Influence of solvent in controlling peptide−surface interactions

Protein binding to surfaces is an important phenomenon in biology and in modern technological applications. Extensive experimental and theoretical research has been focused in recent years on revealing the factors that govern binding affinity to surfaces. Theoretical studies mainly focus on examining the contribution of the individual amino acids or, alternatively, the binding potential energies of the full peptide, which are unable to capture entropic contributions and neglect the dynamic nature of the system. We present here a methodology that involves the combination of nonequilibrium dynamics simulations with strategic mutation of polar residues to reveal the different factors governing the binding free energy of a peptide to a surface. Using a gold-binding peptide as an example, we show that relative binding free energies are a consequence of the balance between strong interactions of the peptide with the surface and the ability for the bulk solvent to stabilize the peptide

Reductive cleavage of sulfones and sulfonamides by neutral organic super electron-donor (S.E.D.) reagent

The sulfonyl group finds extensive applications in organic and medicinal chemistry both in sulfonamides, popular as robust protecting groups for amines, and in sulfones. Frequently, sulfones are introduced into synthetic schemes to assist particular transformations; further progress along the synthetic route can later require the removal of a sulfone group, and this can be achieved by reductive desulfonylation or, in the special cases of α-halo- or ß-acyloxysulfones, by elimination to an alkene

Computational study on the boundary between the concerted and stepwise mechanism of bimolecular SNAr reactions

The text-book mechanism of bimolecular nucleophilic aromatic substitutions (SNAr) reactions is a stepwise process that proceeds via a so-called Meisenheimer intermediate. Only recently the alternative, concerted version of this mechanism has gained acceptance as more and more examples thereof have been reported. But so far only isolated examples of concerted SNAr reactions have been described and a coherent picture of when a SNAr reaction proceeds via a stepwise and when via a concerted mechanism has not yet been established. Here key factors are identified that influence the mechanistic choice of SNAr reactions. Moreover, the electron affinity is used as a simple descriptor to make a prediction on whether a given aryl fluoride substrate favors a concerted or stepwise mechanism

Predicting the reducing power of organic super electron donors

The utilization of computational methods to predict reactivity is an increasingly useful tool for chemists to save time and materials by screening compounds for desirable reactivity prior to testing in the laboratory. In the field of electron transfer reactions, screening can be performed through the application of Marcus Hush theory to calculate the activation free energy of any potential reaction. This work describes the most accurate and efficient approach for modelling the electron transfer process. In particular, the importance of using an electron transfer complex to model these reactions rather than considering donor and acceptor molecules as separate entities is highlighted. The use of the complex model is found to produce more accurate calculation of the electron transfer energy when the donor and acceptor spin densities are adequately localised

Beyond tripeptides - two-step active machine learning for very large datasets

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

C-C bond-forming reactions of ground-state aryl halides under reductive activation

Under basic conditions aryl halides can undergo SRN1 reactions, BHAS reactions and benzyne formations. Appropriate complex substrates afford an opportunity to study inherent selectivities. SRN1 reactions are usually favoured under photoactivated conditions, but this paper reports their success using ground-state and transition metal-free conditions. In benzene, the enolate salt 12, derived by deprotonation of diketopiperazine 11, behaves as an electron donor, and assists the initiation of the reactions, but in DMSO, it is not required. The outcomes are compared and contrasted with a recent photochemical study on similar substrates. A particular difference is the prevalence of hydride shuttle reactions under relatively mild thermal conditions

Supramolecular fibers in gels can be at thermodynamic equilibrium : a simple packing model reveals preferential fibril formation versus crystallization

Low molecular weight gelators are able to form nanostructures, typically fibers, which entangle to form gel-phase materials. These materials have wide-ranging applications in biomedicine and nanotechnology. While it is known that supramolecular gels often represent metastable structures due to the restricted molecular dynamics in the gel state, the thermodynamic nature of the nanofibrous structure is not well understood. Clearly, 3D extended structures will be able to form more interactions than 1D structures. However, self-assembling molecules are typically amphiphilic, thus giving rise to a combination of solvophobic and solvophilic moieties where a level of solvent exposure at the nanostructure surface is favorable. In this study, we introduce a simple packing model, based on prisms with faces of different nature (solvophobic and solvophilic) and variable interaction parameters, to represent amphiphile self-assembly. This model demonstrates that by tuning shape and "self" or "solvent" interaction parameters either the 1D fiber or 3D crystal may represent the thermodynamic minimum. The model depends on parameters that relate to features of experimentally known systems: The number of faces exposed to the solvent or buried in the fiber; the overall shape of the prism; and the free energy penalties associated with the interactions can be adjusted to match their chemical nature. The model is applied to describe the pH-dependent gelation/precipitation of well-known gelator Fmoc-FF. We conclude that, despite the fact that most experimentally produced gels probably represent metastable states, one-dimensional fibers can represent thermodynamic equilibrium. This conclusion has critical implications for the theoretical treatment of gels

Decomposition of nuclear magnetic resonance spin-spin coupling constants into active and passive orbital contributions

The theory for calculating spin-spin coupling constants (SS-CC) was studied using density functional theory (DFT). The mechanism of NMR spin-spin coupling in dependence of the electronic structure of a molecule and its bonding characteristics was also analyzed. A simple form of the new theory for analyzing SSCCs, called decomposition of J into orbital contributions using orbital currents and partial spin polarization (J-OC-PSP), was formulated in terms of one- and two-orbital contributions based on active orbitals. The Fermi contact (FC) coupling mechanism is predominantly based on exchange interactions

Tripeptide emulsifiers

Traditional, surfactant based emulsions have applications in the food, cosmetic, encapsulation and materials industries. The majority of the surfactants that are currently in use are based on lipids that are extracted from natural sources, however, other surfactants, based on polypeptides, copolymers and solid particles (Pickering emulsions)are also used. The process by which traditional amphiphilic surfactants stabilize biphasic mixtures by interfacial assembly and the consequent reduction of surface tension is well understood. Although these surfactants are well-suited to stabilize emulsions, they are not always biocompatible or biodegradable. In addition, they may not have sufficient stability at elevated temperatures or extremes of pH, which can limit their utility in a variety of applications. Therefore, it is desirable to identify a class of surfactants that can be tuned, or tailored, to match the application for which they are used

COGITO : a coarse-grained force field for the simulation of macroscopic properties of triacylglycerides

The use of molecular dynamics (MD) 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 (COGITO) 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 mono-unsaturated 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 done 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