Influence of some anti-inflammatory drugs in membrane fluidity studied by fluorescence anisotropy measurements
文献情報
Marlene Lúcio, Helena Ferreira, José L. F. C. Lima, Carla Matos, Baltazar de Castro, Salette Reis
Non-steroidal anti-inflammatory drugs (NSAIDs) have an important role as anti-rheumatic drugs and their therapeutic effects may be partly due to their ability to induce modifications on physical characteristics of the membrane lipid bilayer. In this study we used fluorescence anisotropy measurements in order to assess the influence of different NSAIDS (nimesulide, tolmetin, acemetacin and indomethacin) in the membrane fluidity. Liposomes were prepared by the thin film hydration method and were used as models of the biological membranes. Membrane fluidity was estimated in large unilamellar vesicles (LUVs) by fluorescence measurements using a set of n-(9-anthroyloxy) fatty acid probes (n = 2, 6, 9 and 12). As the fluorophores of these molecules are located at a graded series of levels from the surface to the centre of the lipid bilayer, using these probes, it was possible to monitor the fluidity gradient through a bilayer leaflet by measurements of fluorescence anisotropy. The location of tolmetin on LUVs was evaluated by fluorescence quenching using the same spectroscopic probes. All the NSAIDs increased membrane fluidity (decreased the fluorescence anisotropy) in a concentration dependent manner with an effectiveness ordered as nimesulide > indomethacin ≥ acemetacin > tolmetin. Although all probes were perturbed, 2, 6 and 9-AS, which are part of the plateau region, have shown to be less susceptible to perturbation than the 12-AS probe closely located to the centre of the bilayer. Moreover, each n-AS probe was differently affected, according to the perturbers preferential location. Besides the investigation of membrane structural perturbations induced by NSAIDs, the aim of the present study was to provide a data analysis of steady-state anisotropy measurements taking into account that the probe itself strongly influences the data, as this problem is most of the times overlooked.
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