Partitioning of caffeine in lipid bilayers reduces membrane fluidity and increases membrane thickness
Literature Information
Adree Khondker, Alexander Dhaliwal, Richard J. Alsop, Jennifer Tang, An-Chang Shi, Maikel C. Rheinstädter
Caffeine is a small amphiphilic molecule, which is widely consumed as a stimulant to prevent fatigue, but is also used as a common drug adjuvant in modern medicine. Here, we show that caffeine interacts with unsaturated lipid membranes made of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC). By combining X-ray diffraction and molecular dynamics simulations, we present evidence that caffeine partitions in lipid membranes and locates at the head group–tail group interface of the bilayers. By attracting water molecules from neighboring lipid molecules, it leads to the formation of “water pockets”, i.e., a local increase of water density at this interface. Through this mechanism, caffeine leads to an overall decrease of the gauche defect density in the membranes and an increase of membrane thickness, indicating a loss of membrane fluidity. These non-specific membrane interactions may increase the efficacy of analgesic drugs through changes in the bioavailability and rate of metabolism of these drugs.
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.













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