Breaching of the skin barrier is essential for delivering active pharmaceutical ingredients (APIs) for pharmaceutical, dermatological and aesthetic applications. Chemical permeation enhancers (CPEs) are molecules that interact with the constituents of skin’s outermost and rate limiting layer stratum corneum (SC), and increase its permeability. Designing and testing of new CPEs is a resource intensive task, thus limiting the rate of discovery of new CPEs. In-silico screening of CPEs in a rigorous skin model could speed up the design of CPEs. In this study, we performed coarse grained (CG) molecule dynamics (MD) simulations of a multilayer skin lipid matrix in the presence of CPEs. The CPEs are chosen from different chemical functionalities including fatty acids, esters, and alcohols. A multi-layer in-silico skin model was developed. The CG parameters of permeation enhancers were also developed. Interactions of CPEs with SC lipids was studied in silico at three different CPE concentrations namely, 1% w/v, 3% w/v and 5% w/v. The partitioning and diffusion coefficients of CPEs in the SC lipids were found to be highly size- and structure-dependent and these dependencies are explained in terms of structural properties such as radial distribution function, area per lipid and order parameter. Finally, experimentally reported effects of CPEs on skin from the literature are compared with the simulation results. The trends obtained using simulations are in good agreement with the experimental measurements. The studies presented here validate the utility of in-silico models for designing, screening and testing of novel and effective CPEs.

Stratum corneum (SC), the outer layer of skin, serves as a barrier for pathogens and maintains the trans-epidermal water loss. The lipid matrix of SC is the major diffusion-rate-limiting pathway as molecules will have to pass through it. Ceramides play a key role in structuring and maintaining the barrier function of the skin. In this study, atomistic molecular dynamics (MD) simulations were used to systematically investigate the effects of the chain length of ceramide (CER) tails on the properties of the bilayer at a skin temperature of 310 K. The barrier properties were examined by means of permeation studies of water through the model membrane using steered MD simulations. Our studies revealed that shorter chains of one leaflet of the bilayer do not interdigitate with the chains of the other leaflet and lead to more free space in the middle of the bilayer, thereby leading to higher permeability. In CERs with dissimilar chain lengths, the lipids on one chain interdigitate with the other leaflet lipids, increasing the electron density in the middle of the bilayer. The bilayer thickness increases with increase in the CER chain length. The permeability of smaller-chain CERs was found to be an order of magnitude higher than that of the longer-chain CERs.

Over last 15 years high-entropy alloys (HEAs) and complex concentrated alloys (CCAs) have gained much appreciation for their numerous superior properties. In this paper we have shown a novel simulation methodology to realistically predict the nanometer level local structural features of complex Ta0.25Nb0.25Hf0.25Zr0.25 HEA. This involves prediction of the morphology of the short-range clustering (SRCs), their quantitative atomic composition at the nano level and the thermodynamic aspects. An alloy structure model containing 11664 atoms was created and this was subjected to structure evolution at 1800 °C. The structure evolution technique is based on a combined hybrid Monte Carlo and molecular dynamics (MC/MD) approach. The simulated results from this work are further validated against experiments and material characterizations reported in literature and done by high-resolution transmission electron micrograph (HRTEM) for the nano-level microstructure, atom probe tomography (APT) for the local chemical compositions and X-ray diffraction at synchrotron sources for the local lattice relaxation effects. This work qualitatively and quantitatively reproduces the materials characterization results reasonably well from the developed simulation methodologies. The structure evolution methods as described in this work are based on independent computer simulations and does not involve any manual intervention for input based on experiments on evolving SRCs. This work shows the potential of utilizing MC/MD based computational methods to reduce the number of costly experimental characterizations and accelerate the pace for materials development.

MD simulations reveal the chemical and physical heterogeneity at the liquid–liquid interface, nature of complexes formed by phosphoric acid ligands with lanthanides, and the sequence of events in the extraction of these ions.

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