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Accurate determination of intermolecular non-covalent-bonded or non-bonded interactions is the key to potentially useful molecular dynamics simulations of polymer systems. However, it is challenging to balance both the accuracy and computational cost in force field modelling. One of the main difficulties is properly representing the calculated energy data as a continuous force function. In this paper, we employ well-developed machine learning techniques to construct a general purpose intermolecular non-bonded interaction force field for organic polymers. The original ab initio dataset SOFG-31 was calculated by us and has been well documented, and here we use it as our training set. The CLIFF kernel type machine learning scheme is used for predicting the interaction energies of heterodimers selected from the SOFG-31 dataset. Our test results show that the overall errors are well below the chemical accuracy of about 1 kcal/mol, thus demonstrating the promising feasibility of machine learning techniques in force field modelling. [ABSTRACT FROM AUTHOR]

Abstract: Design and synthesis of organoselenium compounds with high thiol peroxidase (TPx) and low thiol oxidase (TOx) activities have been a difficult task and remains a synthetic-activity relationship dilemma. In this regard we are reporting for the first time a detail experimental data (both in vitro and in vivo) about the anti-oxidant and toxicological profile of an Imine (–Ning organoselenium compound (Compound A). The TPx activity of Compound A was significantly higher than diphenyl diselenide (DPDS). Both Compound A and DPDS protected sodium nitropruside (SNP) induced thiobarbituric acid reactive species (TBARS) production in rats tissue homogenate with significantly higher activity observed for Compound A than DPDS (p <0.05). The Compound A also exhibited strong antioxidant activity in the DPPH and ABTS radical scavenging assays. This study reveals that an imine group close to selenium atom drastically enhances the catalytic activities in the aromatic thiol (PhSH) assay systems. The oxidation of biologically significant thiols reflects the toxicity of the compounds. However, the present data showed that treatment with Compound A at 0, 10, 25 or 50mg/kg was not associated with mortality or body weight loss. Similarly it did not inhibit α-ALA-D and Na+1/K+1 ATPase (sulfhydryl group containing enzymes) activities after acute oral treatment; rather it enhanced non-protein thiols (NPSH) concentration. The Compound A did not cause any oxidative stress as measured by TBARS production in rat''s tissue preparation. Our data also indicate that exposure to Compound A did not affect plasma transaminase activities or levels of urea and creatinine in rats. Ascorbic acid is always considered a marker of oxidative stress and the reduction of its content may indicate an increase in oxidative stress. Treatment with Compound A did not alter Ascorbic acid levels in rats. The conducted in vitro and in vivo tests show the versatile therapeutic potential of this compound in the area of free radical induced damages, will undoubtedly enhance our understanding of the mechanism of model compounds and may ultimately yield insights that result in improved GPx mimics. [Copyright &y& Elsevier]

[Display omitted] • The collaboration of non-bonded interactions changes pulling force and facilitate ascorbic acid transporting inside CPNTs. • Hydrogen atoms of ascorbic acid have more contributions than its oxygen atoms in interaction with water molecules and CPNTs. • The configurational entropy of ascorbic acid changes in the transport pathway when the molecule moves throughout CPNTs. • The range of the binding energy changes of ascorbic acid with the peptide rings of each of CPNTs is different. Cyclic peptide nanotubes (CPNTs) are potential candidates for drug delivery, separation and recovery technologies, as well as self-assembling nanomaterials. In this study, we investigated the L-ascorbic acid transport behaviour through two CPNTs using computational studies, including quantum calculations, molecular docking and steered molecular dynamics (SMD) simulations. Two cyclic peptide nanotubes 8 × [L-Gln-(D-Leu-L-Trp) 4-D-Leu-] (QLWL) and 8 × [(D-Ala-L-Ala) 5] (AA), embedded in a fully hydrated membrane composed of DPPC/POPC/POPS/cholesterol, were considered. Our findings from SMD simulations revealed that ascorbic acid moves differently in AA nanotube compared to QLWL nanotube. The analysis of the number of hydrogen bonds shows that the hydrogen atoms of ascorbic acid hydroxyl groups form more hydrogen bonds compared to oxygen atoms with water molecules and the CPNTs. This result was supported using the calculations of radial distribution functions of various atoms of the ascorbic acid near the oxygen atom of water molecules and carbonyl groups of the CPNTs during the transport pathway in the lumen of each CPNTs. Entropy calculations show that the configurational entropy of ascorbic acid in the transport pathway is not monotonous, and it changes due to variable behaviour when the molecule moves throughout CPNTs. The interactions that the nanotubes form with their environment play an important role in the binding energy of ascorbic acid with each of the peptide ring that the binding energy value is significant for each of the peptide rings with ascorbic acid. These informations can be useful to future applications and studies in the field of nanoscience and nanotechnology, such as drug delivery and nanosensors. [ABSTRACT FROM AUTHOR]

A knowledge-based method for calculating the similarity of functional groups is described and validated. The method is based on experimental information derived from small molecule crystal structures. These data are used in the form of scatterplots that show the likelihood of a non-bonded interaction being formed between functional group A (the `central group') and functional group B (the `contact group' or `probe'). The scatterplots are converted into three-dimensional maps that show the propensity of the probe at different positions around the central group. Here we describe how to calculate the similarity of a pair of central groups based on these maps. The similarity method is validated using bioisosteric functional group pairs identified in the Bioster database and Relibase. The Bioster database is a critical compilation of thousands of bioisosteric molecule pairs, including drugs, enzyme inhibitors and agrochemicals. Relibase is an object-oriented database containing structural data about protein-ligand interactions. The distributions of the similarities of the bioisosteric functional group pairs are compared with similarities for all the possible pairs in IsoStar, and are found to be significantly different. Enrichment factors are also calculated showing the similarity method is statistically significantly better than random in predicting bioisosteric functional group pairs. [ABSTRACT FROM AUTHOR]

We compare experimental melting curves of short heterogeneous DNA oligomers with theoretical curves derived from statistical mechanics. Partition functions are computed with the one-dimensional Peyrard-Bishop (PB) Hamiltonian, already used in the study of the melting of long DNA chains. Working with short chains we take into account, in the computations, not only the breaking of the interstrand hydrogen bonds, but also the complete dissociation of the double helix into separate single strands. Since this dissociation equilibrium is of general relevance, independent of the particular microscopic model, we give some details of its treatment. We discuss how the non bonded three-dimensional interactions, not explicitly considered in the one-dimensional PB model, are taken into account through the treatment of the dissociation equilibrium. We also evaluate the relevance of the dissociation as a function of the chain length. [ABSTRACT FROM AUTHOR]

This paper describes a (6-8) variant of the Lennard-Jones (6-12) potential,for computing the energy of non-bonded interactions in molecular mechanicscalculations, which combines the overall precision of the Buckingham (6-exp)potential with the computational efficiency of the standard Lennard-Jones(6-12) potential. There is also a note on the radius of convergence of thefull matrix Newton–Raphson optimization procedure. [ABSTRACT FROM AUTHOR]

The understanding of polymer solution thermodynamics and characterization of pressure effects on fundamental polymer physics of macromolecular systems is significant in the manufacturing of polyolefins. Consequently, numerous experimental and theoretical efforts have been made towards understanding phase behavior of polymer solutions at elevated pressures. Despite this progress, only limited efforts are directed towards understanding the underlying phenomena behind the influence of high pressure upon the thermophysical properties of ternary polymer solutions at a molecular level. The present paper, therefore, reports on the influence of supercritical ethylene on the density of PE + hydrocarbon solvent system by exploring ternary mixtures of PE + hexane + ethylene for ethylene concentrations up to 10 wt% at varied temperatures and in a pressure range from 100 to 1000 bar via fully-atomistic molecular dynamics (MD) simulations. Additionally, the modified Sanchez-Lacombe equation of state (EOS) model is iteratively solved to capture the pressure, concentration, and temperature dependence of ternary PE solution density. It is shown that the small amounts of ethylene dissolved in the liquid mixtures of PE + hexane significantly decreases the polymer solution density. The presence of unreacted monomer in the solution polymerization process utilized in PE manufacturing was found to substantially lower the PE solution density particularly at the lower end of the investigated pressure range. This noteworthy reduction in mixture density as a consequence impacts design and operation of the liquid-liquid phase separator in manufacturing of PE via solution polymerization. Another key point to bear in mind is that the mixture density exhibits fairly less sensitivity to ethylene amount as external pressure raises. Nevertheless, pressure, solvent composition, and temperature dependence of density display less sensitivity as pressure increases. In relation to the characterization of the impact of addition of ethylene an atomistic-level insight is provided, which proves to be of great value in revealing intermolecular interactions in the binary subsystems of polymer/solvent/monomer. The MD computations are shown to be in excellent agreement with the theoretical EOS model, confirming the validity of the proposed methodology. Furthermore, the adopted OPLS-AA has been found a reliable atomistic force field, which provides detailed molecular information on the thermophysical properties of polyolefin in hydrocarbon solutions. Ultimately, it is demonstrated that the MD simulations complement parametric EOS predictions and costly experimental approaches. Image 1 • The ternary PE solution density raises with increase in pressure stemming from remarkable variations in non-bonded interactive forces. • The MD-simulated data were found to be in quantitative accordance with the EOS model. • The adopted OPLS atomistic force field is a highly reliable to gain in-depth insights into polyolefin in hydrocarbon solvents. • Molecular modeling supplies an abundant amount of knowledge on variations in intra- and intermolecular interactions versus pressure. [ABSTRACT FROM AUTHOR]