Surfactants are molecules able to spontaneously self-assemble to form aggregates with well-defined properties, such as spherical micelles, planar bilayers, cylindrical micelles or vesicles. Micelles have notably several applications in many domains, such as drug delivery or membrane protein solubilization. In this context, the study of micelle formation in relation with the structural and physico-chemical properties of surfactants is of great interest to better control their use in the different application fields.In this work, we use the MD approach developed by Yoshii et al. and extend it to surfactants with different structures. We aim to systematically investigate different micellar properties as a function of the aggregates size by a molecular dynamics approach, to get an insight into the micellar organization and to collect some relevant descriptors about micelle formation. For this, we perform short MD simulations of preformed micelles of various sizes and analyze three parameters for each micelle size, namely the eccentricity of the micelles, the hydrophobic/hydrophilic surface ratio and the hydrophobic tails hydration. If these parameters are known descriptors of micelles, they were not yet studied in this way by MD.We show that eccentricity, used as “validator” parameter, exhibits minimal values when the aggregate size is close to the experimental aggregation number for surfactants that are known to form spherical micelles. This hence indicates that our methodology gives consistent results. The evolution of the two descriptors follows another scheme, with a sharp increase and decrease, respectively, followed by a leveling-off. The aggregate sizes at which this stabilization starts to occur are close to the respective aggregation number of each surfactant. In our approach, we validate the use of these descriptors to follow micelle formation by MD, from “simple” surfactants to more complex structures, like lipopeptides. Our calculations also suggest that some peculiar behavior, like that of TPC, can be highlighted by our approach.In the context of peptidic surfactants, our methodology could further help to improve computer simulations combined to molecular thermodynamic models to predict micellar properties of those more complex amphiphilic molecules.
Read full abstract