JD-5006 and JD-5037: peripherally restricted (PR) cannabinoid-1 receptor blockers related to SLV-319 (Ibipinabant) as metabolic disorder therapeutics devoid of CNS liabilities.

Analogs of SLV-319 (Ibipinibant), a CB1 receptor inverse agonist, were synthesized with functionality intended to limit brain exposure while maintaining the receptor affinity and selectivity of the parent compound. Structure activity relationships of this series, and pharmacology of two lead compounds, 16 (JD-5006) and 23 (JD-5037) showing little brain presence as indicated by tissue distribution and receptor occupancy studies, are described. Effects with one of these compounds on plasma triglyceride levels, liver weight and enzymes, glucose tolerance and insulin sensitivity support the approach that blockade of peripheral CB(1) receptors is sufficient to produce many of the beneficial metabolic effects of globally active CB(1) blockers. Thus, PR CB(1) inverse agonists may indeed represent a safer alternative to highly brain-penetrant agents for the treatment of metabolic disorders, including diabetes, liver diseases, dyslipidemias, and obesity.

Biphenyl/diphenyl ether renin inhibitors: filling the S1 pocket of renin via the S3 pocket.

Structure-based design led to the discovery of a novel class of renin inhibitors in which an unprecedented phenyl ring filling the S1 site is attached to the phenyl ring filling the S3 pocket. Optimization for several parameters including potency in the presence of human plasma, selectivity against CYP3A4 inhibition and improved rat oral bioavailability led to the identification of 8d which demonstrated antihypertensive efficacy in a transgenic rat model of human hypertension.

Structure-based design and synthesis of 1,3-oxazinan-2-one inhibitors of 11ß-hydroxysteroid dehydrogenase type 1.

Structure based design led directly to 1,3-oxazinan-2-one 9a with an IC(50) of 42 nM against 11ß-HSD1 in vitro. Optimization of 9a for improved in vitro enzymatic and cellular potency afforded 25f with IC(50) values of 0.8 nM for the enzyme and 2.5 nM in adipocytes. In addition, 25f has 94% oral bioavailability in rat and >1000× selectivity over 11ß-HSD2. In mice, 25f was distributed to the target tissues, liver, and adipose, and in cynomolgus monkeys a 10 mg/kg oral dose reduced cortisol production by 85% following a cortisone challenge.

Discovery and optimization of adamantyl carbamate inhibitors of 11ß-HSD1.

Synthesis of 2-adamantyl carbamate derivatives of piperidines and pyrrolidines led to the discovery of 9a with an IC(50) of 15.2 nM against human 11ß-HSD1 in adipocytes. Optimization for increased adipocyte potency, metabolic stability and selectivity afforded 11k and 11l, both of which were >25% orally bioavailable in rat.

Spirocyclic ureas: orally bioavailable 11 beta-HSD1 inhibitors identified by computer-aided drug design.

Structure-guided drug design led to the identification of a class of spirocyclic ureas which potently inhibit human 11beta-HSD1 in vitro. Lead compound 10j was shown to be orally bioavailable in three species, distributed into adipose tissue in the mouse, and its (R) isomer 10j2 was efficacious in a primate pharmacodynamic model.

Optimization of orally bioavailable alkyl amine renin inhibitors.

Structure-guided drug design led to new alkylamine renin inhibitors with improved in vitro and in vivo potency. Lead compound 21a, has an IC(50) of 0.83nM for the inhibition of human renin in plasma (PRA). Oral administration of 21a at 10mg/kg resulted in >20h reduction of blood pressure in a double transgenic rat model of hypertension.

Design and optimization of renin inhibitors: Orally bioavailable alkyl amines.

Structure-based drug design led to the identification of a novel class of potent, low MW alkylamine renin inhibitors. Oral administration of lead compound 21l, with MW of 508 and IC(50) of 0.47nM, caused a sustained reduction in mean arterial blood pressure in a double transgenic rat model of hypertension.

Comparison of full-length versus ligand binding domain constructs in cell-free and cell-based peroxisome proliferator-activated receptor alpha assays.

Peroxisome proliferator-activated receptor alpha (PPARalpha) is the nuclear receptor responsible for regulating genes that control lipid homeostasis. Because of this role, PPARalpha has become a target of interest for the development of drugs to treat diseases such as dyslipidemia, obesity, and atherosclerosis. Assays currently employed to determine potency and efficacy of potential drug candidates typically utilize a truncated form of the native receptor, one which lacks the entire N-terminal region of the protein. The amino terminus, containing the regions that encode the ligand-independent activation function AF-1 and DNA binding domains, is highly structured and contributes significantly to the overall tertiary structure of the native protein. We report that differences in PPARalpha full-length and ligand binding domain constructs result in differences in binding affinity for coactivator peptides but have little effect on potency of agonists in both cell-free and cell-based nuclear receptor assays.

Generation and validation of rapid computational filters for cyp2d6 and cyp3a4.

CYP2D6 and CYP3A4 represent two particularly important members of the cytochrome p450 enzyme family due to their involvement in the metabolism of many commercially available drugs. Avoiding potent inhibitory interactions with both of these enzymes is highly desirable in early drug discovery, long before entering clinical trials. Computational prediction of this liability as early as possible is desired. Using a commercially available data set of over 1750 molecules to train computer models that were generated with commercially available software enabled predictions of inhibition for CYP2D6 and CYP3A4, which were compared with empirical data. The results suggest that using a recursive partitioning (tree) technique with augmented atom descriptors enables a statistically significant rank ordering of test-set molecules (Spearman's rho of 0.61 and 0.48 for CYP2D6 and CYP3A4, respectively), which represents an increased rate of identifying the best compounds when compared with the random rate. This approach represents a valuable computational filter in early drug discovery to identify compounds that may have p450 inhibition liabilities prior to molecule synthesis. Such computational filters offer a new approach in which lead optimization in silico can occur with virtual molecules simultaneously tested against multiple enzymes implicated in drug-drug interactions, with a resultant cost savings from a decreased level of molecule synthesis and in vitro screening.