Biomedical subjects

G O Pesce

Publications and source records attributed to G O Pesce.

3 recordsLinked to original sources

PubMed1990

Computer modeling of subtypes of kappa opioid receptors in adrenal medulla.

The existence of multiple subtypes of kappa opioid receptors in brain and adrenal medulla, has been controversial. We have characterized opioid receptors in frozen membranes from bovine adrenal medulla by use of objective mathematical modeling. [3H]Etorphine, [3H]ethylketocyclazocine (EKC) and [3H][D-Ala2,D-Leu5]enkephalin (DADL) were utilized as labeled ligands. Self- and cross-displacement curves were constructed using the three corresponding unlabeled ligands in the presence or absence of increasing concentrations of DADL. Results indicated: (1) each of the three ligands studied individually showed the presence of heterogeneity of binding sites; (2) sites labeled by etorphine were heterogeneous: 84% of etorphine binding was displaceable by 10(-4) M DADL, while the remaining 16% was DADL non-suppressible; (3) 75% of the binding of EKC was displaceable by DADL while 25% was non-suppressible; (4) mathematical modeling showed the presence of three subtypes of kappa binding sites (a) kappa 1, showing slight selectivity for EKC relative to etorphine; (b) kappa 2, with Kd approximately equal to 1 nM for etorphine, and sufficiently high affinity for DADL (Kd approximately equal to 150 nM) so that it is suppressible by 100 microM DADL; and (c) K3, with no measurable affinity for DADL and a 27-fold selectivity for etorphine relative to EKC. The three subtypes of kappa sites were present at concentrations of 7.4, 75, and 55 fmol/mg protein, respectively. The relative affinities of a series of kappa agonists for the etorphine-binding sites were characterized. The present studies confirm the existence of three subtypes of kappa opioid receptors in bovine adrenal medulla, and indicate the utility of mathematical modeling for characterization of complex receptor systems.

Adrenal Medulla↗

PubMed1986

Opioid receptors of bovine posterior pituitary neurosecretosomes are exclusively kappa.

Intact neurosecretosomes (NSS) from bovine posterior pituitary were prepared and characterized. Ligand binding studies were performed, using 3H-[D-Ala2-D-Leu5]enkephalin (DADL), 3H-etorphine and 3H-ethylketocyclazocine (EKC). The absence of specific binding of 3H-DADL and the inability of DADL to displace 3H-etorphine, implies the absence of mu, delta, or DADL-suppressible benzomorphan ("kappa-2") sites. Self- and cross displacement studies for etorphine and EKC suggested receptor heterogeneity. EKC fails to displace - 20% of specific binding of etorphine. Mathematical modelling indicates the presence of three classes of sites. The present findings imply that bovine posterior pituitary opioid receptors are exclusively of the kappa type.

Analgesics, Opioid↗

PubMed1986

Computer analysis of radioligand data: advantages, problems, and pitfalls.

Mathematical modeling combined with nonlinear least-squares curve fitting provides a systematic, objective, reproducible, and consistent method to aid the interpretation of ligand-binding data. It forces the experimentalist to formulate hypotheses in an unambiguous manner and to consider alternative, closely related models as plausible counter-hypotheses. Modeling provides estimates of the "goodness-of-fit" of the theory to the data and estimates of the minimal uncertainty of the parameters. With the availability of many programs for micro- and mini-computers, as well as mainframe computers, these methods are now becoming widely used. Accordingly, we must emphasize a number of potential problems and limitations, based on our experience. Interpretation of results of modeling study should be made, in light of the following points: no amount of computer analysis will compensate for "bad" or insufficient data, or for poor experimental design; the interpretation of the computer analysis is subject to the caveat that all underlying assumptions must be satisfied; one must examine the data graphically in several coordinate systems (e.g., "raw data," as well as standardized residuals); one must continuously search for possible systematic biases or artifacts; one must closely examine the reproducibility of results between multiple experiments; and one must recognize that all of the "test tubes" in an experiment are not necessarily "independent observations" in a statistical sense. In view of these potential problems and limitations, one should always seek to corroborate results and interpretations of "modeling" studies of ligand binding by independent biochemical, biophysical, or structural evidence. In this context, ligand-binding studies, appropriately analyzed, can play a useful and constructive role.

Computer Simulation↗