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• W2909033498 abstract "Medium chain fatty acids (MCFA) are digestion products of lipid-rich food and lipid-based formulations, and they are used as transient permeability enhancers in formulation of poorly permeable compounds. These molecules may promote drug absorption by several different processes, including solubilization, increased membrane fluidity, and increased paracellular transport through opening of the tight junctions. Therefore, understanding the aggregation behavior of MCFAs is important. A number of studies have measured the critical micelle concentration (CMC) of MCFAs experimentally. However, CMC is highly dependent on system conditions like pH, temperature, and the ionic strength of the buffer used in different experimental techniques. In this study, we investigated the aggregation behavior of four different MCFAs using the coarse-grained molecular dynamics (CG-MD) simulations with the purpose to explore if CG-MD can be used to study MCFA interactions occurring in water. The ratio of deprotonated and non-charged MCFA molecules were manipulated to assess aggregation behavior under different pH conditions and within the box sizes of 22 × 22 × 44 nm3 and 44 nm3 for 1 μs. CMCs were calculated by performing CG-MD simulations with an increasing number of MCFAs. The resulting aggregate size distribution and number of free MCFA molecules were used to determine the CMC. The CMCs from simulations for C8, C10, and C12 were 1.8–3.5-fold lower than the respective CMCs determined experimentally by the Wilhelmy method. However, the variation of MCFA aggregate sizes and morphologies at different pH conditions is consistent with previous experimental observation. Overall, this study suggests that CG-MD is suitable for studying colloidal systems including various MCFAs." @default.
• W2909033498 created "2019-01-25" @default.
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• W2909033498 date "2019-01-09" @default.
• W2909033498 modified "2023-10-06" @default.
• W2909033498 title "Aggregation Behavior of Medium Chain Fatty Acids Studied by Coarse-Grained Molecular Dynamics Simulation" @default.
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• W2909033498 doi "https://doi.org/10.1208/s12249-018-1289-4" @default.
• W2909033498 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6373435" @default.
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• W2909033498 hasPublicationYear "2019" @default.
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