3D-CNN approaches often divide the 3D space of objects into equal-sized voxels. In contrast, OctSurf recursively partitions the 3D space containing the protein-ligand pocket into eight subspaces called octants. Only those octants containing van der Waals surface points of protein or ligand atoms undergo the recursive subdivision process until they reach the predefined octree depth, whereas unoccupied octants are kept intact to reduce the memory cost. Resulting non-empty leaf octants approximate molecular surfaces of the protein pocket and bound ligands. These surface octants, along with their chemical and geometric features, are used as the input to 3D-CNNs. Two kinds of CNN architectures, VGG and ResNet, are applied to the OctSurf representation to predict binding affinity. The OctSurf representation consumes much less memory than the conventional voxel representation at the same resolution. By restricting the convolution operation to only octants of the smallest size, our method also alleviates the overall computational overhead of CNN. A series of experiments are performed to demonstrate the disk storage and computational efficiency of the proposed learning method. Our code is available at the following GitHub repository: https://github.uconn.edu/mldrugdiscovery/OctSurf .

The properties of two- and three-atomic clusters of neon are studied. Based on the Faddeev differential equations in the total angular momentum representation, we have calculated the lowest binding energies for the neon trimer. The results obtained are compared with previous published results

The adenosine receptors have appeared as potent and selective drug target in various diseases especially for central nervous system diseases. Adenosine receptor A2A antagonists have been known as potential treatment for Parkinson’s disease (PD). Radiolabeled A2AR antagonists can be used as positron emission tomography (PET) tracers and diagnostic tools for PD. In the present investigation, we perform the quantitative structure–activity relationship (QSAR) analysis and docking studies of a series of PET tracers as ligands and Adenosine receptors (A2AR) binding affinity, to elucidate the structural properties required for A2AR antagonist in treatment for PD. Several variable-selection methods were used to choose the descriptors that would lead to good QSAR model. Among several models developed, the best model was a five-variable multiple linear regression (MLR) equation with statistical parameters of squared correlation coefficient R 2 = 0.90 ± 0.01 and cross-validated correlation coefficient Q 2 = 0.84 ± 0.02. The QSAR models were also constructed for A2AR selectivity to tracer ligands, that yielded a four-variable model with R 2 = 0.94 ± 0.01 and Q 2 = 0.89 ± 0.02. The most important variables contributed in models construction involved: partial charge, hydrophobic atoms, rotatable bonds, polar van der Waals surface area, potential energy, and conformation-dependent charge descriptors. Finally, molecular docking analysis was carried out to better understand the interactions between ligands and Adenosine receptors. The importance of π-π stacking interactions between aromatic moiety of the ligands and triazine core of A2AR antagonist was confirmed.

Nanoporous graphene membrane (NGM) has enormous potential and excellent properties in practical applications. But almost all of the previous studies were based on the assumption that the nanopores were symmetric along the normal vector of the graphene plane. Asymmetric nanoporous graphene membrane (A-NGM), a promising membrane material in energy, environment and bionic, was seldom researched until now. A kind of graphene membrane with asymmetric semisphere nanopore embedded in it is designed. Such a membrane is provided with the properties of A-NGM. Its electron properties and van der Waals surface are analyzed by quantum chemistry approach. Permeation mechanism of helium, neon and argon across this graphene membrane is analyzed by employing Langmuir adsorption isotherm. Molecular dynamics simulations are used to characterize the asymmetric performance of A-NGM for gas permeance. The driving force of these dynamical processes is revealed by implementing noncovalent interaction analysis. These results are considered not only assist in the designing of asymmetric membrane material, but also pave the way toward the realization of unidirectional graphene membrane in the future.

We investigated the photoelectrical properties of the heterojunctions p-GaTe – n-InSe fabricated by the method of mechanical contact of GaTe oxidized plate with van der Waals surface of InSe. The AFM-images revealed that there was formed thin oxide dielectric layer of Ga2O3 on the heterointerface p-GaTe – n-InSe. The energy band diagram was constructed. It was established that the p-GaTe – n-InSe heterojunction is photosensitive in the spectral range 0.74 - 1.0 µm. Key words: InSe, GaTe, layered crystals, heterojunction, AFM-images spectral characteristics.

The newly discovered hybrid boron nitride-carbon nanotubes (BN-CNTs) are very promising for the innovative design of next-generation nanocomposites. In this work, molecular dynamics simulation-based pull-out studies have been performed to characterise the interfacial properties of BN-CNT reinforced polyethylene (PE) composites. Our results show that the interfacial shear strength (ISS) of BN-CNT/PE nanocomposites strongly depends on the BN composition and the connecting pattern of the C/BN fragment in the embedded BN-CNTs. Specifically, an ISS about 90% greater than that of the PE composite reinforced by the conventional carbon nanotube (CNT) is detected in the composite reinforced by the BN-CNT with certain connecting pattern and BN concentration. Such a superior ISS in the BN-CNT/PE composites is found to mainly originate from the unique rough van der Waals surface of the BN-CNT and the greater binding interaction between the embedded BN-CNT and the PE matrix, both of which contribute to enhancing the interface load transfer of nanocomposites. The enhanced ISS detected in the composite reinforced by BN-CNTs suggests that, compared with the most commonly used CNT, the novel BN-CNT can be a better reinforcement candidate in the design of nanocomposites.

An accurate van der Waals force field (VDW FF) was derived from highly precise quantum mechanical (QM) calculations. Small molecular clusters were used to explore van der Waals interactions between gas molecules and porous materials. The parameters of the accurate van der Waals force field were determined by QM calculations. To validate the force field, the prediction results from the VDW FF were compared with standard FFs, such as UFF, Dreiding, Pcff, and Compass. The results from the VDW FF were in excellent agreement with the experimental measurements. This force field can be applied to the prediction of the gas density (H2 , CO2 , C2 H4 , CH4 , N2 , O2 ) and adsorption performance inside porous materials, such as covalent organic frameworks (COFs), zeolites and metal organic frameworks (MOFs), consisting of H, B, N, C, O, S, Si, Al, Zn, Mg, Ni, and Co. This work provides a solid basis for studying gas adsorption in porous materials. © 2017 Wiley Periodicals, Inc.

We prove van der Waals–London's law of decay of the van der Waals force for a collection of neutral atoms at large separation.© 2017 Wiley Periodicals, Inc.

A method for computing quasi-relativistic two-component dispersion energies is developed and implemented in the TURBOMOLE program package. The method is based on the Casimir–Polder formula for dispersion energies, which occurs in symmetry-adapted perturbation theory. The method is applied to evaluate the dispersion energies of a small set of van der Waals complexes involving heavy elements such as gold, mercury and bismuth.

It is well known that the Van der Waals equation is a modification of the ideal gas law, yet it can be used to describe both gas and liquid, and some important messages can be obtained from this state equation. However, the Van der Waals equation is not a precise state equation, and it does not give a good description of the law of corresponding states. In this paper, we expand the Van der Waals equation into its Taylor’s series form, and then modify the fourth order expansion by changing the constant Virial coefficients into their analogous ones. Via this way, a more precise result about the law of corresponding states has been obtained, and the law of corresponding states can then be expressed as: in terms of the reduced variables, all fluids should obey the same equation with the analogous Virial coefficients. In addition, the system of 3 He with quantum effects has also been taken into consideration with our modified Van der Waals equation, and it is found that, for a normal system without quantum effect, the modification on ideal gas law from the Van der Waals equation is more significant than the real case, however, for a system with quantum effect, this modification is less significant than the real case, thus a factor is introduced in this paper to weaken or strengthen the modification of the Van der Waals equation, respectively.

Understanding the nature of non-covalent interactions (NCIs) between asphaltene molecules is not only theoretically interesting but also important for practical application. We performed quantum chemical calculations to reveal the configuration feature and intermolecular interaction characteristics of asphaltene dimers using three representative asphaltene model compounds and their derivatives. The frontier molecular orbitals and electrostatic potential map of the model asphaltenes were analyzed to reveal the nature of interaction between the asphaltene monomers. The calculation of binding energies indicates that the stability of asphaltene dimers not only depends upon the number of aromatic rings but also relies on the presence of heteroatoms in the aromatic core and aliphatic side chains, which could change the electrostatic charge distribution on the molecular van der Waals surface. In addition, NCIs and the natural bond order analysis method were used to identify the interactions that promote the form...

A comprehensive first-principles study of the electronic properties of twisted 2D transition metal dichalcogenide (TMDC) heterobilayers MX2/MoS2 (M = Mo, Cr, W; X = S, Se) with different rotation angles has been performed. The van der Waals (vdW) interaction is found to have an important effect on the electronic structure of two-dimensional (2D) TMDC heterobilayers. Compared to non-twisted heterobilayers, the interlayer distance of twisted heterobilayers increases appreciably, thereby changing the vdW interaction of the heterobilayers as well as the electronic structure of the MX2/MoS2 systems. As a result, for CrSe2/MoS2 and MoSe2/MoS2 systems, the indirect bandgap (Γ–K) exhibits a notable enlargement (about 0.1 eV), leading to the indirect-to-direct gap transition. At twisting angles between 13.2° and 46.8°, the interlayer distance is nearly constant for the mismatched lattices over the entire sample, resulting in nearly the same electronic structure. Even after considering the spin–orbit coupling (SOC) effect, the indirect-to-direct transition is still predicted to occur in the WS2/MoS2 heterobilayer due to the large spin–orbit splitting.

Close contacts, defined as interatomic separations less than the sum of the respective van der Waals radii, are commonly invoked to identify attractive nonbonded interactions in crystal lattices. While this is often effective, it can also be misleading because (a) there are significant uncertainties associated with van der Waals radii, and (b) it may not be valid to attribute the interactions solely to specific pairs of atoms. The interactions within crystal lattices are Coulombic, and the strongest positive and/or negative regions do not always correspond to the positions of atoms; they are sometimes located between atoms. Examples of both types are given and discussed, focusing in particular upon σ-hole interactions.

The van der Waals interactions are responsible for a large diversity of structures and functions in chemistry, biology, and materials. Discussion of van der Waals interactions has focused on the attractive potential energy that varies as the inverse power of the distance between the two interacting partners. The origin of the attractive force is widely discussed as being due to the correlated fluctuations of electron charges that lead to instantaneous dipole-induced dipole attractions. Here, we use the inelastic tunneling probe to image the potential energy surface associated with the van der Waals interactions of xenon atoms.

An approach to constructing two-phase state regions for real gases, the state of which is described by the modified van der Waals equation in the form proposed by R.L. Fogel’son and E.R. Likhachev, has been discussed.

(Eco)toxicological information of natural deep eutectic solvents (NADES) is scarce, and thus, quantitative structure activity relationship (QSAR) models are an important tool for achieving the prediction of toxicity in this case. For that reason, in this manuscript, a new QSAR model for predicting the ecotoxicity of NADES towards the Aliivibrio fischeri biomodel, using mixing rules, is proposed. The main advantage of the method is that the individual components of the mixtures are molecularly modelled, and then, a mixing rule is used, which simplifies the process. For developing the model, a total of 11 descriptors for each component is used: the dissociation constant, partition coefficient, Van der Waals volume, Van der Waals surface area, topological polar surface area, solvent accessible surface area, minimum projection area, maximum projection area, minimum projection radius, maximum projection radius and molecular weight. The final obtained model includes the topological polar surface area and the dissociation constant, mechanistically interpreted as the ability of a NADES to transport through biological membranes and the severe negative effect of pH on the toxicity and biological response of Aliivibrio fischeri bacteria. The OECD Guidance Document on the Validation of (Quantitative) Structure-Activity Relationships is followed to develop the mathematical model.

Angewandte Chemie. International Edition, 58 (29), ISSN:1433-7851, ISSN:1521-3773, ISSN:0570-0833

Although the inverse gas chromatography technique has been used to measure the surface acid-base properties for almost 50 years, several basic problems still hinder its further development and application. One of the problems is that for the polar probe molecules of dichloromethane, acetone, ethyl acetate, tetrahydrofuran, and ethanol, the molecular area of each probe has different values in literature. In this paper, we point out the incorrect molecular area values presented in the literature by comparing these values with those indicated in Smallwood's Handbook of Organic Solvent Properties. The correct molecular area values of 11 polar probes are determined by plotting the molecular areas of the polar probes versus the van der Waals surface areas reported in the handbook. The correct molecular areas for six common polar probes, namely, dichloromethane, trichloromethane, acetone, ethyl acetate, diethyl ether, and tetrahydrofuran, are 38.0, 44.0, 42.5, 48.0, 47.0, and 45.0 A2, respectively. Benzene is a specific molecule with a conjugated π-bond structure, and its molecular area is estimated to be larger than that of other molecules. Therefore, benzene is unsuitable for use as a probe molecule.

Most often in chemical physics, long range van der Waals surface interactions are approximated by the exact asymptotic result at vanishing distance, the well known additive approximation of London dispersion forces due to Hamaker. However, the description of retardation effects that is known since the time of Casimir is completely neglected for lack of a tractable expression. Here we show that it is possible to describe surface van der Waals forces at arbitrary distances in one single simple equation. The result captures the long sought crossover from non-retarded (London) to retarded (Casimir) interactions, the effect of polarization in condensed media and the full suppression of retarded interactions at large distance. This is achieved with similar accuracy and the same material properties that are used to approximate the Hamaker constant in conventional applications. The results show that at ambient temperature, retardation effects significantly change the power law exponent of the conventional Hamaker result for distances of just a few nanometers., Comment: 6 pages + 4 figures + supplementary material

An essential but missing component in our understanding of microbial interactions leading to coal bed methane (CBM) formation lies in the relationship between coal and coal-adhering microorganisms. Here, we explored the influence of surface physico-chemistry on the microbial cell attachment on coal, utilising a known coal-oxidising bacterium P. fluorescens Pf-5 as a model. Based on the interfacial free energy of adhesion calculation and direct observation of cell adhesion on coal, natural lignite and subbituminous coals offered the most conducive surface for cell attachment driven by favourable hydrophobic and acid-base interactions. Coal pretreatments dramatically decreased coal surface hydrophobicity and increased its electron-donating potential (γ−), resulting in unfavourable interaction with cells that were hydrophilic and possessed high γ−. An exception to this was peroxide treatment, which maintained a low γ− of the coal surface and allowed favourable coal-cell interaction to occur. Cell colonisation on lignite appeared to be the strongest amongst all coal types, likely due to the relatively high van der Waals surface energy component that influence the adhesion strength in favourable cell-coal interactions. This would partly explain the higher methanogenic potential found in lignite compared to subbituminous coal in previous studies, as more adsorbed cells potentially lead to greater liberation of small organic compounds. Although our cell enumeration results generally correlated with the thermodynamic data, some exceptions were present that signify the biological role in cell-to-coal attachment and biofilm formation. Overall, these findings provide insights into the fundamental parameters that are involved in cell-coal adhesion dynamics at the molecular level.

A highly versatile and efficient ultrasound promoted synthesis of xanthenedione derivatives is achieved through condensation of dimedone with various aromatic aldehydes using boric acid as catalyst in ethanol-water medium. The advantages of this method being, mild reaction conditions, short reaction time, easy work-up, purification of products by non-chromatographic methods and additionally this method provides excellent yields. Two of the Xanthendiones derivatives 3a and 3b gave good crystals on recrystallization and their molecular structures were confirmed by crystallographic studies. The molecules in the crystal lattice are held together by weak intermolecular C-H•••O and C-H•••N interactions. Further insights into these interactions using Hirshfeld surface analysis and DFT/B3LYP studies show that in compound 3a H•••H (54.7%), O•••H (18.3%) and in 3b H•••H (53.7%), O•••H (17.6%) are the major contributors to the intermolecular interactions which stabilize the crystal structures. In order to determine molecular electrical transport properties, we studied the energy difference between Highest Occupied, HOMO, and Lowest Unoccupied, LUMO orbitals and the HOMO and LUMO energy gap for compounds 3a and 3b was found to be 3.9261 eV and 4.6436 eV respectively. The 2D fingerprint plot provided percentage contribution of each individual atom-to-atom interactions. The Mulliken atomic charges and molecular electrostatic potential on molecular van der Waals surface were calculated to know the electrophilic and nucleophilic regions of the molecular surface.

A method is presented to analyse the interaction energies in a nanocluster, which is consisting of three neutral molecules bound by non-covalent long range Van der Waals forces. One of the molecules (M0) in the nanocluster has a permanent dipole moment, whereas the two other molecules (M1 and M2) are non-polar. Analytical expressions are obtained for the numerical calculation of the dispersion and induction energies of the molecules in the considered nanocluster. The repulsive forces at short intermolecular distances are taken into account by introduction of damping functions. Dispersion and induction energies are calculated for a nanocluster with a definite geometry, in which the polar molecule M0 is a linear hydrocarbon molecule C5H10 and M1 and M2 are pyrene molecules. The calculations are done for fixed distances between the two pyrene molecules. The results show that the induction energies in the considered three-molecular nanocluster are comparable with the dispersion energies. Furthermore, the sum of induction energies in the substructure (M0, M1) of the considered nanocluster is much higher than the sum of induction energies in a two-molecular nanocluster with similar molecules (M0, M1) because of the absence of an electrostatic field in the latter case. This effect can be explained by the essential intermolecular induction in the three-molecular nanocluster.

The crystalline structures of four homologues of the 1,2-dibromo-4,5-dialkoxybenzene series [Br2C6H2(OCn H2n+1)2 for n = 2, 12, 14 and 18] have been solved by means of single-crystal crystallography. Comparison along the series, including the previously reported n = 10 and n = 16 derivatives, shows a clear metric trend (b and c essentially fixed along the series and a growing linearly with n), in spite of some subtle differences in space groups and/or packing modes. A uniform packing pattern for the aliphatic chains has been found for the n = 12 to 18 homologues, which slightly differs from that of the n = 10 derivative. The crystalline structures of all the higher homologues (n = 10-18) seem to arise from van der Waals interchain interactions and, to a lesser extent, type II Br⋯Br interactions. The dominant role of interchain interactions provides direct structural support for the usual interpretation of melting point trends like that found along this series. Atoms in Molecules (AIM) analysis allows a comparison of the relative magnitude of the interchain and Br⋯Br interactions, an analysis validated by the measured melting enthalpies. Fil: Suarez, Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Constituyentes; Argentina Fil: Müller, Federico Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; Argentina Fil: Gutierrez Suburu, Matias Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; Argentina Fil: Fonrouge, Ana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; Argentina Fil: Baggio, Ricardo Fortunato. Comisión Nacional de Energía Atómica. Centro Atómico Constituyentes; Argentina Fil: Cukiernik, Fabio Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; Argentina

The high moisture content of low-rank coals (LRCs) is associated with the noncovalent interactions between coal and water, such as hydrogen bonding and van der Waals attraction. In this study, the molecular model of lignite was constructed and its electrostatic potential (ESP) on a van der Waals surface was analyzed. The mechanism of water absorption on the hydrophilic or hydrophobic sites of the lignite surface was investigated based on the atoms in molecules analysis and reduced density gradient analysis of seven typical lignite···water complexes. The regions with the most negative and positive ESP values were associated with oxygen in oxygen functional groups, and hydrogen was associated with smaller electronegativity. The typical hydrogen bonds O–H···O were formed between water and oxygen functional groups, whereas the weaker hydrogen bonds C–H···O were formed between water and the skeleton components of lignite, such as the benzene ring and methyl and methylene groups. Oxygen functional groups were r...

A truncated Fourier decomposition of the atom–substrate potential energy is developed for three-dimensional models of van der Waals systems, specifically for adsorption on the basal plane surface of graphite or the (111) face of a face-centered-cubic lattice. This provides a framework for analysis of a priori calculations of physical adsorption energies.

Most nanoporous solids, such as metal–organic frameworks and zeolites, are composed of extended three-dimensional covalent or coordination bond networks. Nevertheless, an increasing number of porous molecular crystals have been reported that display surface areas and separation efficiencies rivaling those of conventional porous materials. In this investigation, a geometry-based analysis and molecular simulations were used to screen over 150000 organic molecular crystal structures, resulting in the identification of 481 potential organic porous molecular crystals, a testament to the rarity of these materials. Subsequently, we have computed the surface area and pore dimensions of these structures. This computer-generated database has been used to uncover a number of trends and properties that had not previously been quantified due to the limited number of reported porous molecular crystals. Finally, we have used machine learning to show that the van der Waals surface area and other related descriptors of molecular size are the molecular properties best able to predict a crystal's propensity to form structural voids, which are strong indicators of permanent porosity. We posit that the identified database is a promising resource for discovering candidate structures for gas-separation applications and providing general design guidelines for the production of new porous crystals.

It is currently admitted that the intermolecular forces implicated in Gas Liquid Chromatography (GLC) can be expressed as a product of parameters (or descriptors) of solutes and of parameters of solvents. The present study is limited to those of solutes, and among them the three ones are involved in the Van der Waals forces, whereas the two ones involved in the hydrogen bonding are left aside at this stage. These three studied parameters, which we call δ, ω and e, respectively reflect the three types of Van der Waals forces: dispersion, orientation or polarity strictly speaking, and induction-polarizability. These parameters have been experimentally obtained in previous studies for 121 Volatile Organic Compounds (VOC) via an original Multiplicative Matrix Analysis (MMA) applied to a superabundant and accurate GLC data set. Then, also in previous studies, attempts have been made to predict these parameters via a Simplified Molecular Topology procedure (SMT). Because these last published results have been somewhat disappointing, a promising new strategy of prediction is developed and detailed in the present article.

International audience; Van der Waals (vdW) interactions are important in numerous physical, chemical, and biological systems. However, traditional density functional theory (DFT) within local or semi-local approximations can hardly treat this interaction. Among various attempts to handle vdW interactions in DFT, semi-empirical correction methods are known to present the advantages of low additional computational costs and easy implementation in conventional DFT codes. In this review, we summarize the state-of-the-art semi-empirical vdW correction methods based on pairwise summations within the atoms-in-molecules scaling framework, such as the Grimme's D3 methods and variants of the Tkatchenko-Scheffler method. In addition, we compare the performance of these methods for systems ranging from molecules to solids, which have dispersive to ionic interactions: 128 molecular pairs, 23 molecular crystals, 4 noble gas crystals, 27 two-dimensional layered materials, and 9 ionic crystals. (c) 2015 Wiley Periodicals, Inc.

Analytical formula to determine van der Waals (vdW) interlayer coefficients of nested spherical fullerenes is suggested. The continuum approximation together with the Lennard–Jones potential is utilized. It is shown herein that the greatest contribution to the vdW interaction comes from the adjacent layers and the contribution from a remote layer may be neglected. The vdW interaction is found to be strongly dependent on the radius of the layer, especially when the radius is small enough (

Resonant micro-Raman spectra and the morphology of the interlayer Van der Waals surface are studied for layered thin films of n-Bi2Te3 and solid solutions based on Bi2Te3. It is found that the composition, thickness, surface morphology, and the method of obtaining films affect the relative intensity of Raman phonons, which are sensitive to the topological surface states of Dirac fermions.

Linear and non-linear quantitative structure–property relationship (QSPR) models were developed to predict corrosion inhibition efficiency for a series of 41 pyridine and quinoline N-heterocycles. Out of 20 physicochemical and quantum chemical variables related to the surface adsorption behaviour of the inhibitors, consensus models were constructed using the genetic algorithm-partial least squares (GA-PLS) and genetic algorithm-artificial neural network (GA-ANN) methods. The consensus GA-PLS model comprised of eight variables (exponential of the calculated adsorption energy, LUMO, van der Waals surface area and volume, polarizability, electron affinity, electrophilicity, electron donor capacity) exhibited an %RMSECV of 16.5% and mean %RMSE of 14.9%. Such a model moderately captured the complex relationships between inhibition efficiency and the quantum chemical variables. The consensus GA-ANN model comprised of nine input variables (exponential of the calculated adsorption energy, HOMO, LUMO, HOMO-LUMO Gap, electronegativity, softness, electrophilicity, electron donor capacity and N atomic charge) exhibited an %RMSECV of 16.7 ± 2.3% and mean %RMSE (training/testing/validation) of 8.8%, performing better than its linear counterpart in terms of predictive ability. Both models revealed the importance of adsorption to the metal surface, and electronic parameters quantifying electron acceptance/donation to/from the iron surface, suggesting key corrosion inhibition design principles.

The separation of eleven antibiotics and ten metabolites were studied using high performance liquid chromatography. The C18-PFP octadecyl with integral PFP, C18-AR octadecyl with integral phenyl, C18-HL octadecyl and phenyl phase were used as stationary phases. Mixtures of acetontrile-0.1 % formic acid in water were investigated as mobile phases. The elution order of the target compounds was similar for all four HPLC columns applied. The best separation was obtained using the column with the pentafluorophenylpropyl chain. In addition, in order to optimize the parameters of retention elution for the column and to predict the conditions for the best separation of the active compounds studied biologically the ChromSword software was used. To obtain reliable information of the physicochemical properties and to estimate the relative biological activity of a group of the studied analytes, the QSRR approach was applied. Molecular descriptors were calculated using the HyperChem software. The study was based on multiple linear regression and the results were presented as quantitative structure-retention relationships equations. The QSRR models were determined using 16 molecular descriptors mainly related to the dipole moment (μ), the solvent accessible surface area (SAS), the van der Waals surface area (VWS), the minimum charge (δmin) as well as the polar surface area (PSA). Moreover, structural descriptors of the target compounds were used to describe their chromatographic retention behavior under the optimized HPLC conditions.