New atoms-in-molecules dispersion models for use in ab initio derived force fields.

Recently, substantial research efforts have gone into bridging the accuracy-efficiency gap between parameterized force field models and quantum chemical calculations by extracting molecule-specific force fields directly from ab initio data in a robust and automated manner. One of the challenging aspects is deriving localized atomic polarizabilities for pairwise distributed dispersion models. The Tkatchenko-Scheffler model is based upon correcting free-atom C6 coefficients according to the square of the ratio of the atom-in-molecule volume to the free-atom volume. However, it has recently been shown that a more accurate relationship can be found if static atomic polarizabilities are also taken into account. Using this relationship, we develop two modified Tkatchenko-Scheffler dispersion models and benchmark their performance against SAPT2+3 reference data and other commonly used dispersion models.

Structural investigations of molecular solutes within nanostructured ionic liquids.

Ionic liquids (ILs) containing sufficiently long alkyl chains form amphiphilic nanostructures with well-defined polar and non-polar domains. Here we have explored the robustness of these amphiphilic nanostructures to added solutes and gained insight into how the nature of the solute and IL ions affect the partitioning of these solutes within the nanostructured domains of ILs. To achieve this, small angle X-ray scattering (SAXS) investigations were performed and discussed for mixtures of 9 different molecular compounds with 6 different ILs containing imidazolium cations. The amphiphilic nanostructure of ILs persisted to high solute concentrations, over 50 mol% of added solute for most 1-butyl-3-methylimidazolium ILs and above 80 mol% for most 1-decyl-3-methylimidazolium ILs. Solute partitioning within these domains was found to be controlled by the inherent polarity and size of the solute, as well as specific interactions between the solute and IL ions, with SAXS results corroborated with IR spectroscopy and molecular dynamics simulations. Molecular dynamics simulations also revealed the ability to induce π+-π+ stacking between imidazolium cations through the use of these added molecular compounds. Collectively, these results provide scope for the selection of IL ions to rationally influence and control the partitioning behaviour of given solutes within the amphiphilic nanostructure of ILs.

Temperature-Dependent Blue Shifting of O-H Stretching Frequencies in Crystalline Cellulose Explained.

Increasing the temperature of a chemical system generally causes covalent bonds to lengthen and weaken, often the first step in initiating chemical reactions. However, for some hydrogen-bonded systems, infrared (IR) spectroscopy measurements reveal that covalent O-H bonds actually strengthen and therefore shorten when heated. In 1957, Finch and Lippincott proposed a simple one-dimensional (1D) model to explain this effect, in which thermal excitation of intermolecular stretching modes leads to lengthening and weakening of intermolecular O-H···O hydrogen bonds, thereby indirectly strengthening the associated covalent O-H bonds. Taking cellulose (an infinitely repeating polymer of d-glucose) as an example, we use molecular dynamics modeling to show that the same mechanism is responsible for temperature-dependent blue shifting of O-H stretching bands in IR spectra of carbohydrate biopolymers, except that interchain hydrogen bonds are weakened by thermal excitation of chain-separation modes, while intrachain hydrogen bonds are weakened by thermally induced changes in ring puckering and orientation of ring substituents but not reorientation of glucose units relative to one another or overall twisting of the cellulose chains.

CherryPicker: An Algorithm for the Automated Parametrization of Large Biomolecules for Molecular Simulation.

Molecular simulations allow investigation of the structure, dynamics and thermodynamics of molecules at an atomic level of detail, and as such, are becoming increasingly important across many areas of science. As the range of applications increases, so does the variety of molecules. Simulation of a new type of molecule requires generation of parameters that result in accurate representation of the behavior of that molecule, and, in most cases, are compatible with existing parameter sets. While many automated parametrization methods exist, they are in general not well suited to large and conformationally dynamic molecules. We present here a method for automated assignment of parameters for large, novel biomolecules, and demonstrate its usage for peptides of varying degrees of complexity. Our method uses a graph theoretic representation to facilitate matching of the target molecule to molecular fragments for which reliable parameters are available. It requires minimal user input and creates parameter files compatible with the widely-used GROMACS simulation software.

Automated simultaneous assignment of bond orders and formal charges.

Bond orders and formal charges are fundamental chemical descriptors. In cheminformatic applications it is necessary to be able to assign these properties to a given molecular structure automatically, given minimal input information. Here we describe a method for determining the bond order and formal charge assignments from only the atom types and connectivity. Our method utilises a graph theoretical description of electron positions. Each electron position assignment is scored according to lookup tables of atomic and bond dissociation energies derived from quantum chemical calculations. We tested three different optimisation methods-local optimisation, an A* pathfinding method, and an FPT optimisation method utilising tree decompositions-for finding the best electron position assignment, from which the bond orders and formal charges are extracted. We show that our method can assign bond orders and formal charges at a high degree of accuracy across a wide range of molecules from two different databases, and that the FPT algorithm provides the best combination of speed and accuracy.

Characterisation of N-(Octadecyl)-1,8-naphthalimide Monolayer Compression Using Molecular Dynamics and Experimental Approaches.

The development of luminescent surfaces is an active area of supramolecular chemistry, particularly for the development of new sensing platforms. One particularly useful surface deposition method is the Langmuir-Blodgett technique where organic amphiphilic fluorophores (e.g. 1,8-naphthalimides) can form ordered monolayers at an air-water interface before being deposited onto solid supports. The ability to simulate monolayer formation and consequently develop predictability over film formation would allow for significant advances in the luminescent materials field where synthesis might be directed by simulation data. Here, we compare pressure-area isotherms of N-(octadecyl)-1,8-naphthalimide determined experimentally, using the Langmuir-Blodgett technique, and computationally, using three different simulation techniques. We find that all three simulation techniques are able to describe the liquid-condensed/liquid-expanded region of the isotherm, and that the isotherms are highly similar in this region, although the NγT ensemble performs best. Experimental isotherms showed film formation properties that align with the simulation data, suggesting that simulations are a viable means to direct synthesis. Investigation of the underlying structural details disclosed by the simulations reveals the compression-induced ordering at atomic-level detail, which will allow prediction of how functionalisation of the naphthalimides will alter the monolayer compression and mounting process.