Mathematical and computational modeling of fats and triacylglycerides.

Fats and oils are found in many food products; however, their macroscopic properties are difficult to predict, especially when blending different fats or oils together. With difficulties in sourcing specific fats or oils, whether due to availability or pricing, food companies may be required to find alternative sources for these ingredients, with possible differences in ingredient performance. Mathematical and computational modeling of these ingredients can provide a quick way to predict their properties, avoiding costly trials or manufacturing problems, while, most importantly, keeping the consumers happy. This review covers a range of mathematical models for triacylglycerides (TAGs) and fats, namely, models for the prediction of melting point, solid fat content, and crystallization temperature and composition. There are a number of models that have been designed for both TAGs and fats and which have been shown to agree very well with empirical measurements, using both kinetic and thermodynamic approaches, with models for TAGs being used to, in turn, predict fat properties. The last section describes computational models to simulate the behavior of TAGs using molecular dynamics (MD). Simulation of TAGs using MD, however, is still at an early stage, although the most recent papers on this topic are bringing this area up to speed.

Martinoid: the peptoid martini force field.

Many exciting innovations have been made in the development of assembling peptoid materials. Typically, these have utilised large oligomeric sequences, though elsewhere the study of peptide self-assembly has yielded numerous examples of assemblers below 6-8 residues in length, evidencing that minimal peptoid assemblers are not only feasible but expected. A productive means of discovering such materials is through the application of in silico screening methods, which often benefit from the use of coarse-grained molecular dynamics (CG-MD) simulations. At the current level of development, CG models for peptoids are insufficient and we have been motivated to develop a Martini forcefield compatible peptoid model. A dual bottom-up and top-down parameterisation approach has been adopted, in keeping with the Martini parameterisation methodology, targeting the reproduction of atomistic MD dynamics and trends in experimentally obtained log D7.4 partition coefficients, respectively. This work has yielded valuable insights into the practicalities of parameterising peptoid monomers. Additionally, we demonstrate that our model can reproduce the experimental observations of two very different peptoid assembly systems, namely peptoid nanosheets and minimal tripeptoid assembly. Further we can simulate the peptoid helix secondary structure relevant for antimicrobial sequences. To be of maximum usefulness to the peptoid research community, we have developed freely available code to generate all requisite simulation files for the application of this model with Gromacs MD software.

Minimal Peptoid Dynamics Inform Self-Assembly Propensity.

Peptoids are structural isomers of natural peptides, with side chain attachment at the amide nitrogen, conferring this class of compounds with the ability to access both cis and trans ω torsions as well as an increased diversity of ψ/φ states with respect to peptides. Sampling within these dimensions is controlled through side chain selection, and an expansive set of viable peptoid residues exists. It has been shown recently that "minimal" di- and tripeptoids with aromatic side chains can self-assemble into highly ordered structures, with size and morphological definition varying as a function of sequence pattern (e.g., XFF and FXF, where X = a nonaromatic peptoid monomer). Aromatic groups, such as phenylalanine, are regularly used in the design of minimal peptide assemblers. In recognition of this, and to draw parallels between these compounds classes, we have developed a series of descriptors for intramolecular dynamics of aromatic side chains to discern whether these dynamics, in a preassembly condition, can be related to experimentally observed nanoscale assemblies. To do this, we have built on the atomistic peptoid force field reported by Weiser and Santiso (CGenFF-WS) through the rigorous fitting of partial charges and the collation of Charmm General Force Field (CGenFF) parameters relevant to these systems. Our study finds that the intramolecular dynamics of side chains, for a given sequence, is dependent on the specific combination of backbone ω torsions and that homogeneity of sampling across these states correlates well with the experimentally observed ability to assemble into nanomorphologies with long-range order. Sequence patterning is also shown to affect sampling, in a manner consistent for both tripeptoids and tripeptides. Additionally, sampling similarities between the nanofiber forming tripeptoid, Nf-Nke-Nf in the cc state, and the nanotube forming dipeptide FF, highlight a structural motif which may be relevant to the emergence of extended linear assemblies. To assess these properties, a variety of computational approaches have been employed.

Predicting Lipid Eutectics Using Coarse-Grained Molecular Dynamics.

Binary triacylglyceride (TAG) systems are known to exhibit nonlinear/eutectic behavior, and predicting this is not straightforward unless the thermodynamic properties of the constituent TAGs are known. While this kind of behavior has been shown previously using molecular dynamics, this was carried out using an atomistic force field and fully saturated symmetric TAGs. In this study, we simulate the changing melting point of binary unsaturated asymmetric TAG systems using a coarse-grained force field. While the simulated melting temperatures of the various TAG ratios are generally found to be less than the empirical values, the nonlinear/eutectic behavior is reproduced very well for the three different binary TAG systems used. Hence, this opens up the possibility of being able to simulate the behavior of different, unknown TAG systems.

[3+2]-Cycloaddition Reactions of gem-Difluorocyclopropenes with Azomethine Ylides - Access to Novel Fluorinated Scaffolds.

The introduction of fluorinated moieties into drugs as well as the increase of their overall three-dimensionality have become key strategies amongst medicinal chemists to generate sets of compounds with favorable drug-like properties. However, the introduction of fluorinated cyclopropane ring systems which combines both strategies is not widely exploited to date. This paper reports synthetic strategies exploiting the reactivity of gem-difluorocyclopropenes in dipolar cycloaddition reactions with azomethine ylides to afford sets of new fluorine-containing 3-azabicyclo[3.1.0]hexanes. In addition, the unexpected formation of complex trifluorinated scaffolds arising from proline esters and gem-difluorocyclopropenes is highlighted along with computational studies to elucidate the underlying mechanism. This study presents new avenues towards pharmaceutically relevant fluorinated 3-azabicyclo[3.1.0]hexanes that are accessible via robust and short synthetic sequences.

Triacylglyceride melting point determination using coarse-grained molecular dynamics.

This study is carried out using the COGITO force field to determine whether the thermodynamic melting point of pure triacylglyceride crystals can be predicted using molecular dynamics simulations. The triacylglycerides used in this study are both saturated and unsaturated, as well as symmetrical and asymmetrical, to test the robustness of both the force field and the direct heating methodology described in this paper. Given the nonequilibrium nature of a melting system, a larger number of simulations are required to ensure that the results are sufficiently converged, that is, with little fluctuation and a small confidence interval. The study also highlights the importance of the presence of defects, in this case as voids, to lower the melting nucleation energy barrier of the crystals and avoid superheating of the systems being tested. The size of these defects is much larger than what would be found in a physical crystal, however, the simple and robust procedure that was developed allows the accurate prediction of melting points of the different triacylglycerides.

Alkali Metal Dihydropyridines in Transfer Hydrogenation Catalysis of Imines: Amide Basicity versus Hydride Surrogacy.

Catalytic reduction of a representative set of imines, both aldimines and ketimines, to amines has been studied using transfer hydrogenation from 1,4-dicyclohexadiene. Unusually, this has been achieved using s-block pre-catalysts, namely 1-metallo-2-tert-butyl-1,2-dihydropyridines, 2-tBuC5 H5 NM, M(tBuDHP), where M=Li-Cs. Reactions have been monitored in C6 D6 and tetrahydrofuran-d8 (THF-d8 ). A definite trend is observed in catalyst efficiency with the heavier alkali metal tBuDHPs outperforming the lighter congeners. In general, Cs(tBuDHP) is the optimal pre-catalyst with, in the best cases, reactions producing quantitative yields of amines in minutes at room temperature using 5 mol % catalyst. Supporting the experimental study, Density Functional Theory (DFT) calculations have also been carried out which reveal that Cs has a pathway with a significantly lower rate determining step than the Li congener. In the postulated initiation pathways DHP can act as either a base or as a surrogate hydride.

Solvent-controlled self-assembly of Fmoc protected aliphatic amino acids.

Self-assembly of modified amino acids facilitate the formation of various structures that have unique properties and therefore serve as excellent bio-organic scaffolds for diverse applications. Self-assembly of Fmoc protected single amino acids has attracted great interest owing to their ease of synthesis and applications as functional materials. Smaller assembly units enable synthetic convenience and potentially broader adoption. Herein, we demonstrate the ability to control the morphologies resulting from self-assembly of Fmoc modified aliphatic single amino acids (Fmoc-SAAs) namely, Alanine, Valine, Leucine, Isoleucine, and Proline. Controlled morphological transitions were observed through solvent variation and the mechanism that allows this control was investigated using coarse-grained molecular dynamics simulations. These show that FmocA can form well defined crystalline structures through uniform parallel Fmoc stacking and the optimization of ion concentrations, which is not observed for the other Fmoc-SAAs. We demonstrate that Fmoc protected aliphatic single amino acids are novel scaffolds for the design of distinct micro/nanostructures through a bottom-up approach that can be tuned by control of the environmental parameters.

Short Peptide Self-Assembly in the Martini Coarse-Grain Force Field Family.

Pivotal to the success of any computational experiment is the ability to make reliable predictions about the system under study and the time required to yield these results. Biomolecular interactions is one area of research that sits in every camp of resolution vs the time required, from the quantum mechanical level to in vivo studies. At an approximate midpoint, there is coarse-grained molecular dynamics, for which the Martini force fields have become the most widely used, fast enough to simulate the entire membrane of a mitochondrion though lacking atom-specific precision. While many force fields have been parametrized to account for a specific system under study, the Martini force field has aimed at casting a wider net with more generalized bead types that have demonstrated suitability for broad use and reuse in applications from protein-graphene oxide coassembly to polysaccharides interactions.In this Account, the progressive (Martini versions 1 through 3) and peripheral (Sour Martini, constant pH, Martini Straight, Dry Martini, etc.) developmental trajectory of the Martini force field will be analyzed in terms of self-assembling systems with a focus on short (two to three amino acids) peptide self-assembly in aqueous environments. In particular, this will focus on the effects of the Martini solvent model and compare how changes in bead definitions and mapping have effects on different systems. Considerable effort in the development of Martini has been expended to reduce the "stickiness" of amino acids to better simulate proteins in bilayers. We have included in this Account a short study of dipeptide self-assembly in water, using all mainstream Martini force fields, to examine their ability to reproduce this behavior. The three most recently released versions of Martini and variations in their solvents are used to simulate in triplicate all 400 dipeptides of the 20 gene-encoded amino acids. The ability of the force fields to model the self-assembly of the dipeptides in aqueoues environments is determined by the measurement of the aggregation propensity, and additional descriptors are used to gain further insight into the dipeptide aggregates.

COGITO: A Coarse-Grained Force Field for the Simulation of Macroscopic Properties of Triacylglycerides.

The use of molecular dynamics simulations is becoming ever more widespread; however, the application of this to pure triacylglyceride (TAG) systems is not. In this study, we are presenting the development, and validation, of a new force field (FF), which we have called the COarse-Grained Interchangeable Triacylglyceride-Optimized FF. The FF has been developed using both a bottom-up and top-down approach for different parameters, with the non-bonded parameters being optimized using a Bayesian optimization method. While the FF was developed using monounsaturated TAGs, results show that it is also suitable for fully saturated TAGs. Description of molecules which were not used during the development of the FF is carried out simply by interchanging the bead in the molecule topologies. Results show that the FF can reproduce the macroscopic properties (density and lattice parameters) of pure TAGs as both crystals and melt with high accuracy, as well as reproduce the differences in enthalpies.

Integrating Computation, Experiment, and Machine Learning in the Design of Peptide-Based Supramolecular Materials and Systems.

Interest in peptide-based supramolecular materials has grown extensively since the 1980s and the application of computational methods has paralleled this. These methods contribute to the understanding of experimental observations based on interactions and inform the design of new supramolecular systems. They are also used to virtually screen and navigate these very large design spaces. Increasingly, the use of artificial intelligence is employed to screen far more candidates than traditional methods. Based on a brief history of computational and experimentally integrated investigations of peptide structures, we explore recent impactful examples of computationally driven investigation into peptide self-assembly, focusing on recent advances in methodology development. It is clear that the integration between experiment and computation to understand and design new systems is becoming near seamless in this growing field.

Rapid Automated Quantification of Triacylglyceride Crystallinity in Molecular Dynamics Simulations.

The relative stability of crystalline polymorphs and the transition between crystalline and melt phases are key parameters in determining the physical properties of triacylglycerides used in food. However, while the determination of properties experimentally is well-defined, the ability to predict the onset of melting and discriminate between polymorphs is less well-defined within a molecular dynamics simulation environment. In this work, we present metrics for measuring the crystallinity, including a new metric, the near-neighbor occupancy time, giving a rapid determination of how many, and which, molecules are found in a crystal over a simulation trajectory, and the polymorphic determination of triacylglycerides over a simulation trajectory.

Hydrocarbon Soluble Alkali-Metal-Aluminium Hydride Surrog[ATES].

A series of group 1 hydrocarbon-soluble donor free aluminates [AM(t BuDHP)(TMP)Al(i Bu)2 ] (AM=Li, Na, K, Rb) have been synthesised by combining an alkali metal dihydropyridyl unit [(2-t BuC5 H5 N)AM)] containing a surrogate hydride (sp3 C-H) with [(i Bu)2 Al(TMP)]. These aluminates have been characterised by X-ray crystallography and NMR spectroscopy. While the lithium aluminate forms a monomer, the heavier alkali metal aluminates exist as polymeric chains propagated by non-covalent interactions between the alkali metal cations and the alkyldihydropyridyl units. Solvates [(THF)Li(t BuDHP)(TMP)Al(i Bu)2 ] and [(TMEDA)Na(t BuDHP)(TMP)Al(i Bu)2 ] have also been crystallographically characterised. Theoretical calculations show how the dispersion forces tend to increase on moving from Li to Rb, as opposed to the electrostatic forces of stabilization, which are orders of magnitude more significant. Having unique structural features, these bimetallic compounds can be considered as starting points for exploring unique reactivity trends as alkali-metal-aluminium hydride surrog[ATES].

Constant pH Coarse-Grained Molecular Dynamics with Stochastic Charge Neutralization.

pH dependence abounds in biochemical systems; however, many simulation methods used to investigate these systems do not consider this property. Using a modified version of the hybrid non-equilibrium molecular dynamics (MD)/Monte Carlo algorithm, we include a stochastic charge neutralization method, which is particularly suited to the MARTINI force field and enables artifact-free Ewald summation methods in electrostatic calculations. We demonstrate the efficacy of this method by reproducing pH-dependent self-assembly and self-organization behavior previously reported in experimental literature. In addition, we have carried out experimental oleic acid titrations where we report the results in a more relevant way for the comparison with computational methods than has previously been done.

Directed Discovery of Tetrapeptide Emulsifiers.

Oil in water emulsions are an important class of soft material that are used in the food, cosmetic, and biomedical industries. These materials are formed through the use of emulsifiers that are able to stabilize oil droplets in water. Historically emulsifiers have been developed from lipids or from large biomolecules such as proteins. However, the ability to use short peptides, which have favorable degradability and toxicity profiles is seen as an attractive alternative. In this work, we demonstrate that it is possible to design emulsifiers from short (tetra) peptides that have tunability (i.e., the surface activity of the emulsion can be tuned according to the peptide primary sequence). This design process is achieved by applying coarse grain molecular dynamics simulation to consecutively reduce the molecular search space from the 83,521 candidates initially considered in the screen to four top ranking candidates that were then studied experimentally. The results of the experimental study correspond well to the predicted results from the computational screening verifying the potential of this screening methodology to be applied to a range of different molecular systems.

Expanding the Conformational Landscape of Minimalistic Tripeptides by Their O-Glycosylation.

We report on the supramolecular self-assembly of tripeptides and their O-glycosylated analogues, in which the carbohydrate moiety is coupled to a central serine or threonine flanked by phenylalanine residues. The substitution of serine with threonine introduces differential side-chain interactions, which results in the formation of aggregates with different morphology. O-glycosylation decreases the aggregation propensity because of rebalancing of the π interactions. The glycopeptides form aggregates with reduced stiffness but increased thermal stability. Our results demonstrate that the designed minimalistic glycopeptides retain critical functional features of glycoproteins and therefore are promising tools for elucidation of molecular mechanisms involved in the glycoprotein interactome. They can also serve as an inspiration for the design of functional glycopeptide-based biomaterials.

Radical and Ionic Mechanisms in Rearrangements of o-Tolyl Aryl Ethers and Amines Initiated by the Grubbs-Stoltz Reagent, Et3SiH/KOtBu.

Rearrangements of o-tolyl aryl ethers, amines, and sulfides with the Grubbs-Stoltz reagent (Et3SiH + KOtBu) were recently announced, in which the ethers were converted to o-hydroxydiarylmethanes, while the (o-tol)(Ar)NH amines were transformed into dihydroacridines. Radical mechanisms were proposed, based on prior evidence for triethylsilyl radicals in this reagent system. A detailed computational investigation of the rearrangements of the aryl tolyl ethers now instead supports an anionic Truce-Smiles rearrangement, where the initial benzyl anion can be formed by either of two pathways: (i) direct deprotonation of the tolyl methyl group under basic conditions or (ii) electron transfer to an initially formed benzyl radical. By contrast, the rearrangements of o-tolyl aryl amines depend on the nature of the amine. Secondary amines undergo deprotonation of the N-H followed by a radical rearrangement, to form dihydroacridines, while tertiary amines form both dihydroacridines and diarylmethanes through radical and/or anionic pathways. Overall, this study highlights the competition between the reactive intermediates formed by the Et3SiH/KOtBu system.

Reproduction of macroscopic properties of unsaturated triacylglycerides using a modified NERD force field.

Unsaturated triacylglycerides are found in many commonly consumed foods, such as cooking oils, nuts and chocolate. There are however very few publications on Molecular Dynamics simulations of such molecules, and, to the best of our knowledge, no such published research on crystalline mono-unsaturated triacylglycerides. The work described in this paper is an evaluation of different force fields (GROMOS96 and NERD) to determine the best force field parameters to reproduce the crystalline and melted macroscopic properties of such molecules accurately. The best results were obtained by modifying the NERD force field, through which we were able to reproduce the crystalline and melted density as well as crystal dimensions of mono-unsaturated triacylglycerides.

Catalyst design in C-H activation: a case study in the use of binding free energies to rationalise intramolecular directing group selectivity in iridium catalysis.

Remote directing groups in a bifunctional molecule do not always behave independently of one another in C-H activation chemistries. A combined DFT and experimental mechanistic study to provide enhanced Ir catalysts for chemoselective C-H deuteration of bifunctional aryl primary sulfonamides is described. This provides a pharmaceutically-relevant and limiting case study in using binding energies to predict intramolecular directing group chemoselectivity. Rational catalyst design, guided solely by qualitative substrate-catalyst binding free energy predictions, enabled intramolecular discrimination between competing ortho-directing groups in C-H activation and delivered improved catalysts for sulfonamide-selective C-H deuteration. As a result, chemoselective binding of the primary sulfonamide moiety was achieved in the face of an intrinsically more powerful pyrazole directing group present in the same molecule. Detailed DFT calculations and mechanistic experiments revealed a breakdown in the applied binding free energy model, illustrating the important interconnectivity of ligand design, substrate geometry, directing group cooperativity, and solvation in supporting DFT calculations. This work has important implications around attempts to predict intramolecular C-H activation directing group chemoselectivity using simplified monofunctional fragment molecules. More generally, these studies provide insights for catalyst design methods in late-stage C-H functionalisation.

Beyond Tripeptides Two-Step Active Machine Learning for Very Large Data sets.

Self-assembling peptide nanostructures have been shown to be of great importance in nature and have presented many promising applications, for example, in medicine as drug-delivery vehicles, biosensors, and antivirals. Being very promising candidates for the growing field of bottom-up manufacture of functional nanomaterials, previous work (Frederix, et al. 2011 and 2015) has screened all possible amino acid combinations for di- and tripeptides in search of such materials. However, the enormous complexity and variety of linear combinations of the 20 amino acids make exhaustive simulation of all combinations of tetrapeptides and above infeasible. Therefore, we have developed an active machine-learning method (also known as "iterative learning" and "evolutionary search method") which leverages a lower-resolution data set encompassing the whole search space and a just-in-time high-resolution data set which further analyzes those target peptides selected by the lower-resolution model. This model uses newly generated data upon each iteration to improve both lower- and higher-resolution models in the search for ideal candidates. Curation of the lower-resolution data set is explored as a method to control the selected candidates, based on criteria such as log P. A major aim of this method is to produce the best results in the least computationally demanding way. This model has been developed to be broadly applicable to other search spaces with minor changes to the algorithm, allowing its use in other areas of research.