5-N,N-Disubstituted 5-aminopyrazole-3-carboxylic acids are highly potent agonists of GPR109b.

A series of 5-N,N-disubstituted-5-aminopyrazole-3-carboxylic acids were prepared and found to act as highly potent and selective agonists of the G-Protein Coupled Receptor (GPCR) GPR109b, a low affinity receptor for niacin and some aromatic d-amino acids. Little activity was observed at the highly homologous higher affinity niacin receptor, GPR109a.

3-Nitro-4-amino benzoic acids and 6-amino nicotinic acids are highly selective agonists of GPR109b.

A series of 3-nitro-4-substituted-aminobenzoic acids were prepared and found to act as potent and highly selective agonists of the orphan human GPCR GPR109b, a low affinity receptor for niacin. No activity was observed at the closely homologous high affinity niacin receptor, GPR109a. A second series, comprising 6-amino-substituted nicotinic acids was, also prepared and several analogues showed comparable activity to the nitroaryl series.

1-Alkyl-benzotriazole-5-carboxylic acids are highly selective agonists of the human orphan G-protein-coupled receptor GPR109b.

1-Substituted benzotriazole carboxylic acids have been identified as the first reported examples of selective small-molecule agonists of the human orphan G-protein-coupled receptor GPR109b (HM74), a low-affinity receptor for the HDL-raising drug niacin. No activity was observed at the highly homologous high-affinity niacin receptor GPR109a (HM74A). The high degree of selectivity was attributed to a difference in the amino acid sequence adjacent to a key arginine-ligand interaction allowing somewhat larger ligands to be tolerated by GPR109b.

Discovery of SCH446211 (SCH6): a new ketoamide inhibitor of the HCV NS3 serine protease and HCV subgenomic RNA replication.

Introduction of various modified prolines at P(2) and optimization of the P(1) side chain led to the discovery of SCH6 (24, Table 2), a potent ketoamide inhibitor of the HCV NS3 serine protease. In addition to excellent enzyme potency (K(i)*= 3.8 nM), 24 was also found to be a potent inhibitor of HCV subgenomic RNA replication with IC(50) and IC(90) of 40 and 100 nM, respectively. Recently, antiviral activity of 24 was demonstrated with inhibition of the full-length genotype 2a HCV genome. In addition, 24 was found to restore the responsiveness of the interferon regulatory factor 3 (IRF-3) in cells containing HCV RNA replicons.

Clinically validated peptides as templates for de novo peptidomimetic drug design at G-protein-coupled receptors.

Recent advances in the development of potent and selective peptide and non-peptide ligands for peptidergic receptors are anticipated to help further unravel the roles of class I and II G-protein-coupled receptors in the pathogenesis of human diseases and to accelerate the clinical utility of small molecule peptidomimetics. Peptidomimetic drug discovery directed towards somatostatin agonists, urotensin II antagonists, gonadotropin-releasing hormone antagonists, neurotensin and complement C5a modulators, melanocortin-4 agonists and vasopressin V(2) agonists has achieved success through integration of conformational-based drug design, site-directed mutagenesis, screening, combinatorial chemistry and classical medicinal chemistry. Acceptance that discreet ensembles of secondary structural motifs underpin the interactions of peptides with their cognate receptors has enabled the development of molecules which mimic or stabilize such pharmacophores.

Data analysis of high-throughput screening results: application of multidomain clustering to the NCI anti-HIV data set.

The routine use of high-throughput screening (HTS) systems in the drug discovery process has resulted in an increasing need for fast, reliable analysis of massive amounts of data. A new automated multidomain clustering method that thoroughly analyzes screening data sets is used to examine both the active and the inactive compounds in a well-known, publicly available data set based on primary screening. Large and small compound sets that defined both chemical families and potential pharmacophore points were discovered. The detection of structure-activity relationships (SAR), aided by the unique classification method, is described in this article.

3-(1H-tetrazol-5-yl)-1,4,5,6-tetrahydro-cyclopentapyrazole (MK-0354): a partial agonist of the nicotinic acid receptor, G-protein coupled receptor 109a, with antilipolytic but no vasodilatory activity in mice.

The discovery and profiling of 3-(1H-tetrazol-5-yl)-1,4,5,6-tetrahydro-cyclopentapyrazole (5a, MK-0354), a partial agonist of GPR109a, is described. Compound 5a retained the plasma free fatty acid lowering effects in mice associated with GPR109a agonism, but did not induce vasodilation at the maximum feasible dose. Moreover, preadministration of 5a blocked the flushing effect induced by nicotinic acid but not that induced by PGD2. This profile made 5a a suitable candidate for further study for the treatment of dyslipidemia.

Fluorinated pyrazole acids are agonists of the high affinity niacin receptor GPR109a.

A series of 5-alkyl pyrazole-3-carboxylic acids were prepared and found to act as potent and selective agonists of the human GPCR, GPR109a, the high affinity nicotinic acid receptor. No activity was observed at the highly homologous low affinity niacin receptor, GPR109b. A further series of 4-fluoro-5-alkyl pyrazole-3-carboxylic acids were shown to display similar potency. One example from the series was shown to have improved properties in vivo compared to niacin.

Agonist lead identification for the high affinity niacin receptor GPR109a.

A strategy for lead identification of new agonists of GPR109a, starting from known compounds shown to activate the receptor, is described. Early compound triage led to the formulation of a binding hypothesis and eventually to our focus on a series of pyrazole acid derivatives. Further elaboration of these compounds provided a series of 5,5-fused pyrazoles to be used as lead compounds for further optimization.

Rule extraction from a mutagenicity data set using adaptively grown phylogenetic-like trees.

A public bacterial mutagenicity database was classified into 2-D structural families using a set of specific algorithms and clustering techniques that find overlapping classes of compounds based upon chemical substructures. Structure-activity relationships were learned from the biological activity of the compounds within each class and used to identify rules that define substructures potentially responsible for mutagenic activity. In addition, this method of analysis was used to compare the pharmacologically relevant substructure of test compounds with their potential toxic substructures making this a potentially valuable in silico profiling tool for lead selection and optimization.