The hydro lipid film is an emulsion of sweat and sebum that covers the surface of the human skin and affects the tribological properties of the human skin. This study investigates the effects of the composition of the sebum on the average coefficient of friction. A range of simplified sebums was developed and the friction behaviour was investigated. Five realistic sebums showed a strong variation in friction results, indicating that interpersonal differences in frictional behaviour might have their origin in differences in sebum composition. A more detailed investigation employing controlled variations of individual ingredients showed that friction is highly sensitive to the amount of squalene in the sebum. The amount of fatty acids in the sebum also showed some effects, whilst the amount of cholesterol does not appear to be relevant for the friction behaviour. The main new outcome from this study is that the composition of sebum has a significant effect on the friction response of skin in ways that are currently not yet fully understood.
Enzyme engineering aims to improve or install a new function in biocatalysts for applications ranging from chemical synthesis to biomedicine. For decades, computational techniques have been developed to predict the effect of protein changes and design new enzymes. However, these techniques may have been optimized to deal with proteins composed of the standard amino acid alphabet, while the function of many enzymes relies on non‐proteogenic parts like cofactors, nucleic acids, and post‐translational modifications. Enzyme systems containing such molecules might be handled or modeled improperly by computational tools, and thus be unsuitable, or require additional tweaking, parameterization, or preparation. In this review, we give an overview of common and recent tools and workflows available to computational enzyme engineers. We highlight the various pitfalls that come with including non‐proteogenic compounds in computations and outline potential ways to address common issues. Finally, we showcase successful examples from the literature that computationally engineered such enzymes.
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