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In the past decade, it became clear that some fundamental problems were arising in drug discovery. It was becoming harder to find new chemical entities with substantial advantages over existing drugs. Consequently, it became riskier and more expensive to develop new drug entities. [ABSTRACT FROM AUTHOR]

Half a century ago, the term "drug discovery" conjured images of adventures into the jungle, beneath the sea, and atop mountains in search of frogs, sponges, lichens, or any unstudied life form that, ground up, might exhibit inhibitory effects toward a major human disease. More romantic and exciting science cannot be, to those of us too young to have participated in the "old" drug discovery paradigm, and perhaps also not more laborious, unpredictable, and frightening when included in a business plan. Combinatorial chemistry and high-throughput screening evolved to fill the need for a more systematic approach to discovery, in which miniaturization and automation were applied, as in traditional manufacturing processes, to reduce costs and cycle times. But to the contrary, the cost associated with producing clinical candidates seems to have actually risen with the application of these technologies (1-3). [ABSTRACT FROM AUTHOR]

With the current and ever-growing offering of reagents along with the vast palette of organic reactions, virtual libraries accessible to combinatorial chemists have dramatically increased in size. Yet, extracting suitable subsets for experimentation is an essential step in the design of combinatorial libraries. Several approaches to this problem can be envisaged, involving either reagent-based or product-based considerations. Reagent-based designs tend to be popular with chemists, as they provide highly practical means of weeding extensive reagent lists based on property and substructure considerations. They can also provide suitable reagent selections for model studies. However, reagent-based designs also overlook the extent of chemical transformations involved in generating products. Several studies have demonstrated the superiority of product-based designs in yielding diverse and representative subsets. Although more computationally intensive, product-based approaches present significant advantages, and they are also more amenable to the incorporation of drug-like restraints. [ABSTRACT FROM AUTHOR]

With the advent of high-throughput technologies in drug discovery, combinatorial chemistry has superseded natural products as the prime source of compounds to be tested in biological screening (1). The reason being that compared with classical synthesis, high-throughput chemistry can produce a much larger number of compounds within a much shorter period of time. However, owing to the combinatorial nature of the problem and the large number of reagents available, many more compounds are theoretically accessible via a given synthetic route than it is actually feasible to synthesize. Therefore, library design techniques are employed to identify those reagents that yield a library enriched with the desired properties. Early on, most applications of these techniques concentrated on designing very diverse libraries, with the idea that these libraries would be tested against a variety of biological assays. The ideal library in this case would be with no voids, no redundancy, and an even distribution with regard to a given chemical space. Nowadays, it is equally common to design targeted libraries to have a maximal activity in a selected assay. Here, all compounds would be designed to be similar to given hits or leads. Other applications of library design techniques include the computational evaluation of templates, i.e., prioritization of candidate libraries for synthesis and screening (see Note 1). [ABSTRACT FROM AUTHOR]

Last year marked the completion of the sequencing effort on the human genome. Advances in the fields of genomics and bioinformatics are widely expected to bring forth a large number of new biochemical targets for drug design by linking specific diseases to single genes or collections thereof. The pharmaceutical and biotechnology sector is now likely to become one of the most active industrial fields in the new century. A dramatic increase in the number of pharmaceutical targets in the near future would create a bottleneck of sorts at the stage of pharmaceutical drug discovery. Historically, this field has used a serial process, screening and optimizing compounds one at a time. However, the advent of combinatorial chemistry and high-throughput screening has significantly altered the face of drug discovery. Rapid generation and screening of combinatorial libraries has become commonplace in both industry and academia; with the ever-growing offering of organic reagents along with the vast palette of organic reactions, the chemical space accessible to combinatorial chemists has dramatically expanded. The application of combinatorial technology, however, is not without a potential caveat—even as the cost of synthesis and testing of a single chemical entity has fallen, it skyrockets when multiplied by the thousands or millions of combinatorial library members. Some of the potential solutions include (i) use of the three-dimensional target structure information in the design process; (ii) application of pharmacophore and quantitative structure-activity relationship (QSAR) methods to focus on libraries that most closely resemble screening hits; and (iii) reduction in the scale on which both medicinal chemistry and screening are currently performed. These solutions imply a need for a rational approach to reducing library size, custom izing the library for a given target, and more efficient in silico screening of a library (or, potentially, multiple libraries) of compounds against a large number of targets of interest. The challenge in accomplishing these goals is in being able to reduce the library while increasing the potential hit rate of individual library members. [ABSTRACT FROM AUTHOR]

Sequencing of the human and other genomes has revolutionized drug discovery. Modern functional genomics methods have brought a wealth of drug discovery targets. Bioinformatic tools are classifying candidate drug targets into different mechanistic classes. Many classes are apparent, but pharmaceutical companies are clearly focusing on proteases, protein kinases, and G-protein coupled receptors (GPCRs). This is perhaps because of the relatively direct nature of assigning these sequences to gene families, especially when the family features are so distinctive, e.g., seven transmembrane segments as a signature for GPCRs. Moreover, two of these are proven pharmaceutical targets with large drug markets (proteases and GPCR). Even though most target genes will fit into mechanistic families as determined by bioinformatic tools, others will fail to fit. Also, some fits will be misleading for example, the sequences of membrane forms of guanylyl cyclases are homologous to protein kinases (1). Thus, there is a need for tools to find surrogate ligands and substrates to serve as reagents to measure inferred bioactivities and discover leads to both pharmacologically validate novel drug targets and provide entry for lead optimization to obtain new drugs for unMet medical needs. [ABSTRACT FROM AUTHOR]

The development of combinatorial chemistry has made a profound impact on the pharmaceutical industry by producing a large number of structurally diverse compounds in a very short amount of time. Combined with high-throughput screening, bioinformatics, and laboratory automation, the combinatorial chemistry approach has led to a significantly accelerated drug discovery process compared to a traditional one-compound-at-a-time approach (1). With a potential explosion of the number of biological targets available for various diseases from genomics and proteomics, combinatorial chemistry and parallel synthesis will be further embraced by the pharmaceutical industry, leading the way to rapidly generate a large number of chemical libraries to screen for different disease targets. Currently, thousands of potentially bioactive compounds are made every week by combinatorial chemistry synthesis. Subsequently, these compounds go through various high-throughput biological screens in different therapeutic areas to find biologically active compounds or hits. However, in order to ensure true hits from these various screening assays, initial sample purification to remove assay-interfering components is required to prevent false positive or negative results. This initial sample cleanup step poses a great challenge to synthetic and analytical chemists, because purification in a high-throughput and fully automated fashion is needed to keep up with the fast pace of combinatorial synthesis and high-throughput biological screening. [ABSTRACT FROM AUTHOR]

Combinatorial methods have been applied with a measure of success in the field of metal ion coordination chemistry (1-5). High-throughput screening methods have been used to facilitate the discovery of new catalysts and to design ligands for binding metal ions (6-9). Metal ion coordination complexes have been central to the development of dynamic combinatorial methods as well. Dynamic combinatorial methods utilize a library whose composition is con-trolled through reversible interactions with a target molecule (10,11). Metalligand bonds are often labile enough to undergo reversible bond formation under mild conditions, making metal ions ideal components for dynamic librar-ies. Such metal ion complexes are used in dynamic combinatorial libraries for the purpose of designing compounds with unusual shapes or recognition properties (12,13). [ABSTRACT FROM AUTHOR]

As human enzymes and cell surface receptors possess handedness, the enantiomers of a racemic pair of compounds may be absorbed, activated, and degraded in different manners. In some instances, two enantiomers of a racemic drug may have different or even opposite pharmacological activities. In order to acknowledge these differing effects, the biological activity of each enantiomer often needs to be studied separately. This and other factors within the pharmaceutical industry have contributed significantly to the need for enantiomerically pure compounds (1). Consequently, the need to analyze and separate racemic compounds efficiently is of significant importance in pharmaceutical research. Among the asymmetric technologies developed, chromatographic methods are widely used. [ABSTRACT FROM AUTHOR]

Rapid lead discovery in the drug development process relies on highthroughput screening of diverse compounds against protein targets. These compounds come from traditional organic synthesis, natural products isolation, and combinatorial synthesis (1). For compounds from combinatorial synthesis, the hit rate highly depends on the quality of the compounds. We employ parallel solid-phase (2) and solution-phase (3) synthesis methods to make lead discovery libraries containing approx 6000 compounds in each library. [ABSTRACT FROM AUTHOR]

Cross-linked polymer supports are now ubiquitous throughout the fields of combinatorial chemistry, organic synthesis, and catalysis (1,2). However, problems associated with the heterogeneous nature of the ensuing chemistry and with "on-bead" spectroscopic characterization have meant that soluble polymers are developing as alternative matrices for combinatorial library production and organic synthesis (3,4). Synthetic approaches that utilize soluble polymers, termed "liquid-phase" chemistry or soluble polymer-supported chemistry, couple the advantages of homogeneous solution chemistry—high reactivity, lack of diffusion phenomena, and ease of analysis—with those of solid phase methods—use of excess reagents and easy isolation and purification of products. Separation of the functionalized matrix can be achieved by a number of processes. Methods include solvent or heat precipitation, membrane filtration, and size-exclusion chromatography. This chapter will detail both the different areas of synthetic and combinatorial chemistry in which soluble polymer supports are used and the experimental techniques exploited. [ABSTRACT FROM AUTHOR]

Over the past few years, combinatorial chemistry has emerged as an exciting new approach to discover novel drug candidates. It contains many tactics and processes for the rapid synthesis of large, organized collections of lowmolecular-weight compounds without tedious and time-consuming purification. In combination with high-throughput screening, combinatorial organic synthesis of pharmaceutically interesting molecules may revolutionize the drug discovery program. Combinatorial chemistry has become increasingly popular in academic institutes and industries. It has been reported (1) that in the early years of 1992−1998, 63% contributors of combinatorial chemistry were from industry and 37% from academic laboratories. In the past two years, both academic institutes and pharmaceutical companies have developed novel combinatorial techniques for library synthesis equally. The majority of academic publications showed new synthetic methodologies; however, pharmaceutical companies used this technique for rapid screening and synthesizing of biologically active compounds. [ABSTRACT FROM AUTHOR]

The purity control and the structure verification of compound collections from automated synthesis and combinatorial chemistry play an essential role in the success of medicinal chemistry programs. High performance liquid chromatography (HPLC), mass spectrometry (MS), and liquid chromatographymass spectrometry (LC-MS) techniques are generally accepted as the most appropriate means of characterization (1,2). While these analytical methods are fast and easy to automate, they do not provide sufficient structural and quantitative data about the desired products. [ABSTRACT FROM AUTHOR]

At the heart of host—guest chemistry is the design and construction of artificial receptors. While great progress has been achieved in the specific recognition of a multitude of substrates, rational design has still failed to equal the degree of association strength and substrate specificity observed in nature. Evolutionary selection has allowed biopolymers to take advantage of their large size to position varied functionality in the rigid context of tertiary structure, but the limitations of chemical synthesis dictate that artificial receptors will be smaller, less structurally defined, and, as a result, less effective. Combinatorial chemistry offers a new approach to the task of receptor design by quickly creating a library of combinatorial receptors containing a variety of binding or catalytic groups, and subsequently determining the most active component of that library (1-5}). Combinatorial receptors also provide the possibility for using substrate binding to selectively create a receptor from a dynamic library (6-8). To be effective, however, library synthesis should require minimal synthetic expenditure and the entire library must be screened efficiently. [ABSTRACT FROM AUTHOR]

Very few diseases are directly caused by ion channel mutations, yet many drugs for various diseases work by modulating ion channel activity. This is because ion channels are cellular "gatekeepers," monitoring intracellular concentrations of Na+, Ca+, K+, or Cl− to control cardiac pacemaking, membrane potential, neurotransmitter release, hormone secretion, cell proliferation, cell volume regulation, and lymphocyte differentiation. One ion channel that controls lymphocyte differentiation is the highly T cell specific Kv1.3 channel. Since the discovery of Kv1.3 channels in Tc cells, these lymphocyte channels have been targeted in developing immunomodulatory drugs that might exhibit lower toxicities than those currently in use (1,2). [ABSTRACT FROM AUTHOR]

Small molecules that recognize double-stranded DNA have the capacity to modulate various cellular processes, including DNA replication and repair, gene expression, cell cycle regulation, and growth, and therefore may serve as treatments for cancers or various genetic diseases. Currently, most DNA-binding therapeutics target short sequences of DNA with rather low selectivity, causing deleterious effects in both diseased and healthy cells (1). Thus, the development of molecules that target longer, more cell-type-specific sequences of DNA is of great interest. In this chapter, a rapid solid-phase synthesis of hairpin polyamides, a promising class of minor groove binding agents developed by the Dervan group at Caltech, is described (2). The robust coupling methods of aromatic amino acids outlined facilitate the application of combinatorial methods to polyamides and their further development as pharmaceutical reagents. [ABSTRACT FROM AUTHOR]

The recent interest in organic solid phase synthesis, triggered by the advent of chemical combinatorial methods (1-7), also accelerated methodology development. Simplification of chemical protocols, their robustness, and amenability to handling large arrays of compounds, prepared by combinatorial/ parallel solid phase synthesis, is one area that witnessed numerous novel contributions. This chapter describes an apparatus and method for gaseous cleavage of compounds from solid phase supports. [ABSTRACT FROM AUTHOR]

An inherent feature of parallel solid phase synthesis is the need to handle a large number of reaction vessels at the same time. Consequently, in order to make demanding synthetic tasks manageable, two categories of synthesizers, manual and automated, have been designed and produced. The main feature of a manual synthesizer is the integration of reaction vessels and common steps during synthesis. Reaction vessels are combined into so-called reaction blocks that enable performing specific operations (e.g., washing resin beads, adding common reagents, incubation) in all integrated reaction vessels at the same time. An automated synthesizer offers full automation of the entire synthetic process. The reaction vessels can be controlled on an individual basis and independent protocols can be performed in different vessels. Semiautomatic instruments feature integration and automation of the most commonly occurring steps. Even though full automation brings numerous advantages, the throughput of "manual" laboratories does not need to suffer. Without any expensive automated devices, production may still reach a thousand compounds per day. [ABSTRACT FROM AUTHOR]

The revolution in genomics and proteomics is projected to expand the number of potential therapeutic targets to between 5,000 and 10,000 from the approximately 500 targets that have historically been used by the pharmaceutical industry in the development of drugs (1,2). The research and development of a safe and effective drug is a slow and expensive process, which is currently estimated to take an average of 12 years and to have a risk adjusted cost of $500 million per drug (3). The pharmaceutical industry is under intense pressure to bring novel drugs to market quickly and cost-effectively. Combinatorial chemistry has emerged during the past decade as a powerful tool to help accelerate the drug discovery process (4-7). Combinatorial chemistry refers to methods for the high-throughput synthesis of a significant number (102 to >106) of compounds (8). Among the various methods developed (9-20), the solidphase split-pool synthesis (21-23) is perhaps the most efficient approach for the rapid synthesis of a large number of compounds. In this approach, a library that usually contains >10,000 members can be constructed very rapidly from a small number of chemical building blocks. Figure 1 illustrates the split-pool synthesis with a two step reaction A + B that uses three building blocks in step 1 (A1, A2, A3) and three building blocks in step 2 (B1, B2, B3). Nine products can be generated using only six reactions. [ABSTRACT FROM AUTHOR]

Combinatorial chemistry (1-7) has drastically modified the drug discovery process by allowing the rapid simultaneous preparation of numerous organic molecules to feed bioassays. Most of the time, syntheses are carried out using solid-phase methodology (8). The target compounds are built on an insoluble support (resins, plastic pins, etc). Reactions are driven to completion by the use of excess reagents. Purification is performed by extensive washing of the support. Finally, the molecules are released in solution upon appropriate chemical treatments. [ABSTRACT FROM AUTHOR]

Since the introduction of solid-phase peptide synthesis by Merrifield (1) nearly forty years ago, solid-phase techniques have been applied to the construction of a variety of biopolymers and extended into the field of small molecule synthesis. The last decade has seen the emergence of solid-phase synthesis as the leading technique in the development and production of combinatorial libraries of diverse compounds of varying sizes and properties. Combinatorial libraries can be classified as biopolymer based (e.g., peptides, peptidomimetics, polyureas, and others [2,3]) or small molecule based (e.g., heterocycles [4], natural product derivatives [5], and inorganic complexes [6,7]). Libraries synthesized by solid-phase techniques mainly use polystyrene-divinylbenzene (PS) derived solid supports. Owing to physical and chemical limitations of PS-derived resins, other resins have been developed (8,9). Most of these resins are prepared from PS by functionalizing the resin beads with oligomers to improve solvent compatibility and physical stability (8,9). [ABSTRACT FROM AUTHOR]