Perspective on the Relationship between GABAA Receptor Activity and the Apparent Potency of an Inhibitor

Allison L. Germann, Spencer R. Pierce, Alex S. Evers, Joe Henry Steinbach, Gustav Akk

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Background: In electrophysiological experiments, inhibition of a receptor-channel, such as the GABAA receptor, is measured by co-applying an agonist producing a predefined control response with an inhibitor to calculate the fraction of the control response remaining in the presence of the inhibitor. The properties of the inhibitor are determined by fitting the inhibition concentra-tion-response relationship to the Hill equation to estimate the midpoint (IC50) of the inhibition curve. Objective: We sought to estimate sensitivity of the fitted IC50 to the level of activity of the control response. Methods: The inhibition concentration-response relationships were calculated for models with distinct mechanisms of inhibition. In Model I, the inhibitor acts allosterically to stabilize the resting state of the receptor. In Model II, the inhibitor competes with the agonist for a shared binding site. In Model III, the inhibitor stabilizes the desensitized state. Results: The simulations indicate that the fitted IC50 of the inhibition curve is sensitive to the degree of activity of the control response. In Models I and II, the IC50 of inhibition was increased as the probability of being in the active state (PA) of the control response increased. In Model III, the IC50 of inhibition was reduced at higher PA. Conclusion: We infer that the apparent potency of an inhibitor depends on the PA of the control re-sponse. While the calculations were carried out using the activation and inhibition properties that are representative of the GABAA receptor, the principles and conclusions apply to a wide variety of re-ceptor-channels.

Original languageEnglish
Pages (from-to)90-93
Number of pages4
JournalCurrent Neuropharmacology
Volume20
Issue number1
DOIs
StatePublished - Jan 2022

Keywords

  • Activation
  • GABA receptor
  • IC
  • Inhibition
  • Modeling

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