Solid-Phase Synthesis and Combinatorial Technologies

5.4 LIBRARY DESIGN VIA COMPUTATIONAL TOOLS 203

The use of both druglike filters for monomers and structural information for target classes can easily produce high-quality libraries targeted to these receptors. In our example the replacement of the embedded pepstatinlike features could bias the obtained libraries toward other representatives of the aspartyl proteases. These firstround targeted libraries may then be further optimized, thus speeding enormously the discovery of novel potent, biologically active molecules.

5.4.4 Recent Advancements

The use of computational methods in combinatorial technologies is extremely popular, and many contributions have appeared recently. A brief list of them, together with a minimal description of their content, should be of use for all the readers to expand their knowledge about any specific topic.

Molecular descriptors are stimulating many groups of researchers, and novel descriptors are generated and validated at a fast pace. Pogliani (133) has used molecular connectivity terms to model properties such as aqueous solubility and the pH at the isoelectric point; Randic and Basak (134) have optimized the relative weight of weighted path numbers to be better suited for structure–property studies; Benigni et al. (135) have studied the potential of IR-embedded information in QSAR analysis, comparing the fingerprint region of IR spectra with other known QSAR descriptors; Filimonov et al. (136) have reported the use and the validation of multilevel neighborhoods of atoms as a set of descriptors and have successfully proven their ability to predict several physicochemical and biological properties; Eisfeld and Maurer (137) have established a good correlation between quantum-chemical calculated descriptors and the octanol/water partition coefficient of several diverse chemicals.

Descriptors have been applied to specific examples, successfully discriminating between sets of active and inactive molecules. Stanton (138) has used the burden, chemical abstract service, University of Texas (BCUT) descriptors (71) to study and rank a set of inhibitors of dihydrofolate reductase; Robert et al. (139) have used descriptors derived from steric and electrostatic quantum similarity measures to predict satisfactorily the corticosteroid-binding globular binding affinity of a family of steroids; the partial least-squares (PLS) projections to latent structures technique has been used to predict the blood–brain distribution of a set of structurally diverse drugs by Luco (140) and to predict the intestinal absorption in humans for a set of druglike compounds by Norinder et al. (141); Mestres et al. (142) have applied the a software program, based on molecular field-based similarity methods, to the creation of a pharmacophoric model for binding to HIV-1 reverse transcriptase from three non-nu- cleoside inhibitors.

The selection of compounds from molecular databases to assemble screening sets or to select sets to be acquired was reported by Sadowski (143), comparing different selection methods based on dissimilarity or clustering protocols; the selection of the most diverse subsets of reagents to create a diverse combinatorial library by using various algorithms was reported by Gardiner et al. (144); the same task was approached by Mount et al. (145) using a dissimilarity-based program which considers the conformational flexibility of reactants and of final compounds.

204 SYNTHETIC ORGANIC LIBRARIES: LIBRARY DESIGN AND PROPERTIES

Klebe and Abraham (146) reported the evaluation and ranking of virtual combinatorial libraries as sources for thermolysin inhibition through their scoring for enzyme affinity; Muegge et al. (147) scored a database of several thousands of small molecules for FK506 binding protein (FKBP) binding and compared the results with NMR-cal- culated binding affinities using the acquired information to design meaningful focused libraries; de Julian-Ortiz et al. (148) screened two large virtual libraries of phenol esters and anilides for their anti-herpes activity and selected several individuals which confirmed a moderate, micromolar activity against HSV-1 and could be considered novel leads to be further optimized.

Several reviews dealing with different areas of library design have been published (149–159); their content and the references cited therein should further illustrate the future tendencies of computer-assisted combinatorial chemistry.

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Solid-Phase Synthesis and Combinatorial Technologies. Pierfausto Seneci Copyright © 2000 John Wiley & Sons, Inc.

ISBNs: 0-471-33195-3 (Hardback); 0-471-22039-6 (Electronic)

6Synthetic Organic Libraries: Solid-Phase Discrete Libraries

This chapter will cover the subject of SP discrete libraries, which is the most popular library format currently in use in many industrial and academic laboratories. The most appealing features of this format are the significantly increased throughput and quality of individual compounds through the use of methods that allow better control of the reaction intermediates and the final library components.

The main aspects of the preparation of discrete libraries on SP will be covered in the first section, which will deal with the area of so-called parallel synthesis and discuss its application to different chemical problems. The choice of manual versus automated or semiautomated parallel synthesis will also be discussed through the detailed description of selected examples.

The analytical techniques and purification procedures used for quality control and structure determination of the intermediates and final library components will be treated in Section 6.2. A section will be devoted to five examples of SP discrete libraries, presenting in detail different approaches and solutions to obtain libraries of various size and complexity.

Finally, a section will be devoted to emerging trends in SP-supported discrete library synthesis such as the development of new supports and techniques aimed at increasing the throughput of parallel synthesis by taking advantage of miniaturization.

6.1 SYNTHESIS OF SOLID-PHASE DISCRETE LIBRARIES

6.1.1 Parallel Synthesis

The use of heterogeneous supports for organic synthesis and the SPS of small organic molecules were extensively discussed in Chapters 1 and 3, respectively. When a number of compounds are prepared simultaneously rather than sequentially, as in classical organic synthesis, the synthetic procedure can be described as being a parallel synthesis (1–5), a concept that is valid for both SP and solution-phase libraries of discretes, as we will see in Chapter 8. Thus, it is not the number of compounds produced that determines if we are synthesizing a discrete library, but rather the fact that the whole synthesis is run in parallel. This means that the preparation of reagents and solutions, the addition of monomer sets to separate reaction vessels, the reaction monitoring, and all the work-up and purification procedures are each carried out on all of the components simultaneously for any given step. For example, we could

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prepare a small array of 5 compounds in parallel as a discrete library, while the sequential synthesis of 100 compounds cannot be defined as a library but rather as a set of derivatives prepared via classical organic synthesis. The special features of parallel synthesis will be discussed in the following sections.

6.1.2 High-Throughput Organic Synthesis: Manual, SemiAutomated and

Automated Devices

The main purpose of parallel high-throughput organic synthesis (HTOS) is, as already mentioned in Chapter 4, to prepare focused libraries of discrete compounds that can be used to assess a fast, preliminary structure–activity relationship for a specific target. The components of these libraries may vary in number from tens to thousands of compounds; therefore different instrumentation and expertise are required depending on the library size.

Many examples, among which a few are cited here (6–10), report SP discrete libraries prepared by manual techniques using nonautomated laboratory equipment. This may include glassware such as reaction flasks or, more commonly, glass vials in conjunction with the typical synthetic organic chemist’s arsenal of tools such as plastic syringes with porous frits, Eppendorf tubes, pipettes, and pipette tips (all of which are cheap); some basic analytical instrumentation to monitor reactions off-bead after cleavage of the intermediates; and some equipment for work-up and purification such as manifolds to connect syringes to the vacuum and rotary evaporators. With just a simple mind switch and some inexpensive materials, the synthesis of 10or even 100-member discrete libraries is quickly and effectively accomplished in any organic chemistry laboratory. The addition of commercially available multiple synthetic devices, often based on 96-well plate architectures (Fig. 6.1; 11–13), of smart handling protocols of alternate supports (14) and of multichannel pipettes for solution handling allows the parallel synthesis, work-up, and purification of hundredsto thousandsmember libraries of discretes with reasonable effort and moderate expense.

Repetitive operations are the rule, rather than the exception, in SP library synthesis, especially when the library size increases, and sometime they become tedious for the operator and can become a significant source of experimental error. While manual synthesis can be effective and inexpensive, the introduction of partially or fully automated procedures allows a more reliable experimental protocol and often a higher throughput. Moreover, the automated steps do not require the presence of the chemist, who thus can focus his or her attention on the more scientifically challenging problems of chemical assessment and library design. When automation is introduced in some of the steps of library preparation, we talk of semiautomated techniques. Normally the repetitive operations are automated while other steps (e.g., addition of solid reagents and evaporation of cleavage solutions) are still performed manually by the chemist. For example, a popular semiautomated synthetic device (15–17) has been designed to automate operations such as washing cycles, bubbling of gas, and stirring of resin aliquots, thus decreasing (or eliminating) the most tedious steps, which require the attention of the chemist. Other operations with a more significant variance are performed manually. Other similar devices (18–20) are suited not only to the produc-

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reaction well

96-well plate

Figure 6.1 A 96-well architecture of a microtiter plate for SP parallel synthesis.

tion of small discrete libraries but also to semiautomated optimization studies to assess the best SP conditions for a synthetic strategy. They are flexible and can be easily located in a chemistry cupboard and, although their cost is significant, this is balanced by their usefulness in a laboratory that produces several focused libraries per year. A higher throughput, simple semi-automated robotic station based on surface suction rather than on filtration of liquids is suited to wash in parallel thousands of SP discretes but also, in particular conditions, to perform basic SP reaction protocols (21).

More complex instrumentation that allows the automation of every step of an SPS of discrete libraries is also available from several commercial sources. These fully automated machines can be grouped into instruments that are best suited to chemical assessment studies (22) in which the reaction conditions of each reaction vessel can be varied and instruments that are directed toward library production (23–27) in which an automated protocol is used to generate sets of compounds on a common reaction block, usually made up of 96 reaction wells. It is important to note that, while some operations are significantly accelerated using automation, others require the same or even more time than when performed manually. The advantage of a fully automated synthesizer is that the system controls and drives everything and the operator supposedly only collects the outcome of the synthetic procedure at the end of the operations. In terms of throughput, automated SP synthesizers can vary from low (chemical assessment) to medium (library production) while high-throughput SP organic syn-