Current Topics in Medicinal Chemistry - Volume 12, Issue 11, 2012

Phosphodiesterases (PDEs) are a family of enzymes that metabolically inactivate the second messengers 3’,5’- cyclic adenosine monophosphate (cAMP) and/or 3’,5’-cyclic guanosine monophosphate (cGMP). These two messengers regulate the extracellular signal from the plasma membrane G protein-coupled receptors (GPCRs) to the intracellular effector proteins, hence modulating a wide variety of biological processes both in the central nervous system (CNS) and peripheral tissues. Although there are many radiotracers available for positron emission tomography (PET) studies of different receptors, there are just a few tracers available for imaging studies of second messenger systems. The first reported PDE PET ligands were the 11C-labeled versions of the PDE4 inhibitors rolipram and Ro 20-1724, and, to date, PET imaging studies in human subjects have only been reported with [11C]rolipram. As a consequence of the growing interest in identifying selective PDE inhibitors as potential new therapeutic agents, new PET radiotracers for imaging specific PDEs have been described in literature as well. This article highlights these efforts on the design and evaluation of novel PET radioligands for in vivo imaging of PDEs.

Drug discovery is a highly complex process requiring scientists from wide-ranging disciplines to work together in a well-coordinated and streamlined fashion. While the process can be compartmentalized into well-defined functional domains, the success of the entire enterprise rests on the ability to exchange data conveniently between these domains, and integrate it in meaningful ways to support the design, execution and interpretation of experiments aimed at optimizing the efficacy and safety of new drugs. This, in turn, requires information management systems that can support many different types of scientific technologies generating data of imposing complexity, diversity and volume. Here, we describe the key components of our Advanced Biological and Chemical Discovery (ABCD), a software platform designed at Johnson & Johnson to bring coherence in the way discovery data is collected, annotated, organized, integrated, mined and visualized. Unlike the Gordian knot of one-off solutions built to serve a single purpose for a single set of users that one typically encounters in the pharmaceutical industry, we sought to develop a framework that could be extended and leveraged across different application domains, and offer a consistent user experience marked by superior performance and usability. In this work, several major components of ABCD are highlighted, ranging from operational subsystems for managing reagents, reactions, compounds, and assays, to advanced data mining and visualization tools for SAR analysis and interpretation. All these capabilities are delivered through a common application front-end called Third Dimension Explorer (3DX), a modular, multifunctional and extensible platform designed to be the “Swiss-army knife” of the discovery scientist.

Determination of drug distribution in brain and other tissues is important in pharmaceutical research. Tissue drug levels need to be determined routinely as they are usually diagnostic for both efficacy and toxicity. Determination of tissue levels in small organ subregions is frequently performed due to important functional considerations. These measurements have traditionally been very tedious requiring extensive dissection and specimen pooling to achieve detection of analytes of interest. Direct and indirect methods utilizing mass spectrometry have been reported for detection of analytes in tissue specimens. Typically, these require very specialized MS or sampling equipment and are only partially successful due to analyte response. We have developed a novel approach for quantitation of tissue sections called Functional Tissue Microanalysis (FTM) in which small circular samples are removed from subregions of interest, extracted and analyzed by conventional LC/MS/MS utilizing electrospray ionization. This allows direct measurement of regional concentrations without dissection and homogenization of tissue specimens as many subregions can be sampled from a single mounted section. Utilization of the FTM approach for analysis of both sagittal and coronal rat brain sections is shown for quantitation of raclopride and rimonabant. Reproducibility of this approach and comparison to conventional methods is reported.

Supercritical fluid (SF) was discovered 200 years ago, but the use of this fluid as a mobile phase in chromatography only became popular fifty years ago. The development of the supercritical fluid chromatography (SFC) was progressing slowly due to technological problems since ten years; the interest for this chromatographic mode has been growing up as the construction of the SFC instruments is more or less similar with HPLC instruments. The main difference in SFC is the installation of a back pressure regulator which is implemented to control the pressure above the critical pressure. SFC is widely used in chiral chromatography where Polysaccharide phases are the most versatile in use. The mobile phase is mainly composed by CO2 but the polarity can be increased by adding alcohol. The nature of the alcohol can change drastically the selectivity. The choice of the best tandem stationary phase / mobile phase is difficult to predict. Hence a full screening with different stationary phases and mobile phase solvents is often mandatory. For the achiral separation, SFC is more and more used. Achiral SFC can be classified as normal phase mode, it means that stationary phases are more polar than mobile phase and retention times decrease as polarity of the mobile phase increases. Most popular stationary phases are silica linked with polar group such as aminopropyl, cyanoprpyl, diol or 2-ethylpyridine. Mobile phase are generally composed by CO2 and methanol. SFC can be used as a complementary technique for reversed phase HPLC or sometimes even to replace HPLC.

In this paper we report the development of chromatographic methods for the separation of 8 biologically active hydroxycholesterols (OHC’s) which include the single-hydroxyl addition species 7α-OHC, 7β-OHC, 25-OHC and 27- OHC, together with the double-hydroxyl addition species 7α, 25-OHC, 7β, 25-OHC, 7α, 27-OHC, and 7β, 27-OHC. Four complementary techniques were employed (gas chromatography, normal phase and reversed phase high performance liquid chromatography, and supercritical fluid chromatography), and for each of the techniques, an optimized method for the separation of all eight compounds in a mixture is presented.

A small-molecule drug discovery effort can benefit from having several chemical series. Where multiple series are not available, it is often the goal of a project to find novel scaffolds. Structural studies of ligand/protein complexes provide important information on the interactions driving binding. By generalizing these, it is possible to find molecules lacking in similarity in their connectivity yet retaining the ability to interact with the same target protein. Our studies on inhibitors of the cFMS tyrosine kinase provide a dramatic example of three different chemical series that make the same key interactions with the target protein. Collectively, these structural data provide a striking example of the pharmacophore hypothesis at work. In addition, they should prompt one to employ a broad approach when attempting scaffold hopping or any search for a novel series. It is clear that molecules that bind with similar interactions to a target need not possess 2-dimensional molecular similarity.

A major strategy used in drug design is the inhibition of enzyme activity. The ability to accurately measure the concentration of the inhibitor which is required to inhibit a given biological or biochemical function by half is extremely important in ranking compounds. Since the concept of the half maximal inhibitory concentration (IC50) is used extensively for studying reversible inhibition enzymatic reactions, it is important to clearly understand the experimental design and the mathematical modeling techniques used to generate IC50 values. The most important part of the experimental design is to measure the rate of production of [P] during the linear phase of the time course of the reaction and to prove that the enzyme- catalyzed reaction is reversible. The most important part of the mathematical modeling is to select the correct model and to have a firm understanding on how to handle outliers in the data. These topics are discussed in greater detail along with a discussion on how much quantitative and mechanistic information can be reasonably deduced from an experiment.

Various CYP time-dependent inhibition (TDI) assays have been widely implemented in drug discovery and development which has led to great success in positively identifying compounds with mechanism-base inhibition liability. However, drug-drug interaction (DDI) predictions by various in-silico models utilizing kinetic parameters obtained from TDI assays have met with significant challenges including questionable kinetic data, over-simplified in-vitro models and unreliable mathematic algorithms. Although significant efforts have been made to standardize the TDI assay and refine mathematical models, recent evaluation studies have revealed that the kinetic parameters of TDI, the most important invitro data required by all DDI prediction models, are significantly impacted by a variety of experimental variables including microsomal protein concentration, metabolic stability, CYP-specific probes, and post-incubation time. This review attempts to provide medicinal chemists a brief overview on the current status of TDI assays, determination of kinetic parameters and in silico DDI predictions with emphasis on the complexity of the TDI kinetics and limitations of current invitro models and DDI prediction methodologies.

Increasing pressure on the pharmaceutical industry to reduce cost and focus internal resources on “high value” activities is driving a trend to outsource traditionally “in-house” drug discovery activities. Compound collections are typically viewed as drug discovery’s “crown jewels”; however, in late 2007, Johnson & Johnson Pharmaceutical Research & Development (J&J PRD) took a bold step to move their entire North American compound inventory and processing capability to an external third party vendor. The authors discuss the combination model implemented, that of local compound logistics site support with an outsourced centralized processing center. Some of the lessons learned over the past five years were predictable while others were unexpected. The substantial cost savings, improved local service response and flexible platform to adjust to changing business needs resulted. Continued sustainable success relies heavily upon maintaining internal headcount dedicated to vendor management, an open collaboration approach and a solid information technology infrastructure with complete transparency and visibility.