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47.The diagonal peaks lie along the F2 at F1 0 axis and represent the chemical shift as in a COSY spectrum. The F1 axis represents one-half of the chemical shift difference between the coupled spins.

48.S Sarkar, RS Garigipati, JL Adams, PA Keifer. An NMR method to identify nondestructively chemical compounds bound to a single solid-phase-synthesis bead for combinatorial chemistry applications. J Am Chem Soc. 118:2305–2306, 1996.

49.A Borchard, WC Still. Synthetic receptor binding elucidated with an encoded combinatorial library. J Am Chem Soc 116:373–374, 1994.

50.RM Valerio, AM Bray, RA Campbell, A Dipasquale, C Margellis, S. J. Rodda, HM Geysen, NJ Maeji. Multipin peptide synthesis at the micromole scale using 2-hydroxyethyl methacrylate grafted polyethylene supports. Int J Peptide. Protein Res 42:1–9, 1993.

51.HU Gremlich, SL Berets. Use of FT-IR internal reflection spectroscopy in combinatorial chemistry applied spectroscopy 50:532–536, 1996.

52.WP Aue, E Bartholdi, RR Ernst. Two dimensional spectroscopy. Application to nuclear magnetic resonance. J Chem Phys 64:2229, 1976.

53.M Spraul, M Hoffman, P Dvortsak, JK Nicholson, ID Wilson. High-performance liquid chromatography coupled to high-field proton nuclear magnetic resonance spectroscopy: application to the urinary metabolites of ibuprofen. Anal Chem 65:327–330, 1993.

54.K Albert Angew. Direct on-line coupling of capillary electrophoresis and 1H NMR spectroscopy. Chem Int Ed Engl 34:641–642, 1995.

55.DL Olson, TL Peck, AG Webb and JV Sweedler. On-line NMR detection for capillary electrophoresis applied to peptide analysis. Peptides: Chem Struct Biol PTP Pravin, RS Hedges, (eds.). Mayflower Scientific, Ltd. 730–731, 1996.

56.JC Lindon, RD Farrant, PN Sanderson, PM Doyle, SL Goughg, M Spraul, M Hoffman, JK Nicholson. Separation and characterization of components of peptide libraries using on-flow coupled HPLC-NMR spectroscopy. Magn Reson Chem 33:857–863, 1995.

57.S Smallcombe, SL Patt, PA Keifer. WET solvent suppression and its applications to LC NMR and high-resolution NMR spectroscopy. J Magn Reson A 117:295– 303, 1995.

58.C Dalvit, JM Bohlen. Multiple-solvent suppression in double-quantum NMR experiments with magic angle pulsed field gradients. Magn Reson Chem 34:829– 833. 1996.

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60.F Sebestyen, G Dibo, A Kovacs, A Furka. Chemical synthesis of peptide libraries. Bioorg Med Chem Lett 3:413–418, 1993.

61.K Johnson, LG Barrientos, PPN Murthy. Application of two-dimensional total correlation spectroscopy for structure determination of individual inositol phosphates in a Mixture. Anal Biochem 231:421–431, 1995.

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62.P Stilbs, K Paulsen, PC Griffiths. Global least squares analysis of large, correlated spectra data sets. Application to component-resolved FT-PSGE NMR spectroscopy. J Chem Phys 100:8180–8189, 1996.

63.SJ Gibbs, CS Johnson Jr. A PFG NMR experiment for accurate diffusion and flow studies in the presence of eddy currents. J Magn Reson 93:395–402, 1991.

64.KF Morris, CS Johnson Jr. Diffusion-ordered two-dimensional nuclear magnetic resonance spectroscopy. J Am Chem Soc 114:3139–3141, 1992.

65.KF Morris, CS Johnson Jr. Resolution of discrete and continuous molecular size distributions by means of diffusion-ordered 2D NMR spectroscopy. J Am Chem Soc 115:4291–4299, 1993.

66.KF Morris, P Stilbs, CS Johnson Jr. Analysis of mixtures based on molecular size and hydrophobicity by means of diffusion-ordered 2D NMR. Anal Chem 66:211–215, 1994.

67.M Lin, DA Jayawickrama, RA Rose, JA Delvisio, CK Larive. Nuclear magnetic resonance spectroscopy analysis of the selective complexation of the cis and trans isomers of phenylalanylproline by B-cyclodextrin. Anal Chim Acta 307: 449–457, 1995.

68.M Liu, JK Nicholson, JC Lindon. High-resolution diffusion and relaxation edited oneand two-dimensional 1H NMR spectroscopy of biological fluids. Anal Chem 68 3370–3376, 1996.

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5

The Role of Liquid Chromatography

Michael E. Swartz

Waters Corporation

Milford, Massachusetts

I.INTRODUCTION

Chromatography alone, or in combination with other analytical techniques, has been used for a number of years in the drug discovery process in support of traditional organic synthesis for compound identification, compound purity and stability determinations, from lead discovery to final lead optimization, testing, and candidate selection. However, in response to increasing demands in the pharmaceutical industry to accelerate the drug discovery process and identify lead compounds in increasing numbers, new avenues of approach, such as combinatorial chemistry, must be investigated.

Combinatorial chemistry synthesis techniques have presented new challenges to the analytical chemist. During lead discovery, libraries of large numbers of compounds, numbering from 10–20, to hundreds, thousands, ten of thousands, or even millions of compounds are generated. Therefore, due to the sheer numbers of compounds, assays must be rapid, as well as capable of determining quantity, purity, and whether or not the proper compound was synthesized. Further along the drug discovery path, during lead optimization and testing leading to candidate selection, compounds are required in larger quantities. Analytical techniques used in lead discovery now give way to preparative, mass-directed autopurification techniques, capable of isolating and purifying 10–20 mg of the compound of interest during a single chromatographic analysis. Furthermore, all of the assays, from the analytical to prepara-

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tive scale, must be accessible to everyone in the drug discovery process, in what has become to be known as an ‘‘open access’’ environment. In response to these challenges, chromatographers have had to rethink their strategy in order to provide timely and complete information and feedback.

In order to be successful, a proper method, like any other type of assay, run on the appropriate instrument, must be employed. In addition, software, both for systems operation/integration and data analysis, also plays a central role. This chapter will address how chemists, using chromatography, have adapted in answering the challenges presented by a combinatorial chemistry program of drug discovery. While not intended to be an exhaustive review, this chapter focuses predominantly on liquid chromatography (LC), discussing various applications and techniques that highlight its use in the drug discovery process.

Since application of fast, generic LC methods with mass spectrometry (LC/MS) is emerging as the technique of choice for assessing the progress and final quality of large combinatorial arrays in drug discovery, it will be discussed in some detail, along with other detection techniques. Mass-directed purification and characterization on the preparative scale will also be addressed.

II.BASIC HIGH-THROUGHPUT ANALYSIS AND CHARACTERIZATION

A.Chromatographic Optimization and Injection Overhead Reduction

The first step in drug discovery is lead identification before high-throughput screening. This step is characterized by use of combinatorial libraries varying in size from a few hundred to tens of thousands (or more) compounds. Assays should provide simple, basic information such as compound identification on a molecular weight basis, and the synthesis yield (purity). In order to answer these questions, methods must satisfy certain requirements. Gradient reverse phase liquid chromatography (RP-LC) with various detection modes can satisfy these requirements and is currently the method of choice for the analysis of combinatorial libraries and synthesis-related products (1–5).

The sheer number of samples, their diversity, and a lack of suitable standards for quantitation can at first seem an insurmountable challenge. Since method development for individual samples is not feasible due to time and economic factors, a broadly applicable ‘‘generic’’ method must be developed, without sacrificing information content. Also, an inject-to-inject cycle time of

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2–5 min (or less!) is desired to accomplish the required sample throughput. Methods and instruments also need to be compatible with various detection methods in addition to MS, such as photodiode array (PDA), evaporative light scattering, and nitrogenand sulfur-specific chemiluminescence detection. Finally, it is important to keep in mind that once a lead has been identified, it may be necessary to scale up the separation (with instrument and chemistry implications) to isolate larger amounts of pure material for additional studies.

Chromatographic instruments used in support of combinatorial chemistry require features somewhat different from those of traditional systems (5– 8). The basic components of a system are the same: a solvent manager (pump), a sample manager (autosampler or injector), a detector(s), a data system, and, in some instances, a fraction collector. However, some important differences exist. The most significant difference is the sample manager. Samples can be presented in standard vials, tubes, or microtiter plates of various sizes and capacities, either singly or in various combinations. Therefore some type of ‘‘XYZ’’ sample management device is dictated. Other important differences include software instrument access and control, and data reduction and reporting.

Let’s examine a typical hypothetical situation. Assume an analyst has just received a combinatorial library on six high-density 384-well microtiter plates, for a total of 2304 samples of which all are unknown, all are different, and all differ in the degree of purity, for analysis in the lab. The traditional approach would be to use a gradient RP-LC method similar to that presented in Fig. 1. Using a long column and a shallow gradient is typically the first step in developing and optimizing a method. However, given the number of compounds involved, individual method development is highly impractical. Under the conditions used in Fig. 1, including 20 min of postrun reequilibration time, analysis of the 2304 samples would take more than 96 days! Although multiple systems could be used to analyze the samples, additional steps must be taken to improve sample throughput and to maintain final method detector compatibility in a full-time combinatorial chemistry support laboratory.

Several options, either alone or in combination, can be employed to improve sample throughput. Obvious options include using shorter columns, higher flow rates and temperatures, and/or sacrificing resolution. Figure 2A shows a separation of the same sample illustrated in Fig. 1, but with a smaller column at higher flow rates. The chromatographic test sample used spans a wide elution range; however, the peak capacity of the method remains high. Under these conditions, the total time for the analysis of the 2304 samples was decreased by an order of magnitude to less than 8 days. The column used

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Figure 1 Separation of a chromatographic test mixture by a traditional gradient method. Separation was performed on Waters Alliance HPLC System (Waters Corporation, Milford, MA) and a 3.9 by 150mm 5 micron particle size Symmetry C18

column at 30° C. The mobile phase consisted of 0.1% phosphoric acid as the A solvent, and acetonitrile as the B solvent, run as a linear gradient from 0–80% B over 40 minutes at 1.0 mL/min. Total analysis time does not include twenty minutes of post run reequilibration of the column and system. UV detection at 254nm, and a 20 L injection was used. Peaks 1–12 (0.1mg/mL each in 50/50 methanol/water) are uracil, theophyline, acetylfuran, acetanilide, acetyl-, propio-, butyro-, benzo-, valero-, hexano-, hep- tano-, and octano-phenone, respectively.

to generate the example chromatogram shown in Fig. 2A had a smaller particle size (3.5 m) and an increased internal diameter was used (4.6 mm) to accommodate the increased flow rate of 4 mL/min. A formic acid instead of a phos- phate-buffered mobile phase was used for better MS compatibility.

Besides using a lot of mobile phase, analyses run at these high flow rates are not compatible with an MS detector without some sort of split to divert flow. For many LC analyses, flow splitters are a fact of life when using MS detection. However, Fig. 2B illustrates that separation of the chromatographic test sample can be further scaled to a 2.1-mm i.d. column, now running at an equivalent linear velocity (1.0 mL/min). Under the conditions used in

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Figure 2 (A) Generic method optimized for high-throughput. Separation was performed on a 4.6 by 50mm 3.5 micron particle size Symmetry C18 column (Waters

Corporation, Milford, MA) at 30° C. The mobile phase consisted of 0.1% formic acid as the A solvent, and acetonitrile as the B solvent, run as a linear gradient from 0– 100% B over 3 minutes at 4.0 mL/min. All other conditions (injection, detection, and sample) were identical to those listed in Figure 1. (B) Chromatography optimized by

APCI/MS detection. Separation was performed on a 2.1 by 50mm 3.5 micron particle size Symmetry C18 column (Waters Corporation, Milford, MA) at 1.0 mL/min. and

at 30° C. Mobile phase and gradient conditions were identical to Figure 2A. All other conditions (injection, detection, and sample) were identical to those listed in Figure 1.

Fig. 2B, atmospheric pressure ionization MS can be used directly without splitting the flow. However, depending on the compound class or type in the library being analyzed, electrospray ionization might be preferred and in some cases might still necessitate a split flow, depending on the flow rate and mobile phase composition.

Figures 3 and 4 illustrate the diversity of the method. In Fig. 3, six penicillin-type antibiotics representing a somewhat more realistic sample are separated. Peak 1 is the synthetic precursor for the rest of the compounds in the

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Figure 3 Separation of penicillin type antibiotic homologous series. Separation conditions are identical to those reported in Figure 2B. Peaks 1–6 are: 6-aminipenicillanic acid, amoxicillin, ampicillin, oxicillin, cloxicillin, and dicloxicillin, respectively.

mixture, and peaks 4–6 differ only by a chlorine atom, representing possible synthesis byproducts. The generic method readily resolves all of the components in this series of homologous compounds, in spite of the wide polarity range. Figure 4 shows the separation of another test mix of ‘‘drug-like’’ compounds reported in the literature for use as a chromatographic test mixture (8).

Although the improvements illustrated in Figs. 2–4 are significant, it is possible to improve sample throughput even more dramatically. When determining sample throughput capabilities for short run times, additional system timing issues must be taken into account. That is, to determine actual sample throughput, cycle-to-cycle inject times must be determined that take into account all other aspects of each individual sample analysis. Run time, while important, is only one factor in determining overall cycle-to-cycle inject times. The amount of time it takes to position the injector, aspirate a sample, load the sample loop, inject the sample, and rinse the injector apparatus is referred to as ‘‘injection overhead.’’ While injection overhead varies from instrument to instrument, times from 1 to 2 min per injection cycle are not uncommon. In

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Figure 4 Separation of chromatographic test mix showing generic method diversity. Separation conditions are identical to those reported in Figure 2B. Peaks 1–5 are uracil, 1-hydroxy-7-azabenzotriazole, methoxybenzenesulfonamide, methyl-3-amino-2-thio- phenecarboxylate, and 4-aminobenzophenone, respectively.

a 40-min run, with 15–20 min of post run time, 1–2 min is hardly significant. However, with run times as short as 5 min, the injection overhead can add 20% or more to the cycle-to-cycle inject time. Another parameter that must be considered in the cycle-to-cycle inject time is the time it takes to reequilibrate the column and the system following the gradient. Each of these functions is illustrated in Fig. 5 for an LC system operated in the traditional ‘‘sequential’’ mode. Obviously, anything that can be done to reduce the time it takes to accomplish these tasks will also improve sample throughput. As shown in Fig. 6, a separation of an 11-component mix in the sequential mode with a 5-min run time can consume an additional 1.2 min due to injection overhead, for a total cycle to cycle inject time of 6.2 min. If, however, some of these functions can be performed in a ‘‘parallel’’ mode, as illustrated in Fig. 7 (p. 122), additional time savings could be realized. In the parallel mode of operation, sample-manager needle and inject port washes, and aspiration of the next sample takes place during the actual run, saving considerable time.