Discovery of Clinical Candidate 2-((2S,6S)-2-Phenyl-6-hydroxyadamantan-2-yl)-1-(3'-hydroxyazetidin-1-yl)ethanone [BMS-816336], an Orally Active Novel Selective 11ß-Hydroxysteroid Dehydrogenase Type 1 Inhibitor.

BMS-816336 (6n-2), a hydroxy-substituted adamantyl acetamide, has been identified as a novel, potent inhibitor against human 11ß-hydroxysteroid dehydrogenase type 1 (11ß-HSD1) enzyme (IC50 3.0 nM) with >10000-fold selectivity over human 11ß-hydroxysteroid dehydrogenase type 2 (11ß-HSD2). 6n-2 exhibits a robust acute pharmacodynamic effect in cynomolgus monkeys (ED50 0.12 mg/kg) and in DIO mice. It is orally bioavailable (%F ranges from 20 to 72% in preclinical species) and has a predicted pharmacokinetic profile of a high peak to trough ratio and short half-life in humans. This ADME profile met our selection criteria for once daily administration, targeting robust inhibition of 11ß-HSD1 enzyme for the first 12 h period after dosing followed by an "inhibition holiday" so that the potential for hypothalamic-pituitary-adrenal (HPA) axis activation might be mitigated. 6n-2 was found to be well-tolerated in phase 1 clinical studies and represents a potential new treatment for type 2 diabetes, metabolic syndrome, and other human diseases modulated by glucocorticoid control.

Core-shell potential-derived point charges.

The present work details the development of a core-shell model for the purposes of obtaining potential-derived point charges from the ab initio molecular electrostatic potential. In contrast to atomic point charge models, the core-shell model decomposes all atoms into a core with static charge located at a fixed atomic position and a shell with variable charge and position. The optimization of shell charges and positions is discussed. The core-shell model was found to significantly improve description of the ab initio electrostatic potential when compared to potential-derived net atomic point charge models as well as distributed multipoles with contributions up to atomic quadrupole moments. The core-shell model was found to produce similar results as the Weller-Williams lone-pair model and differences in the implementation of the models are discussed.

Cannabinoid CB(1) receptor ligand binding and function examined through mutagenesis studies of F200 and S383.

The cannabinoid CB(1) G protein-coupled receptor has been shown to be a regulator of food consumption and has been studied extensively as a drug target for the treatment of obesity. To advance understanding of the receptor's three-dimensional structure, we performed mutagenesis studies at human cannabinoid CB(1) receptor residues F200 and S383 and measured changes in activity and binding affinity of compounds from two recently discovered active chemotypes, arylsulfonamide agonists and tetrahydroquinoline-based inverse agonists, as well as literature compounds. Our results add support to previous findings that both agonists and inverse agonists show varied patterns of binding at the two mutated residue sites, suggesting multiple subsites for binding to the cannabinoid CB(1) receptor for both functional types of ligands. We additionally find that an F200L mutation in the receptor largely restores binding affinity to ligands and significantly decreases constitutive activity when compared to F200A, resulting in a receptor phenotype that is closer to the wild-type receptor. The results downplay the importance of aromatic stacking interactions at F200 and suggest that a bulky hydrophobic contact is largely sufficient to provide significant receptor function and binding affinity to cannabinoid CB(1) receptor ligands.

Application of error-ranked singular value decomposition for the determination of potential-derived atomic-centered point charges.

The present work provides a detailed investigation on the use of singular value decomposition (SVD) to solve the linear least-squares problem (LLS) for the purposes of obtaining potential-derived atom-centered point charges (PD charges) from the ab initio molecular electrostatic potential (V(QM)). Given the SVD of any PD charge calculation LLS problem, it was concluded that (1) all singular vectors are not necessary to obtain the optimal set of PD charges and (2) the most effective set of singular vectors do not necessarily correspond to those with the largest singular values. It is shown that the efficient use of singular vectors can provide statistically well-defined PD charges when compared with conventional PD charge calculation methods without sacrificing the agreement with V(QM). As can be expected, the methodology outlined here is independent of the algorithm for sampling V(QM) as well as the basis set used to calculate V(QM). An algorithm is provided to select the best set of singular vectors used for optimal PD charge calculations. To minimize the subjective comparisons of different PD charge sets, we also provide an objective criterion for determining if two sets of PD charges are significantly different from one another.