IV. Discovery of CXCR3 antagonists substituted with heterocycles as amide surrogates: improved PK, hERG and metabolic profiles.

The structure-human CXCR3 binding affinity relationship of a series of pyridyl/pyrazinyl-piperazinyl-piperidine derivatives were explored with a focus to improve PK, hERG and metabolic profiles. Several small heterocycles were identified as amide surrogates, which minimized many potential metabolite issues. During the course of SAR development, we have observed the additive effect of desirable functional groups to improve hERG and PK profiles which lead to the discovery of many clinically developable CXCR3 antagonists with excellent overall profile.

II. SAR studies of pyridyl-piperazinyl-piperidine derivatives as CXCR3 chemokine antagonists.

The structure-human CXCR3 binding affinity relationship of a series of pyridyl-piperazinyl-piperidine derivatives was explored. The optimization campaign highlighted the pronounced effect of 2'-piperazine substitution on CXCR3 receptor affinity. Analog 18j, harboring a 2'(S)-ethylpiperazine moiety, exhibited a human CXCR3 IC(50) of 0.2 nM.

III. Identification of novel CXCR3 chemokine receptor antagonists with a pyrazinyl-piperazinyl-piperidine scaffold.

The SAR of a novel pyrazinyl-piperazinyl-piperidine scaffold with CXCR3 receptor antagonist activity was explored. Optimization of the DMPK profile and reduction of hERG inhibition is described. Compound 16e with single-digit CXCR3 affinity, good rat PK and hERG profiles has been identified as a lead for further study.

Novel CXCR3 antagonists with a piperazinyl-piperidine core.

High-throughput screening of an encoded combinatorial aryl piperazine library led to the identification of a novel series of potent piperazinyl-piperidine based CXCR3 antagonists. Analogs of the initial hit were synthesized via solid and solution phase methods to probe the influence of structure on the CXCR3 binding of these molecules. Various functional groups were found to contribute to the overall potency and essential molecular features were identified.

Development of BACE1 inhibitors for Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disease and the most common cause of dementia. The production and accumulation of beta-amyloid peptides (Abeta) from the beta-amyloid precursor protein (APP) are believed to play a key role in the onset and progression of AD. BACE1 (beta-site APP cleaving enzyme 1) is the protease responsible for the N-terminal cleavage of APP leading to the production of Abeta peptides and the development of BACE1 inhibitors as potential therapeutic agents for AD has generated tremendous interests from both academia and the pharmaceutical industry. A wide variety of BACE1 inhibitors have been reported, several of which have demonstrated highly promising efficacy in animal models of AD. This review focuses on recent disclosures of BACE1 inhibitors in the patent and scientific literature, covering the period from approximately May 2004 to November 2005.

Deriving knowledge through data mining high-throughput screening data.

Deriving general knowledge from high-throughput screening data is made difficult by the significant amount of noise, arising primarily from false positives, in the data. The paradigm established for screening an encoded combinatorial library on polymeric support, an ECLiPS library, has a significant amount of built-in redundancy. Because of this redundancy, the resulting data can be interpreted through a rigorous statistical analysis procedure, thereby significantly reducing the number of false positives. Here, we develop the statistical models used to analyze data from high-throughput screens of ECLiPS libraries to derive unbiased true hit rates. These hit rates can also be calculated on subsets of the collection such as those compounds containing a carboxylic acid or those with molecular weight below 350 Da. The relative value of the hit rate on the subset of the collection can then be compared to the overall hit rate to determine the effect of the substructure or physical property on the likelihood of a molecule having biological activity. Here, we show the effects that various functional groups and the standard physical properties, molecular weight, hydrogen bond donors, hydrogen bond acceptors, log P, and rotatable bonds, have on the likelihood of a compound being biologically active. To our knowledge this is the first published account of the use of high-throughput screening data to elucidate the effects of physical properties and substructures on the likelihood of compounds showing biological activity over a broad range of pharmaceutically relevant targets.

Privileged structure-based combinatorial libraries targeting G protein-coupled receptors.

Combinatorial chemistry has become a key component of today's drug discovery process. Privileged structures, with their inherent affinity for diverse biological receptors, represent an ideal source of core scaffolds and capping fragments for the design and synthesis of combinatorial libraries targeted at various receptors. GPCRs-distributed widely in the body and involved in many physiological and pathophysiological processes-have been historically among the most popular targets for drug discovery. Numerous privileged structure-based combinatorial libraries have been designed and synthesized, and these libraries have proved to be an extremely powerful tool to aid the rapid discovery and optimization of potent and selective ligands for a wide variety of GPCR targets. This review focuses on recent developments in applying privileged structure-based combinatorial libraries for the discovery and optimization of GPCR ligands and critically evaluates the advantages of the various types of GPCR-targeted libraries.

Understanding hERG inhibition with QSAR models based on a one-dimensional molecular representation.

Blockage of the potassium channel encoded by the human ether-a-go-go related gene (hERG) is well understood to be the root cause of the cardio-toxicity of numerous approved and investigational drugs. As such, a cascade of in vitro and in vivo assays have been developed to filter compounds with hERG inhibitory activity. Quantitative structure activity relationship (QSAR) models are used at the very earliest part of this cascade to eliminate compounds that are likely to have this undesirable activity prior to synthesis. Here a new QSAR technique based on the one-dimensional representation is described in the context of the development of a model to predict hERG inhibition. The model is shown to perform close to the limits of the quality of the data used for model building. In order to make optimal use of the available data, a general robust mathematical scheme was developed and is described to simultaneously incorporate quantitative data, such as IC50 = 50 nM, and qualitative data, such as inactive or IC50 > 30 microM into QSAR models without discarding any experimental information.

Discovery of tetralin ureas as potent melanin concentrating hormone 1 receptor antagonists.

Melanin concentrating hormone (MCH) plays an important role in the regulation of food intake and energy balance in mammals. MCH-1 receptor (MCH1R) deficient mice are lean and resistant to diet-induced obesity. As such, MCH1R antagonists are believed to have potential as possible treatments for obesity. The discovery of a novel class of tetralin ureas as potent MCH1R antagonists is described herein.

Design, synthesis, and evaluation of tetrahydroquinoline and pyrrolidine sulfonamide carbamates as gamma-secretase inhibitors.

Gamma-secretase is a key enzyme involved in the production of beta-amyloid peptides which are believed to play a critical role in the onset and progression of Alzheimer's disease (AD). As such, inhibition of gamma-secretase has been an attractive approach to AD therapy. In this paper, the design, synthesis, and evaluation of tetrahydroquinoline and pyrrolidine sulfonamide carbamates as gamma-secretase inhibitors are described.

Discovery and SAR of 4-amino-2-biarylbutylurea MCH 1 receptor antagonists through solid-phase parallel synthesis.

-4-Amino-2-arylbutylbenzamides such as 1 were identified as micromolar MCH 1 receptor (MCH1R) antagonists via screening using a scintillation proximity assay based on [125I]-MCH binding to recombinant, human MCH1R. Subsequent lead optimization efforts using solid-phase parallel synthesis resulted in the defined structure-activity relationships and the identification of 4-amino-2-biarylbutylureas, such as 11g, as potent single digit nanomolar MCH1R antagonists.

Discovery and SAR of biaryl piperidine MCH1 receptor antagonists through solid-phase encoded combinatorial synthesis.

An encoded combinatorial library based on aryl and biaryl piperidine scaffolds was designed and synthesized. Screening of this library resulted in the discovery of high-nanomolar biaryl piperidine-based MCH1 receptor antagonists. Follow-up optimization using a parallel synthesis provided potent, single digit nanomolar antagonists.