Novel delta opioid receptor agonists exhibit differential stimulation of signaling pathways.

A novel family of 1,3,5-trisubstituted 1,2,4-triazoles was discovered as potent and selective ligands for the delta opioid receptor by rational design. Compound 5b exhibited low-nanomolar in vitro binding affinity (IC(50)=5.8 nM), excellent selectivity for the delta opioid receptor over the alternative mu and kappa opioid receptors, full agonist efficacy in receptor down-regulation and MAP kinase activation assays, and low-efficacy partial agonist activity in stimulation of GTPgammaS binding.

Structural model of the Plasmodium CDK, Pfmrk, a novel target for malaria therapeutics.

Malaria, with 300-500 million clinical cases resulting in 1-3 million fatalities a year, is one of the most deadly tropical diseases. As current antimalarial therapeutics become increasingly ineffective due to parasitic resistance, there exists an urgent need to develop and pursue new therapeutic strategies. Recent genome sequencing and molecular cloning projects have identified several enzymes from Plasmodium (P.

3D-QSAR comparative molecular field analysis on delta opioid receptor agonist SNC80 and its analogs.

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) for a series of delta opioid receptor agonists: SNC80 analogs. Quantum chemical calculations on SNC80 show that protonation is preferred at the basic N4 atom over the alternative N1 atom, accordingly N4 protonation may contribute significantly to ligand-receptor interactions under physiologically relevant conditions. Statistically significant and predictive CoMFA models were achieved by pooling biological data from independent published sources, including compounds with both alphaR and alphaS benzylic configurations.

3D-QSAR comparative molecular field analysis on opioid receptor antagonists: pooling data from different studies.

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) on a series of opioid receptor antagonists. To obtain statistically significant and robust CoMFA models, a sizable data set of naltrindole and naltrexone analogues was assembled by pooling biological and structural data from independent studies. A process of "leave one data set out", similar to the traditional "leave one out" cross-validation procedure employed in partial least squares (PLS) analysis, was utilized to study the feasibility of pooling data in the present case.