Chrome Extension
WeChat Mini Program
Use on ChatGLM

Quantitative Analysis of the Membrane Affinity of Local Anesthetics Using a Model Cell Membrane

MEMBRANES(2021)

Cited 3|Views15
No score
Abstract
Local anesthesia is a drug that penetrates the nerve cell membrane and binds to the voltage gate sodium channel, inhibiting the membrane potential and neurotransmission. It is mainly used in clinical uses to address the pain of surgical procedures in the local area. Local anesthetics (LAs), however, can be incorporated into the membrane, reducing the thermal stability of the membrane as well as altering membrane properties such as fluidity, permeability, and lipid packing order. The effects of LAs on the membrane are not yet fully understood, despite a number of previous studies. In particular, it is necessary to analyze which is the more dominant factor, the membrane affinity or the structural perturbation of the membrane. To analyze the effects of LAs on the cell membrane and compare the results with those from model membranes, morphological analysis and 50% inhibitory concentration (IC50) measurement of CCD-1064sk (fibroblast, human skin) membranes were carried out for lidocaine (LDC) and tetracaine (TTC), the most popular LAs in clinical use. Furthermore, the membrane affinity of the LAs was quantitatively analyzed using a colorimetric polydiacetylene assay, where the color shift represents their distribution in the membrane. Further, to confirm the membrane affinity and structural effects of the membranes, we performed an electrophysiological study using a model protein (gramicidin A, gA) and measured the channel lifetime of the model protein on the free-standing lipid bilayer according to the concentration of each LA. Our results show that when LAs interact with cell membranes, membrane affinity is a more dominant factor than steric or conformational effects of the membrane.
More
Translated text
Key words
local anesthetics,membrane affinity,lipid bilayer membrane,calorimetric assay,cramicidin A,fibroblast cells
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined