A Method for Identifying and Developing Functional Group Tolerant

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A Method for Identifying and Developing Functional Group Tolerant Catalytic Reactions: Application to the Buchwald−Hartwig Amination Jeffery Richardson,*,† J. Craig Ruble,‡ Elizabeth A. Love,§ and Simon Berritt∥

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Discovery Chemistry Research and Technologies, Eli Lilly and Company Limited, Erl Wood Manor, Windlesham, Surrey GU20 6PH, United Kingdom ‡ Discovery Chemistry Research and Technologies, Eli Lilly and Company, Indianapolis, Indiana 46285, United States § Translational Research Office Drug Discovery Group, University College London School of Pharmacy, 29−39 Brunswick Square, London WC1N 1AX, United Kingdom ∥ Penn/Merck Laboratory for High-Throughput Experimentation, Department of Chemistry, University of Pennsylvania, 231 South 34th Street, Philadelphia, Pennsylvania 19104-6323, United States S Supporting Information *

ABSTRACT: Transition-metal catalysis has revolutionized organic synthesis, but difficulties can often be encountered when applied to highly functionalized molecules, such as pharmaceuticals and their precursors. This results in discovery collections that are enriched in substances possessing less desirable properties (high lipophilicity, low polar surface area). Masking groups are often employed to circumvent this problem, which is in opposition to the inherent ideality of these methods for green chemistry and atom economy. A general screening methodology, related to robustness screening described by Glorius et al., builds a broad understanding of the impact of individual functional groups on the success of a transformation under various conditions and provides a simple framework for identifying new conditions that tolerate challenging functional groups. Application of this approach to profile the conditions for the Buchwald−Hartwig amination and rapidly identify bespoke conditions for challenging substrate classes is described.

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INTRODUCTION Drug discovery programs frequently call upon compound libraries to establish structure−activity relationships, testing hypotheses around binding affinity and efficacy, in addition to absorption, distribution, metabolism, and excretion properties of potential drug candidates. The ability to efficiently prepare these diverse libraries is vital to the success of drug discovery programs, so robust and reliable methods that tolerate the presence of diverse functional groups are essential. In spite of the many “general” reaction conditions that are described in the literature, the preparation of diverse libraries of compounds for determination of structure−activity relationships best demonstrates some important challenges for new methodologies, especially in catalysis. Cernak, Dreher, and co-workers at Merck recently disclosed an analysis of 2149 metal-catalyzed C−N couplings performed in the synthesis of highly functionalized drug leads.1 This revealed that 55% of reactions failed to deliver any product at all and pointed to the “growing recognition that the tendency of polar, highly functionalized compounds to fail in catalysis may actually enrich compound sets in hydrophobic © 2017 American Chemical Society

molecules that are less likely to become successful drug candidates.”2 Similarly, the increased number of protecting group manipulations that appears in the pharmaceutical patent literature over the last 30 years has been attributed to increased use of catalytic methods that frequently do not tolerate druglike functional groups without protection.3 This opposes the goals of green chemistry,4 atom economy,5 and protecting group free manipulations6 that are becoming increasingly important in modern organic chemistry. One of the challenges in preparing a library of compounds seeking to explore different dimensions of property space is that the chemistry used to prepare each library member is likely to perform differently. Ideally, for any given transformation, a single set of reaction conditions would exist that is effective for all conceivable substrates. Since the various starting materials are likely to have different properties (reactivity, stability and solubility) and purities, this is extremely unlikely. Although Received: January 25, 2017 Published: February 28, 2017 3741

DOI: 10.1021/acs.joc.7b00201 J. Org. Chem. 2017, 82, 3741−3750

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The Journal of Organic Chemistry

Figure 1. Model Buchwald−Hartwig amination reaction and overview of approach to identify functional group tolerant conditions.

synthetic methodology publications typically describe the scope of a new method and present several examples of the tolerance of certain functional groups, it is often the case that there is not enough directly comparable data in the literature to draw conclusions as to which method might work when applied to a highly functionalized substrate. Indeed, a key issue with literature mining and reaction databases is that hits are inherently enriched in older conditions, leading to the possible conclusion that newer conditions do not tolerate certain functional groups due to lack of exemplification. Furthermore, negative results are not always reported. Therefore, a systematic approach is required that compares the numerous existing conditions for a particular transformation in order to quickly identify those that are most appropriate for a new substrate and also to find and overcome gaps in the existing methodologies. Glorius and co-workers have developed a “robustness screen”7 designed to assess the scope of a given set of conditions in an unbiased manner by performing a reaction in the presence of an intermolecular functional group additive (FGA). To date, this methodology has only been applied to single reaction conditions, i.e., “Will this reaction work for my substrate?” and has not been used as a comparative tool to facilitate method selection, “Which conditions will work for my substrate?” To answer this broader question, a variant of this protocol was conceived where a large number of known conditions for a transformation could be compared on a model reaction in the presence of a series of FGAs. The results can thus be extrapolated to substrates containing the various functional groups, allowing preselection of different conditions for individual family members in a synthetic library (Figure 1). Additionally, for FGAs that are poorly tolerated across all conditions, it was envisaged that optimization of the model reaction in the presence of the FGA would allow rapid development of alternate conditions that overcome this substrate incompatibility. Therefore, for a given library, several sets of known conditions could be “tailored” for certain family members, while bespoke conditions could be sought in an expedited fashion for those library members that are deemed problematic from the initial assessment.

Screening several known reaction conditions against a panel of FGAs develops a picture of the functional groups that are inherently tolerated by each set of conditions. For those that are not well tolerated, optimization of the model reaction in the presence of the FGA generates new conditions that are expected to perform well in substrates containing those functional groups. This approach quickly generates uniform understanding of the effect of various FGAs and highlights appropriate reaction conditions for molecules containing the corresponding functional group. Limiting the initial screen to conditions known to have a broad scope of reactivity increases the likelihood of effectiveness when applied to a broad range of substrates. The Buchwald−Hartwig amination reaction exemplifies this problem well; it is a highly versatile method for the conversion of aryl and vinyl halides and pseudohalides to the corresponding amino derivatives and has become a central tool for the construction of C−N bonds in drug discovery. In a recent analysis of the medicinal chemistry literature it was shown around 6% of the reactions used in the pursuit of drug candidates were amine arylations, making it the most popular C−N bond-forming reaction after amide formation8 and one of a limited number of recently developed reaction types that is frequently used in medicinal chemistry.9 Since the early reports by Buchwald10 and Hartwig,11 the scope of this reaction continues to expand to encompass a wide variety of coupling partners, driven by the development of new ligand classes,12 deeper understanding of reactivity,12h and advances in catalyst activation.13 The success of a given amination reaction is dependent on many factors; the properties of the amine and aryl halide/pseudohalide, catalyst activation/deactivation, competing side reactions, and poisoning from low level impurities are all possible contributors to reaction performance.12h To overcome these hurdles, the nature of the catalyst, solvent, and base can be addressed, as well as concentration and reaction temperature. In spite of numerous significant advances, it remains difficult to rationally preselect conditions for application to highly functionalized substrates. A recent study of the patent literature linked the increased use of protecting groups to the rise in application of catalytic methods and also 3742

DOI: 10.1021/acs.joc.7b00201 J. Org. Chem. 2017, 82, 3741−3750

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Figure 2. Generalized high-throughput screening (HTS) protocol and summary of FGAs employed. Numbers in parentheses are the mean yield of 3 in the various amination conditions tested in the presence of that FGA (see Tables S2−S70) determined by UPLC analysis against internal standard. All reactions were performed for the length of time described in the original publication.

groups, with 17 of the top 25 best-selling small molecule drugs from 2013 containing this moiety.14 Interestingly, of the 15 worst performing FGAs in this model reaction, 11 contain the N−H moiety (average yield for the bottom 15 = 11.5%). Histogram plots (Figures S3−S97) further demonstrate the tendency for these FGAs to be clustered at the lowest end of the yield range but also facilitate the identification of conditions that are outliers and could represent good starting points for further optimization. The mechanism by which different classes of FGA prevent the desired reaction can be understood to some extent. Many additives prevent the desired reaction without forming any discernible byproducts, suggesting that catalyst poisoning or inhibition of active catalyst formation is occurring. In contrast, certain FGAs create strongly competing side reactions. Several products of potential side reactions were prepared as analytical standards to allow the quantitative assessment of these competing processes (Figure S2). Focusing on those FGAs

revealed that the Buchwald−Hartwig amination of both aryl bromides and chlorides were 2 of the 10 worst performing reactions in terms of median yield.3

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RESULTS AND DISCUSSION To combat this problem, a study was designed to assess a number of general conditions for the Buchwald−Hartwig amination reaction (Table S1) against a matrix of 47 FGAs, representing commonly occurring functional groups and heterocycles, in a high-throughput screening format (Figure 2). Across all conditions the mean yield (determined by UPLC analysis vs internal standard) for the model reaction in the absence of any FGA was 59.6%, which reflects that some conditions selected were not optimized for the chosen model reaction. A number of additive classes did not adversely affect the model reaction with average yields close to that of the control. Bioactive molecules and pharmaceuticals invariably contain hydrogen bond donors and acceptors especially N−H 3743

DOI: 10.1021/acs.joc.7b00201 J. Org. Chem. 2017, 82, 3741−3750

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The Journal of Organic Chemistry Scheme 1. Optimization of Model Reaction in the Presence of Benzenesulfonamidea

a Condition set a: Pd2(dba)3 (10 mol %), 4 (15 mol %), NaOtBu (1.4 equiv), PhMe, 110 °C. Condition set b: [(cinnamyl)PdCl]2 (1.2 mol %), 5 (10 mol %), NaOtBu (1.5 equiv), TPGS-750-M (2% in H2O), 65 °C. Condition set c: [(allyl)PdCl]2 (1.5 mol %), 6 (6 mol %), base, dioxane, 100 °C. Condition set d: 7 (3 mol %), 8 (3 mol %), NaOtBu (1.5 equiv), dioxane, 110 °C. Condition set e: 9 (3 mol %), base, solvent, 80 °C.

The approach described in Figure 1 was therefore applied to develop reaction conditions that would tolerate these functional groups. Benzenesulfonamide was selected for further study (Scheme 1) given that N−H sulfonamide groups were particularly underrepresented in the literature, with only a single example15 of the group being present as a nonreacting spectator in the various methodology papers from which our screening conditions were chosen (Table S72). The first iteration was to verify the small number of conditions that showed promise from the HTS. While the initial HTS data were obtained as single points with no repetition and on a small scale, the screening data translated well when repeated in a non-HTS setting. A few examples of reactions where the product was formed but the sulfonamide was degraded were also analyzed (see Table S71) to add certainty to this validation.16 Several conditions performed well, with the AdBippyphos and PEPPSI-IPent (Figure 3) conditions described by

that led to the lowest average yields, we confirmed that thiophenol, indole, indoline, aniline, and 2-phenylethanamine were all readily arylated under numerous reaction conditions (see Tables S2−S70). Conversely, carbazole, a byproduct of the reductive elimination in second- and third-generation Buchwald palladacycles,13d,f was rarely arylated but still had a significant detrimental effect on the yield of the model reaction (Figure S56). This is consistent with recent observations in amination reactions13g and potentially explains the relatively poor results obtained when using a third generation palladacycle (Table S57). To apply this screening data to the selection of Buchwald− Hartwig amination conditions for highly functionalized substrates, conditions could be chosen where the yield of the model reaction is high, the additive is unconsumed, and the literature suggests that the coupling partners are sterically and electronically compatible. This approach can be used to systematically evaluate the effect of a given functional group on the coupling across a wide range of conditions, but substrate-specific influences such as changes in solubility, metal chelation, steric, or electronic effects caused by other groups or by the functional group itself should also be considered when selecting conditions for application to novel targets.7a Using the Data to Generate Functional Group Tolerant Conditions. Across the broad spectrum of conditions studied, several FGAs caused significant inhibition of the model reaction and certain FGAs afforded no suitable hits whatsoever. The significant negative impact of benzenesulfonamide, benzamide, and indole (Figures S26, S44, and S52) on the performance of the majority of catalyst systems was striking, particularly given the frequency with which these substructures are encountered in medicinal chemistry efforts. There were also stark differences between certain N−Hcontaining additives and their N-methylated derivatives. Specifically, indole was far more inhibitory than N-methylindole (Figure S52 versus S68) and N-phenylacetamide was far more inhibitory than N-methyl-N-phenylacetamide (Figure S46 versus S10). In neither case could the degree of inhibition be fully explained by simple consumption of the N−H-containing additive (Figures S53 and S47).

Figure 3. Ligands and Pd complexes that were defined as hits in HTS of sulfonamide, indole, and amide FGAs. Ad = 1-adamantyl. 3744

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The Journal of Organic Chemistry Scheme 2. Optimization of Model Reaction in the Presence of Indole*

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Condition set a: Pd2(dba)3 (10 mol %), 4 (15 mol %), NaOtBu (1.4 equiv), PhMe, 110 °C. Condition set c: [(allyl)PdCl]2 (1.5 mol %), 6 (6 mol %), base, dioxane, 100 °C. Condition set e: 9 (3 mol %), base, solvent, 80 °C. aN-Arylation to form 10 competes.

Scheme 3. Optimization of Model Reaction in the Presence of N-Phenylacetamidea

*

Condition set a: Pd2(dba)3 (10 mol %), 4 (15 mol %), NaOtBu (1.4 equiv), PhMe, 110 °C. Condition set c: [(allyl)PdCl]2 (1.5 mol %), 6 (6 mol %), base, dioxane, 100 °C. Condition set e: 9 (3 mol %), base, solvent, 80 °C. aFrom HTS data without repeat.

Hartwig17 and Organ,18 respectively, giving outstanding conversion to the desired target with little degradation of the benzenesulfonamide additive. During the hit verification reactions with PEPPSI-IPent (9), it was noticed that those using 1,2-dimethoxyethane (DME) as solvent were somewhat capricious, giving variable conversions for all reactions when repeated. Upon switching from DME to 1,4-dioxane, these reactions became very efficient and reproducible (Table S71). For the second iteration, the model reaction was optimized in the presence of the FGA. Even though seemingly adequate conditions had been identified in the first iteration, the second iteration allows optimization in other dimensions, for example, selecting a base that might be more tolerant of other functional groups that could be present in potential library members. In instances where the first screening hits are less successful, this second iteration is invaluable for arriving at suitable conditions. The conditions employing AdBippyphos and PEPPSI-IPent (condition sets c and e) were selected for further study, since these conditions overlapped with successful conditions for the other FGAs under consideration here. A simple screen of commonly used bases for these coupling reactions12h showed that, for both catalyst systems, cesium carbonate, potassium tert-butoxide, and lithium hexamethyldisilazide were highly

effective bases for the model reaction with little degradation of the benzenesulfonamide additive. Similarly, optimization was performed with indole as the FGA (Scheme 2). One of the key differences between the sulfonamide and indole as an additive in this model reaction is the competing side product formation. Conditions were selected from the HTS data where the side N-arylation to form 10 was minimized. Notably, the AdBippyphos and PEPPSI-IPent conditions (condition sets c and e) from the previous screen were also high-quality starting points for indole. Further screening of bases in the second iteration showed that the AdBippyphos conditions favored the coupling of morpholine, but that coupling of indole was a significant side reaction. Interestingly, with a variety of bases PEPPSI-IPent did not afford indole arylation to an appreciable extent. A truncated set of conditions was assessed in an identical manner for N-phenylacetamide as the FGA. Conditions that had previously tolerated benzenesulfonamide and indole were selected preferentially, and further study of bases identified several conditions where the additive was tolerated and not significantly consumed (Scheme 3). When applying these data to the selection of conditions for use with medicinally interesting substrates, conditions could be individually selected for either each FGA class or a single set of conditions that is 3745

DOI: 10.1021/acs.joc.7b00201 J. Org. Chem. 2017, 82, 3741−3750

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Figure 4. Application of optimized reaction conditions to functional group containing substrates. Isolated yields, average of two runs. (a) HPLC yield vs internal standard. (b) Cs2CO3 (2 equiv), dioxane, 100 °C. (c) KOtBu (2 equiv), dioxane, 100 °C. (d) Reaction performed at room temperature. (e) Reaction performed at 30 °C.

containing the same functional group) may be due to the formation of a stable palladacycle intermediate that prevents catalyst turnover. Despite this, knowledge of the conditions that tolerate a particular functional group provides excellent starting points for focused design of follow-up experiments and more rapid development of conditions that might overcome such challenges.

effective for all, although conditions that are perhaps not optimal for any could be chosen. Following the latter of these paths, PEPPSI-IPent (9) was selected to prepare a small library of products from coupling partners containing sulfonamides, indoles, and amides (Figure 4). The catalyst was paired with lithium hexamethyldisilazide, which is precedented to show some NH tolerance19 in such couplings. Note that any of the successful hits using different catalysts, bases, and solvents could similarly have been selected (Table S71). Across a wide variety of sulfonamide-, indole-, and amidecontaining aryl bromides, very good yields of desired product were obtained in most instances, and 17 of the 18 members gave useful quantities of the target compounds. This is particularly impressive given that this library is composed entirely of substrates bearing challenging functional groups. Although optimized with a secondary alkyl amine, primary amines and aniline derivatives were also coupled effectively under these conditions. The coupling of morpholine with 4bromobenzenesulfonamide to afford 11 and the coupling of N(2-bromophenyl)acetamide to afford 24 both delivered product under the standard conditions but were hindered by limited solubility of the starting material in the reaction solvent. Performing these reactions in dioxane at higher temperature and with alternate bases resulted in substantially improved yield. Using the first pass conditions, all compounds were formed in sufficient yield to be considered as successful in a parallel synthesis setting with the exception of 17. This high success rate is in stark contrast to the 55% failure rate described for Buchwald−Hartwig couplings of functionalized substrates by the Merck group.1 One limitation of this method is that the impact of the proximity of the functional groups to the reacting centers is not predicted. For example, the low yield of 15 (relative to 11

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CONCLUSION A simple and systematic approach for identifying and optimizing reaction conditions with high functional group tolerance is described. The application to the medicinally important Buchwald−Hartwig amination demonstrates the potential of this approach for tailoring conditions to provide libraries containing desirable functional groups without the need for protecting groups. By applying such tailored conditions, an improvement in the reaction success rate can be expected with concomitant improvements in the amount of chemical space explored. Reducing the number of missed opportunities will result in diverse libraries that contain molecules with more suitable physicochemical properties and thus a higher probability of finding drug leads or candidates. This approach is equally applicable to other catalytic and noncatalytic processes and will readily generate large data sets, enabling chemists to select conditions prior to experimentation and thus access compound libraries with the properties required for biomedical research, rather than those dictated by the method of synthesis. The data can also be used to identify trends and new opportunities to improve these methods in a manner that does not require attempted application in the rarified circumstances of synthesizing a specific target. 3746

DOI: 10.1021/acs.joc.7b00201 J. Org. Chem. 2017, 82, 3741−3750

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increased. Reactions reached their target temperature within 1 min and cooled back to room temperature within 3 min upon completion. Synthesis of Compounds Prepared in Figure 4. 4Morpholinobenzenesulfonamide (11). A 20 mL microwave vial equipped with a stir bar was charged with 4-bromobenzenesulfonamide (500 mg, 2.05 mmol), Pd-PEPPSI-IPent (51 mg, 3 mol %), and cesium carbonate (1.34 g, 4.11 mmol). The vial was sealed and purged with 3× vacuum/nitrogen cycles. 1,4-Dioxane (4 mL) and morpholine (250 μL, 2.87 mmol) were then added via a syringe and the vial purged with a further 2× vacuum/nitrogen cycles. The vial was placed in a preheated aluminum block at 100 °C and stirred at this temperature for 24 h. After being cooled to room temperature, the reaction mixture was diluted with EtOAc and filtered through a plug of silica. The silica plug was rinsed with EtOAc, and the organic filtrates werecombined and concentrated in vacuo. Purification by column chromatography (gradient elution 0−90% EtOAc in heptane) yielded the desired product 11 as a yellowish white solid (run 1 = 402 mg, 81% yield; run 2 = 394 mg, 79%). Mp: 213−216 °C. 1H NMR (400 MHz, DMSO): 7.63 (d, J = 9.0 Hz, 2H), 7.06−7.02 (m, 4H), 3.75− 3.72 (m, 4H), 3.24−3.21 (m, 4H). 13C NMR (100 MHz, DMSO): 153.5, 133.8, 127.5, 114.0, 66.3, 47.7. IR (neat, cm−1): 3186, 2962, 2862, 1593. HRMS (ESI) m/z: [M+] calcd for C10H14N2O3S 242.0725, found 242.0731. N-Methyl-2-morpholinobenzenesulfonamide (12). A 20 mL microwave vial equipped with a stir bar was charged with 2-bromoN-methylbenzenesulfonamide (500 mg, 1.96 mmol) and Pd-PEPPSIIPent (50 mg, 3 mol %). The vial was sealed and purged with 3× vacuum/nitrogen cycles. LiHMDS (1 M in THF, 7 mL, 7 mmol) and morpholine (240 μL, 2.75 mmol) were then added via a syringe and the vial purged with a further 2× vacuum/nitrogen cycles. The vial was placed in a preheated aluminum block at 60 °C and stirred at this temperature for 18 h. After being cooled to room temperature, the reaction mixture was adsorbed onto silica and purified by column chromatography (gradient elution 0−5% methanol in DCM) to yield the desired product 12 as a white solid (run 1 = 480 mg, 96% yield; run 2 = 438 mg, 87%). Mp: 174−177 °C. 1H NMR (400 MHz, CDCl3): 8.03 (dd, J = 1.6, 7.8 Hz, 1H), 7.61 (td, J = 7.8, 1.6 Hz, 1H), 7.42 (dd, J = 1.0, 8.0 Hz, 1H), 7.35 (td, J = 7.6, 1.0 Hz, 1H), 5.86 (d, J = 5.1 Hz, 1H), 3.88 (d, J = 3.9 Hz, 4H), 3.07−3.05 (m, 4H), 2.52 (d, J = 5.7 Hz, 3H). 13C NMR (100 MHz, CDCl3): 150.3, 134.4, 134.0, 130.7, 126.0, 123.4, 67.7, 54.2, 29.8. IR (neat, cm−1): 3337, 3097, 2964, 1587. HRMS (ESI) m/z: [M+] calcd for C11H16N2O3S 256.0882, found 256.0887. N-(4-Morpholinophenyl)methanesulfonamide (13). A 20 mL microwave vial equipped with a stir bar was charged with N-(4bromophenyl)methanesulfonamide (400 mg, 1.58 mmol) and PdPEPPSI-IPent (39 mg, 3 mol %). The vial was sealed and purged with 3× vacuum/nitrogen cycles. LiHMDS (1 M in THF, 5.5 mL, 5.5 mmol) and morpholine (200 μL, 2.29 mmol) were then added via a syringe, and the vial was purged with a further 2× vacuum/nitrogen cycles. The mixture was then stirred at 30 °C for 66 h. After the reaction mixture was absorbed onto silica, purification by column chromatography (gradient elution 0−10% MeOH in DCM) yielded the desired product 13 as a yellow solid (run 1 = 399 mg, 99% yield; run 2 = 398 mg, 99%). Mp: 184−188 °C. 1H NMR (400 MHz, DMSO): 9.25 (s, 1H), 7.11−7.08 (m, 2H), 6.94−6.91 (m, 2H), 3.73− 3.71 (m, 4H), 3.06−3.04 (m, 4H), 2.86 (s, 3H). 13C NMR (100 MHz, MeOD): 149.4, 130.0, 123.4, 116.3, 66.5, 49.5, 37.3. IR (neat, cm−1): 3227, 2970, 2819, 2361, 1738, 1512. HRMS (ESI) m/z: [M+] calcd for C11H16N2O3S 256.0882, found 256.0884. N,N-Dimethyl-2-morpholinobenzenesulfonamide (14). A 20 mL microwave vial equipped with a stir bar was charged with 2-bromoN,N-dimethylbenzenesulfonamide (500 mg, 1.86 mmol) and PdPEPPSI-IPent (46 mg, 3 mol %). The vial was sealed and purged with 3× vacuum/nitrogen cycles. LiHMDS (1 M in THF, 6.5 mL, 6.5 mmol) and morpholine (230 μL, 2.64 mmol) were then added via a syringe, and the vial was purged with a further 2× vacuum/nitrogen cycles. The vial was placed in a preheated aluminum block at 60 °C and stirred at this temperature for 6 h. After being cooled to room temperature, the reaction mixture was adsorbed onto silica gel and

Applying this approach to other commonly used and high value transformations could have a significant impact on library synthesis by allowing the identification and development of bespoke conditions for challenging substrates in an efficient manner prior to working with the actual library members. Those functional groups that cannot be improved by varying the reaction parameters provide a foundation for future innovation in catalyst design, as chemists continue to deliver syntheses that are efficient, environmentally benign (protecting group free), and robust (i.e., tolerant of process impurities).

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EXPERIMENTAL SECTION

General Methods. All reagents were purchased from commercial suppliers and used as received. Solvents were purchased from Aldrich, anhydrous, Sure/Seal quality, and used with no further purification. The ligands and bases were purchased from commercial sources and stored in the glovebox. All HTS reactions were performed inside a Vacuum Atmospheres glovebox operating with a N2 atmosphere (oxygen typically