A pharmacological characterization of GABA, THIP and DS2 at binary α4ß3 and ß3δ receptors: GABA activates ß3δ receptors via the ß3(+)δ(-) interface.

There is growing evidence that GABA (γ-aminobutyric acid) can activate GABAA receptors (GABAARs) in the absence of an α subunit. In this study, we compared the pharmacology of homomeric and binary α4, ß3 or δ subunits with ternary α4ß3δ to identify subunit interfaces that contribute to the pharmacology of GABA, THIP, and DS2, and the antagonists, Zn(2+), gabazine and bicuculline. ß3δ receptors form functional GABA-gated channels when expressed in Xenopus oocytes with a pharmacology that differs to homomeric ß3, binary α4ß3 and ternary α4ß3δ receptors. GABA had similar potency at α4ß3 and ß3δ receptors (25µM and 26µM, respectively) but differed at α4ß3δ receptors where GABA exhibited a biphasic concentration-response (EC50 (1)=12.6nM; EC50 (2)=6.3µM). THIP activated ß3δ receptors (EC50=456µM) but was a more potent activator of α4ß3 (EC50=27µM) and α4ß3δ receptors (EC50 (1)=27.5nM; EC50 (2)=29.5µΜ), indicating that the α4 subunit significantly contribute to its potency. The δ-preferring modulator, DS2 had marginal or no effect at ß3δ and α4ß3 receptors, indicating a role for both the α4 and δ subunits for its potency. Gabazine inhibited GABA-elicited currents at ß3δ receptors whereas bicuculline activated these receptors. Mutational analysis verified that GABA binds to the ß3(+)δ(-) interface formed by the ß3 and δ subunits. In conclusion, evaluating agents against binary GABAARs such as ß3δ and α4ß3 receptors enables identification of interfaces that may contribute to the pharmacology of the more complex ternary α4ß3δ receptors.

A hydrophobic area of the GABA ρ1 receptor containing phenylalanine 124 influences both receptor activation and deactivation.

Experimental evidence suggests that GABA ρ1 receptors are potential therapeutic targets for the treatment of a range of neurological conditions, including anxiety and sleep disorders. Homology modelling of the GABA ρ1 extracellular N-terminal domain has revealed a novel hydrophobic area that extends beyond, but not including the GABA-binding site. Phenylalanine 124 (F124) is predicted to be involved in maintaining the structural integrity of the orthosteric-binding site. We have assessed the activity of a series of GABA ρ1 receptors that incorporate a mutation at F124. Wild-type and mutant human GABA ρ1 subunits were expressed in Xenopus laevis oocytes and AD293 cells, and the pharmacology and kinetic properties of the receptors were measured using electrophysiological analysis. Mutation of F124 had minimal effect on receptor pharmacology. However, the rate of deactivation was significantly increased compared to wild type. This study provides further information about the role of residues within a novel hydrophobic area of the GABA ρ1 receptor. This knowledge can help future studies into the design of potent and subtype-selective ligands with therapeutic value.

Demographic, laboratory, and operational variables that influence short- and long-term plateletpheresis yields.

We studied the demographic, laboratory, and operational parameters that might influence individual, as well as average, plateletpheresis yields. Multivariate linear regression analyses showed that 25.4% and 11.6% of variability, among males and females, respectively, in individual yields was explained by the platelet count prior to that donation and 55% of the variation in mean platelet yields (PYs) was explained by the pre-first donation platelet count, the first donation PY and the body mass index (BMI). Logistic regression analysis showed that donors with first donation PYs higher, compared to those with lower yields, than the median of all mean PYs were more likely to be relatively high platelet yielders over the long term. A statistically significant, although clinically insignificant, decline in predonation platelet counts is seen in all donors regardless of the total number of donations or interdonation interval. Donors with high pre-first donation platelet counts, first donation yields, and BMI are likely to be consistent good platelet yielders.