Analysis of Past and Present Synthetic Methodologies on Medicinal

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Analysis of Past and Present Synthetic Methodologies on Medicinal Chemistry: Where Have All the New Reactions Gone? Miniperspective Dean G. Brown*,† and Jonas Boström‡ †

AstraZeneca Neurosciences, IMED Biotech Unit, AstraZeneca R&D Boston, 141 Portland Street, Cambridge, Massachusetts 02139, United States ‡ CVMD Innovative Medicines, IMED Biotech Unit, AstraZeneca, Mölndal SE-431 83, Sweden S Supporting Information *

ABSTRACT: An analysis of chemical reactions used in current medicinal chemistry (2014), three decades ago (1984), and in natural product total synthesis has been conducted. The analysis revealed that of the current most frequently used synthetic reactions, none were discovered within the past 20 years and only two in the 1980s and 1990s (Suzuki−Miyaura and Buchwald− Hartwig). This suggests an inherent high bar of impact for new synthetic reactions in drug discovery. The most frequently used reactions were amide bond formation, Suzuki−Miyaura coupling, and SNAr reactions, most likely due to commercial availability of reagents, high chemoselectivity, and a pressure on delivery. We show that these practices result in overpopulation of certain types of molecular shapes to the exclusion of others using simple PMI plots. We hope that these results will help catalyze improvements in integration of new synthetic methodologies as well as new library design.

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INTRODUCTION In a previous paper, we examined the biases inherent in reagent selection (specifically para substituted aromatics) and concluded that at least one source for the biases in reagent selection originated from historical synthetic routes.1 The outcome of that study prompted us to examine in more detail the impact of organic synthesis on medicinal chemistry practices. For example, how long did it take for any new synthetic methodology to become a major reaction type used in drug discovery? Why are certain methodologies more favored than others, and what is the impact? It has been previously reported that the decision on the exact molecules to make and which reagents to use has a subjective nature2 and is often done based on the experience and background of individual chemists on the project. In an attempt to understand these questions, we set out to monitor frequently used synthetic methodologies in both modern and historical medicinal chemistry and also examined how these reactions were used in the step yielding final screening compounds (“production step”). We also compared this to synthetic methodologies used in natural product total synthesis schemes in order to understand both the overlap and uniqueness between the fields. The strategic and practical role of organic synthesis is critical to the success of discovering and developing new drugs. Historically, medicinal chemists were recruited for their expertise in organic synthesis (typically natural product total © 2015 American Chemical Society

synthesis) and were subsequently taught the practice of medicinal chemistry as part of an on-the-job training program. Many drugs originated from natural product origins;3 thus, the aptitude for chemists capable of retrosynthetic planning on complicated scaffolds provided a good fit in the pharmaceutical industry. As a result of this model, some discoveries of new drugs were driven by synthesis innovation and curiosity, such as the benzodiazepines in the 1950s. This important class of compounds was discovered by pursuing a design approach that was “chemically most attractive, challenging, and satisfying”.4 It is also important to highlight that legacy drug discovery programs (e.g., pre-1980s) were driven not only by chemistry but also by the implementation of in vivo testing early in the testing cascade.5 The consequences of this requirement were that it generally dictated the need for gram-quantity scales of pure material in the early discovery phase. The accessibility of commercial reagents was not the same as in the current era, and thus, more reagents and starting materials had to be prepared by individual chemists. All of this led to synthesizing and testing fewer compounds; however, these were typically made in larger amounts as compared to the modern era.1 Through the years, this model has evolved, as have the roles of a medicinal chemist. For example, organizational changes over the past decade have Received: September 11, 2015 Published: November 16, 2015 4443

DOI: 10.1021/acs.jmedchem.5b01409 J. Med. Chem. 2016, 59, 4443−4458

Journal of Medicinal Chemistry

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Another important factor in selecting the synthetic route in lead optimization is how well it scales for process chemistry to access material for clinical testing. If a project team waits too long to understand the possible issues for scale-up, significant delays can result in clinical development costing both time and money. If a team engages too early on a process development route, the medicinal chemistry strategy may change and the often-expensive scale-up efforts is thus wasted. As can be seen, the underlying reasons for the selection of synthetic schemes used in medicinal chemistry are complex and involve evaluation of both scientific and strategic components. The decision of which chemistry routes to use throughout a medicinal chemistry program have immense impact on the project timelines and cost and if done well can lead to competitive and fast moving drug discovery programs. However, if done without rigor, scrutiny, or for the wrong reasons (to keep the cascade moving), it can result in a significant waste of time and money. With that in mind, one goal with the current work was to determine and understand the most frequently used medicinal chemistry reactions and examine how this has changed over time. An important predecessor paper to this work was published by Roughley and Jordan,6 where a detailed analysis of the synthesis types used in 139 publications from three major pharmaceutical companies from the year 2008 (GSK, Pfizer, and AstraZeneca) were analyzed. The top reaction types seen in that survey were the following: (a) amide formation (16% of all reactions), (b) heterocycle formation (7.4%), (c) Narylation (6.3%), (d) CO2H deprotection (5.4%), (e) Nalkylation (5.3%), (f) reductive amination (5.3%), and (g) NBoc deprotection (4.9%). Although the methods employed between the Roughley−Jordan paper and this work are different, the top reactions generally remain the same for both studies and have largely remained the same for the past 3 decades as we will discuss below.

been made at some large pharmaceutical companies where the role of “synthesis chemist” and “medicinal chemist” has been separated into distinct job descriptions. Another major change in drug discovery models today is of course the shift in organic synthesis which is conducted “in-house” compared to within the laboratories of contract research organizations (CRO). Outsourcing synthetic chemistry has become standard operating procedure, and with it comes a unique set of concerns. Different ways of working with items such as shipping, accessibility of reagents, time-zone logistics, and synthetic capabilities all have to be settled prior to working with any CRO. Furthermore, a synthetic chemist may be assigning chemistry to a CRO they themselves have never run, which presents a very different model than that in the benzodiazepine era outlined above. For example, when a reaction fails, it may not be as easy to troubleshoot or discover “aha” moments (e.g., unexpected crystals from a long discarded reaction) compared to the legacy model of a chemistry team leader working on the same chemistry in the laboratory alongside his or her coworkers. Adding to this complicated picture, if the CRO is paid by a per-compound basis, both the CRO and the partner will need to agree on the balance of straightforward versus more difficult chemistry to pursue. Another factor that has influenced the chemistry models and reaction schemes used by medicinal chemists in the modern era has been the implementation of high-throughput assays for in vitro biology as well as in vitro absorption, distribution, metabolism, and excretion (ADME) screening. A chemistry team may feel pressure to ensure that the screening cascade is running on a regular basis and perhaps give into the influence to ensure the need to keep the cycle running with a regular stream of compounds. Large gaps where few compounds are submitted may result in a team changing their synthetic strategy in order to keep the cascade moving. Although generically this statement may seem like poor strategic decision making, (e.g., Who would not want to follow the right science and favor making the right compounds?), it may be ambiguous as to what the “right” compounds and subsequent “right” synthetic routes may be, especially at early stages of the project when structure− activity and structure−property relationships (SAR/SPR) are still emerging. There are several important factors often considered when deciding on which medicinal chemistry design route to pursue for the desired compounds. One such consideration is the convergence of the route in the preparation of the compounds. Quite often, the synthetic route chosen by the chemistry team is one in which a bulk intermediate is used to access diverse analogs in the last step (or near to the last step) of the sequence. We define this last step of a reaction as the “production step” and use that terminology throughout the manuscript. A dilemma that faces the medicinal chemistry team is when to invest in new route development and leave the established route behind for both the discovery and the process scale requirements. A lead optimization team that has a mature and robust route in place for accessing analogs in discovery may be hard-pressed to change the route for a number of reasons. If new design ideas require significant deviation from the original route, the team will weigh the pros and cons and decide if such an investment is worthwhile. If the team is successful in developing a new route, it may enable new frontiers in the medicinal chemistry landscape; however, a significant investment into new chemistry routes may also detract from routine compound submission if unsuccessful.

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METHODS A manual extraction of the literature was conducted for a representative set of papers from the Journal of Medicinal Chemistry in two separate years (1984 and 2014) of which a total of 125 papers were selected from each period. The manual extraction method provided the advantage of being able to systematically categorize each reaction using normal conventions used by synthetic chemists. (It should be noted that we were unable to find a suitable automated extraction and curation tool for this purpose; thus, the manual method was employed.) For each paper, each novel reaction type was identified and counted only once (which differs from the method used in the Roughley−Jordan publication).6 This analysis also included manuscripts from both academia and industry, which is also different from the Roughley−Jordan manuscript which focused on three large pharmaceutical companies. The papers identified for analysis were a crosssection of multiple sources and were not dominated by small numbers of companies or academic laboratories. For each publication in Journal of Medicinal Chemistry, the “production step” was identified (as best as possible), which was the step ultimately yielding final screening compounds. For natural product total synthesis papers, 30 papers were selected from 2014 to 2015 publications from both the Journal of the American Chemical Society and Angewandte Chemie, International Edition. An expanded data set of the top reactions for all categories is included in the Supporting Information. Substructure searching 4444



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Figure 1. Occurrence of a particular reaction, plotted as the percentage of which it shows up in at least one manuscript (n = 125; representative data set taken from 2014, J. Med. Chem., blue; 1985, J. Med. Chem., red). The arrows (and years) indicated the first citation of this technology in the primary literature.

coupling on activated aromatics and heteroaromatics was available, the advance of catalytic methods has greatly expanded this technology. Catalytic cross-coupling reactions have also become widely used in medicinal chemistry, with the largest category being the Suzuki−Miyaura type using palladium catalysis. The initial Suzuki paper was published in 1981;12,13 however, the impact of this work was yet to be seen in 1984 and will be discussed in detail later in the manuscript. Sonogahsira type coupling is observed in both the modern and historic data sets, with the initial publication occurring in1975.14 The remainder of the top-20 most common reaction types is for the most part from discoveries of reactions that are well-established (e.g., Grignard type related organic anion reactions, 1900, and Wittig type reactions, 1954, or the Horner−Wadsworth−Emmons variation in 1958).15−18 Two other interesting observations are noted in Figure 1. The number of amide bond forming reactions is more frequently found in 2014 (∼50%) compared to 1984 (∼25%), whereas the occurrences of heterocycles made in 2014 is less than in 1984 (∼24% vs ∼45%). This is perhaps a reflection of the trends of commercially available reagents over the years, where more functionalized heterocycles had to be prepared in 1984 compared to those that are now commercially available in 2014. Another reason is the growth of high throughput chemistry, of which amide bond reactions are more amenable than is heterocycle synthesis. Another intriguing observation from Figure 1 is the relative disproportionate use of Boc protection/deprotection chemistry employed in 1984 versus 2014. Di-tert-butyl dicarbonate was introduced in a 1976 publication19 and is described in a 1979−1980 Aldrich catalog as a “new reagent for tert-butoxy carbonylation” (and relatively inexpensive at 100 g for $45).20 It would appear that the use of Boc protection groups was slow to gain acceptance but is now one of the preferred protecting groups for amines. The most common reactions in 1984 were generally the same reactions used in 2014 with the exception of three reactions (Table 1). Decarboxylations (7.2%), Friedel−Crafts type acylation/alkylation (4.8%), and elimination of alcohols to give olefins (4.8%) made the top 20 list in 1984 but were not in the top-20 reactions in 2014 (1.6%, 0.8%, and 0.8%, respectively, details on expanded data set on 2014 and 1984 shown in Supporting Information). Since the percentages are small, it is hard to make any generalizations about the decrease

done in both IBEX and Dictionary of Natural Products was accomplished by allowing for open sites with those atoms marked with “R” or “A” in Figure 4. Principal moment of inertia calculations were done according to the published method7 and reprogrammed using IPython notebook and the OpenEye toolkits.8

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RESULTS AND DISCUSSION Most Frequent Reactions in Medicinal Chemistry, 1984 vs 2014. We first examined the frequency for which a particular transformation appeared within a subset of manuscripts of recent literature in 2014 and compared the data to 1984. The top 20 reactions from this analysis are shown in Figure 1 for both time periods. For 2014, the five most frequently occurring reactions were found to be the following: (a) amide formation, (b) SNAr reactions, (c) Boc protection/ deprotection, (d) ester hydrolysis, and (d) Suzuki−Miyaura coupling. The frequency of these reactions was similar to those found in the Roughley−Jordan paper. It was observed that many of the modern (2014) manuscripts contained a plethora of redundant reaction schemes with only minor variances (e.g., different amide coupling reagents or order of protection/ deprotection strategies, etc.), and by counting each unique reaction only once, the overall diversity of synthetic procedures could be evaluated. By use of this approach, amide bond formation was observed at least once in the majority (∼50%) of the manuscripts in the modern literature (2014). Two categories were used for amide formations, which were peptide synthesis (in cases where it employed solid-phase/automated methods, 7.2%; see Supporting Information) and all other amide-bond couplings (∼50%, Figure 1). If we had combined the two categories of amide bonds, then amide bond coupling was seen at least once in ∼60% of the 2014 manuscripts examined. Similar to the Roughley−Jordan paper, heterocycle synthesis was kept as a separate category, even though there are many methods that may lead to each individual heterocycle (e.g., condensation, aromatization, etc.). We next compared the frequency of the 2014 reactions to those in 1984 in order to understand how trends in synthesis evolved over time in medicinal chemistry (Figure 1, red bars). Only one of the top-20 reactions was unavailable in 1984 (Buchwald−Hartwig coupling). The Buchwald−Hartwig chemistry was published in 1994,9−11 and although SNAr type 4445



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other hand, one has to question why other newly developed synthetic reactions do not penetrate into the top 20. Most Frequent Production Reactions in Medicinal Chemistry, 1984 vs 2014. The analysis of the overall types of chemistry utilized in a given medicinal chemistry scheme provided us with an interesting insight into the evolution of the medicinal chemistry reactions and synthetic strategies from 1984 and 2014. However, “putting a compound in a bottle” is an often rewarding and cited key goal for many medicinal chemists, and as such, we next examined reactions used in the final step, or the “production step”. The top 20 reaction occurrences for the production step for 2014 are illustrated in Figure 2 (blue bars) and compared to 1984 (red bars). Current versus Past Use of Production Reactions. Comparison between the current and past production reactions highlights only a few differences, namely, a few modern synthetic reactions that are now employed (Suzuki−Miyaura, Buchwald−Hartwig) and have been discussed previously. One interesting difference is that phenol alkylation was not widely used as a final step production reaction in 1984 (0.1%) but was to a wider extent in 2014 (6%). Some reactions that were in the top-20 production-type reaction in 1984 but did not make the 2014 list were demethylation of phenol (7.8% in 1984 and 0% in 2014) and aromatic halogenations (3.5% in 1984 and 0% in 2014, details shown in Supporting Information). One possible explanation is that demethylation of phenol was common due to more targets in that era that favored phenols (e.g., estrogen receptors) but also more of a tolerance to phenol as a functional group in the end products (whereas in 2014 it would by many be viewed as a potential metabolic liability giving rise to glucoronidation or reactive metabolite formation). It should also be noted that we observed it to be more common in the 1984 papers to test all intermediates than it was in 2014. Thus, it is possible that some of these small variances (e.g., 3.5% aromatic halogenation in 1984) are due to more of a cultural reason for testing intermediates than a clear scientific reason, and as such, caution is placed on any overinterpretation. Reactions Rarely Used in Production Step. A comparison of the frequently occurring reactions (Figure 1) and those used in the production step (Figure 2) highlighted a number of reactions that are infrequently used in the

Table 1. Reactions Frequently Used in 1984 but Not in 2014 reaction type decarboxylation Friedel−Crafts elimination of alcohol to olefin

frequency in 1984a (%)

frequency in 2014a (%)

7.2 4.8 4.8

1.6 0.8 0.8

a

Frequency as a percentage of a given reaction type found at least once in manuscripts in 1984 and 2014 (125 representative manuscripts examined in each era).

in utility of this chemistry over the years. It is possible however that Friedel−Crafts type reactions have been replaced with cross-coupling reactions or other organometallic reagents not available in 1984. Olefin formation which might have been made via elimination chemistry is now accessible through other methods such as cross-metathesis. It is also possible that decarboxylation chemistry was a necessary step from a preferred method of carbon−carbon bond formation (e.g., βketo ester reactions) but is now replaced with more efficient and versatile procedures. However, as stated above, the low frequencies of these reactions make any generalization in that regard speculative at best. The main conclusion from the comparison between 2014 and 1984 is that only a few reactions have dropped out of the top 20 and only a small number have taken their place (e.g., Suzuki−Miyaura, Buchwald−Hartwig). In spite of all the new synthetic innovation and continual influx of synthetically trained new hires into the industry over the past 3 decades, the bar seems very high for any new synthetic methodology to significantly impact medicinal chemistry practice. This is also interesting when considered in the context of changing strategies (i.e., leaving one therapeutic area for another) and the wide spectra of target protein classes covered the past decades. In spite of all of the changes across the industry over the past 3 decades, the core reactions in 1984 are for the most part the core reactions of 2014. It may be wrong to judge this observation as good or bad for drug discovery. On one hand, new drugs have been discovered using these core reactions, so they certainly have earned their titles as top reactions. On the

Figure 2. Occurrence of a particular production reaction (or last step reaction), plotted as the percentage of which it shows up in at least one manuscript. Representative data set was taken from 1984, n = 114, and 2014 in Journal of Medicinal Chemistry, n = 118. Several manuscripts from the original n = 125 set were not used in this analysis, since the production step was not readily discernible. 4446



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of oxygen, halide, carbon, and sulfur nucleophiles used in this reaction, but none of these were used in the production step. It is possible that handling of the intermediate diazonium salt may be a safety concern to isolate and restrict the use of this chemistry. However, if it is safe enough to handle on large scale (many examples available in the manuscripts studied), then in principle it should be safe enough to handle on small scale in parallel. The lack of Grignard reactions in the production step is also somewhat surprising, since the versatility would allow for the generation of ketones, alcohols, amines, and other functional groups not formed via Suzuki−Miyaura reactions. Grignard reagents can be purchased, but their use can be perceived as inconvenient when it comes to workup, handling, and cross-reactivity with protic solvents, and as such, the need for protecting groups is often required with these reagents. The lack of Wittig and Horner−Wadsworth−Emmons type reactions could be attributed to the fact that their final product is an olefin, which often is perceived to be not “drug friendly” as a functional group (e.g., potentially susceptible to biotransformation to a reactive metabolite25 or to photoinstability26). Comparison of Medicinal Chemistry Reactions to Natural Product Synthesis and Natural Product Chemical Space. It should not be forgotten that many important scientific advances come from copying the science of Mother Nature itself. Relevant to this work, natural product synthesis is viewed by many as a critical breeding ground for new synthetic methodologies. As an example, Schindler et al. point out in a recent review that many novel reactions and reagents were discovered in the modern era of natural product synthesis by serendipity while in pursuit of a complex natural product scaffold.27 Natural products have also been the source and inspiration for many marketed drugs and therefore serve as the training ground for many aspiring medicinal chemists. With that in mind, the differences between the two practices were compared by examination of frequency of reaction type similar to that used in Figure 1. As in Figures 1 and 2, the frequency of use of a reaction in Figure 3 is not a measure of the importance of any particular reaction; it is simply a reflection of how often it is used. How often a reaction is used provides insight into the most pervasive synthetic strategies and tactics used to obtain final compounds. In the case of medicinal chemistry, these strategies reflect a propensity to make amide bonds, aryl−aryl

production step (Table 2). It may be obvious why some of these reactions are infrequently used in the productions step in Table 2. Reactions Frequently Used but Not as Frequent in Production Step reaction type phenol alkylation aromatic halogenation reduction of NO2 to NH2 ester formation diazotization Wittig (including HWE type rxn) Grignard oxidation to sulfone demethylation of phenol oxidation of alcohol reduction of double bond

frequency 2014 (any step)a

frequency 2014 (production step)a

12.8 8.8 12.0 10.4 11.2 9.6

4.1 0 0.7 2.7 0 0

4.0 5.6 5.6 10.4 7.2

0 0.7 0 0.7 0.7

a

Frequency as a percentage of a given reaction type found at least once in manuscripts in 1984 and 2014. Any step refers to the data in Figure 1, that is, a reaction type found anywhere in a manuscript. Production step refers to the last step of the sequence that gives rise to final analogs. HWE = Horner−Wadsworth−Emmons reactions.

the modern era, such as halogenation which would lead to often unpredictable chemoselectivity, and the perception of little diversity gained by halogenation of a final compound. However, it should be noted that late-stage fluorination is a popular and growing technology in medicinal chemistry with applications such as blocking site-specific metabolism and development of potential PET ligands,21,22 but little evidence was found of widespread incorporation. However, the lack of use of some of these reactions in the production step is not obvious such as phenol alkylations, Grignard reactions, and diazotizations/ functionalizations. Diazotization and subsequent functionalization reactions can lead to many diverse nucleophiles to exchange for diazonium salts (generated from the amine precursor).23 For example, Sanford et al. have published a room temperature C−H arylation of diazonium salts with wide functional group tolerability, some of which are not tolerant to other arylation reactions (e.g., oximes).24 We found examples

Figure 3. Occurrence of a particular reaction type plotted as the percentage of which it shows up in at least one medicinal chemistry manuscript (n = 125, representative data set taken from 1984 and 2014, Journal of Medicinal Chemistry) versus natural product papers (30 papers from 2014, J. Am. Chem Soc. and Angew. Chem., Int. Ed.). HWE = Horner−Wadsworth−Emmons. 4447



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types are the following (% in medicinal chemistry vs % in natural product chemistry): SNAr (29.6% vs 3.3%), Suzuki− Miyaura (22.4% vs 3.3%), electrophile reactions with amines (20% vs 0%), and reductive aminations (15.2% vs 6.6%). It was clear from the analysis that many more carbon−nitrogen (C− N) bond forming reactions occur in medicinal chemistry, which is consistent with previous reports.29 It was also evident from the analysis that the preferred method of carbon−carbon (C− C) bond formation in medicinal chemistry is through Suzuki− Miyaura coupling, but this was not observed in natural product chemistry. The top C−C bond forming type reactions in natural product chemistry were aldol, Wittig/HWE, and Grignard. However, this certainly begs the question as to what drives the use of so many Suzuki−Miyaura coupling reactions in medicinal chemistry. Is there where druglike space is most fertile, or is this done out of convenience? Natural product synthesis aims to deliver very discrete and singleton compounds, and it appears that a diversity of C−C bond forming reactions are employed. In the case of medicinal chemistry, there are often many choices of end products and perhaps many that have similar priority. If this is the case, we speculate that favor may be placed in those end products that are most amenable to reliable chemistry that can be quickly expanded in many analogs and/or have previously demonstrated activity in biological assays (e.g., substituted aromatic rings, etc.). To further probe this, we next investigated the frequency of a few common functional groups that could be obtained with the top production reactions in both medicinal chemistry patents compared to natural product chemical space. This was done by employing substructures searches on the IBEX database (6.2M records form the patent and journal literature)30 and comparing the results to a substructure search on the Dictionary of Natural Products.31 Three common functional groups are shown in Figure 4 (amides, biphenyls, and anilines), which are expected in most cases to be synthesized by three of the top productions reactions (Amide, Suzuki−Miyaura, SNAr). The differences in the frequency of amide bonds and anilines between medicinal chemistry space and natural product space are striking. Obviously amide bonds are rich in biological structures such as proteins but perhaps not so much in secondary metabolites

bonds, and amino−aryl bonds. For natural product chemistry, these strategies reflect the need to functionalize oxygen atoms, set stereocenters, and make carbon−carbon bonds. The first notable difference between the two groups was the use of asymmetric synthesis, which has been established previously.28 We made no effort to exactly quantify the use of asymmetric reactions in either medicinal chemistry or natural product literature. But a fair estimate from this data set is that approximately 90% of the natural product total synthesis papers examined utilized an asymmetric step, compared to only about 10% of the manuscripts from 2014 medicinal chemistry. Figure 3 compares the natural product literature and the 2014 medicinal chemistry data. An obvious key difference between the two data sets in our study is the number of oxygen functionalization reactions in natural product chemistry compared to medicinal chemistry (e.g., silyl protection/ deprotection, aldol, oxidations, and reduction reactions of alcohols and ketones). This observation is consistent with that reported previously by Vasilevich, where the authors concluded that C−O bond formation and C−C bond formation were more frequently used than C−N bond formation in natural product synthesis as compared to medicinal chemistry.29 It should be noted that the goals of a natural product synthesis and a medicinal chemistry scheme are generally not the same. Quite often the goal of those working on natural product syntheses is to illustrate the utility of a particular novel reaction type and often on a complex and biologically interesting scaffold. The decision of which synthetic schemes used by medicinal chemists is quite different in this regard in that the primary goal is to efficiently find new drug candidates irrespective of the innovation illustrated by the methodology. Given those two different motivations, it is expected that a different set of chemical reactions would be used. This difference is also highlighted in Table 2 where the diversity of synthetic schemes using natural product synthesis is much broader than in medicinal chemistry. For example, it only required 30 papers to achieve the same number of unique reactions as compared to 125 papers for the medicinal chemistry, whereas the data pattern is strikingly similar for 1984 and 2014 (Table 3). At first glance, it would appear that Table 3. Data Set Analysis data set

manuscripts

types of unique reactions

medicinal chemistry, 2014 medicinal chemistry, 1984 natural products

125 125 30

238 233 235

the natural product papers suffer from the same innovation gap as seen in Figures 1 and 2 in that it appeared that relatively few modern synthetic innovations are used frequently. However, it should be noted that each of these natural products contained at least one chiral center, which was quite often made by asymmetric synthesis as discussed above. In many cases the innovation and impact in a particular natural product synthesis stem from a novel application of asymmetric synthesis, but this is not the case for medicinal chemistry laboratories whose purpose is to deliver end products/screening compounds and not illustrate a new methodology. Common Reactions Found in Medicinal Chemistry but Not in Natural Product Synthesis. Among the top-20 reactions in medicinal chemistry, several reactions are not heavily utilized in natural product synthesis. These reaction

Figure 4. Occurrence of a functional group in the IBEX database (6.2M records of pharmaceutical drug discovery patents and journals)30 versus those found in the Dictionary of Natural Products (0.23M records).31 Where indicated, a nonspecific R group represents a free site at any position. As an example, THP would include any pyranose derivative found in the DNP. 4448



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Suzuki−Miyaura coupling chemistry. It should also be noted that many chemical registrations spiked around year 2000 due to HTS and combichem,1 but the Suzuki−Miyaura reactiontype increased more relative to other reaction types. For comparison purposes Figure 5b illustrates the increase in amide bond containing structures over time, which shows an approximate 2-to 3-fold increase. It should be noted that these data are a result of substructure searches and do not necessarily mean that every compound in the search was made through amide bond coupling or Suzuki−Miyaura technology (such accurate information cannot be retrieved from AZ databases currently). However, that being said, we believe that this provides a good approximation of the increase of these types of structures which are commonly made through those reaction types. It should not be concluded from this work that making biphenyl containing compounds is bad practice. In fact, there are many approved drugs that contain embedded aromatic and heteroaromatic biphenyl groups. Figure 6 provides two examples made by Suzuki−Miyaura type coupling from 199534 and a more recent example in 2014.35 Thus, biphenyl containing fragments do find themselves in known drugs and the Suzuki−Miyaura technology will continue to be an important methodology. The question we raise in this manuscript is rather does this technology experience overuse at the expense of others, which we address in the following section. Para Bias in Biphenyl Compounds and Diversity of Chemical Space. With the increase in utility of the Suzuki− Miyaura reaction in production-step chemistry, we next examined which shapes the molecules can adopt using this reaction type. To accomplish this, we utilized IBEX (a custom in-house database of 6.2M compounds from patents and journals)30 and queried the possible substitution patterns of mono- and disubstituted biphenyl substructures. In order to simplify the search, the query was divided into monosubstituted compounds and disubstituted compounds where each biphenyl was substituted only once and all other sites were substituted with hydrogens. The two sets made up ∼20% of all the biphenyl containing compounds in the IBEX data set. The results are shown in Figure 7. These results indicated that the most favored substitution pattern for monosubstituted biphenyl compounds was the para-substituted arrangement, which was 5−6 times more frequent than meta-substitution and 2−3 times more frequent than the ortho-substitution. These data indicate a strong preference for para-substitution in the simple substituted biphenyl fragments, consistent with our previous paper on para-bias. 1 We next examined disubstituted compounds in which each aromatic ring had one non-hydrogen substitution. Among the disubstituted compounds, the most common substitution patterns were the ones where at least one substituent was para, with the most frequent substitution being the para−ortho arrangement. The least frequent patterns were the ortho−ortho and meta−meta arrangements. Overall, the frequency analyses of monosubstituted and disubstituted biphenyl compounds indicate that a few substitution patterns are highly favored by medicinal chemistry while others remain relatively under-populated (Figure 7). After establishing that a disproportionate frequency of substitution patterns was observed for biphenyl containing compounds, we wished to investigate how this impacted the diversity of chemical shape space. A theoretical library was enumerated (25 × 25) for three representative biphenyl

which are of primary interest to natural product screening and synthesis. Anilines on both aromatic and heteroaromatic cores are also less frequent in the Dictionary of Natural Products than in medicinal chemistry. Biphenyl groups are found in both sets, but it needs to be pointed out that the nature of these biphenyl groups is different. Later in the manuscript, we will discuss in detail the bias or preference of medicinal chemistry in biphenyl orientations. Also included in Figure 4 for comparative purposes are a selection of oxygen containing functional groups found in high abundance in natural products (phenol, 1,3-diol, and THP) but not found in high frequency in medicinal chemistry. This serves to illustrate that there are many gaps in medicinal chemistry that could be inspired by natural-productlike fragments, perhaps complementary to library designs previously published by Waldmann et al.32 Impact of Top Production Reactions. When a chemist selects a reaction scheme to use to produce screening compounds, it is assumed that the underlying reason is to answer and address specific scientific problems (e.g., improved potency, improved ADME, etc.). There may be many methods of choice to answer a specific problem. It is reasonable to assume that selecting the simplest way (i.e., Occam’s razor)33 to test a hypothesis is often favorable among medicinal chemists (e.g., efficient reactions with high and predictable yields, chemoselectivity, accessibility of reagents to diversify in the final step, etc.).6 Although this sounds like a reasonable justification, we wondered if indeed this approach led to large libraries with many members of similar shape and overall similar properties. Our case study for this question was the Suzuki−Miyaura reaction, since it is one of the few reaction types to become a standard reaction type in the medicinal chemistry toolbox in our study. As a first line of investigation into this question, we examined the frequency of the biphenyl fragment over time in the AstraZeneca screening collection (Figure 5). For this search, biphenyl fragment with any

Figure 5. Percentage of the biphenyl fragments (a) and amides (b) incorporated into registered compounds in the AstraZeneca screening collection over time.

substitution was allowed except where it formed additional rings (e.g., which would remove compounds with 6.5.6 rings formed from methods other than Suzuki−Miyaura as examples). We observed that from the period between 1982 and 1990, the number of registered biphenyl fragments remained small and constant (2%). This number steadily grew over time, where in the modern era it constitutes ∼12% of all registered compounds, an approximate 6-fold increase in use of this fragment. This is attributed to the rise in increased use of 4449



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Figure 6. Two example known drugs with biphenyl motifs made via Suzuki−Miyaura technology.34,35

purchased or synthesized easily from known routes (generic details provided in Supporting Information). Subsequently, the principle moments of inertia (PMI)7,8 were calculated to assess the proportion of space that was occupied (linear, disk, or spherelike). The results illustrate that the two dominant substitution patterns (e.g., para−para and para−ortho) result in a high density of linear and disk shape molecules. In contrast, the underpopulated ortho−ortho substitution pattern results in a more even distribution of shapes across the triangle plot. This supports our hypothesis that in the modern era of drug discovery, if we continue to increase biphenyl containing molecules as we currently do, we will tilt the distribution toward linear and disklike populations even further. By simply making more ortho−ortho substituted compounds (which may require new synthetic methods in some cases), one can sample a wider area of PMI shape space. This example serves to point out that there may be many areas to expand chemical shape space if one were to look at both the emerging synthetic methodologies and innovative expansion to older methodologies. Arguably this may prove advantageous as the

Figure 7. Frequency population of various biphenyl regioisomers in the IBEX.30

substitution patterns shown by Figure 8. A set of reagents was selected with a diversity of R substituents which could be

Figure 8. Population analysis of representative biphenyl compounds illustrating the geometrical diversity of para−para (green), meta−para (blue), and ortho−ortho (pink) compounds. Representative sets (25 × 25 libraries) were enumerated for each scaffold, and the principal moment of inertia (PMI) was calculated. ref = reference molecules (see Supporting Information for these molecules). 4450



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Figure 9. Population analysis of representative compounds from the ChEMBL database (v18).33

pharmaceutical industry ventures into new diseases areas and new target classes which require different molecular shapes to bind and achieve the desired effect. For comparative purposes, we analyzed a random set of compounds from the ChEMBL (v18)36 database using the PMI analysis (Figure 9). This figure also illustrates that most of medicinal chemical shape space is clustered toward a more linear shape. Thus, not only does the Suzuki−Miyaura chemistry favor this shape, but it is assumed that many of the dominant reactions in Figure 1 favor this space as well. We also analyzed random compounds from 1984 and 2014 from the AstraZeneca collection (Supporting Information), and the results are also quite similar. By definition there will be a bias toward linear/disk side of the plot for any data set, since there are many more possibilities of making such shapes as compared to spherical ones. PMI plots are simplistic but serve the purpose for the current study. More elaborate calculations may be achieved by using small molecule-shape fingerprints.37 More Compounds Made Does Not Equal More Drugs to the Market. Given the rise of more commercially available reagents, chemoselective chemistry, and robust reactions such as amide bond formation, SNAr reactions, and Suzuki−Miyaura type coupling, it would be expected that the relative number of compounds made by pharmaceutical companies for respective drug programs should increase over the years per drug program. The method used to test this hypothesis is shown in Figure 10, which illustrates substances appearing in Journal of Medicinal Chemistry from 1984 to 2014 (blue line). This graph illustrates that since 1984, the number of compounds appearing over the past 30 years has increased by ∼5-fold. This is likely attributed to high throughput chemistry technologies, improvement in purification, and the heavy use of the top five production reactions mentioned above. However, when this is superimposed on the number of FDA approved drugs (green line), it becomes apparent that even though the pharmaceutical

Figure 10. Plot of number of FDA approved drugs (green) taken from the e-LEA3D drugs database,39 compared to substances in Journal of Medicinal Chemistry (×1000 in blue) from 1984 to 2014. Data were generated using SciFinder from CAS, A Division of the American Chemical Society.40

production of compound synthesis has greatly increased, the numbers of approved drugs remain the same. Previous studies have used different measures of pharmaceutical R&D investment other than increased chemistry output (e.g., dollars spent) and have arrived at the same conclusion; increased R&D investments did not increase the number of marketed new drugs.38 Our interpretation of the data in Figure 10 is the following: synthetic technology and pharmaceutical medicinal chemistry laboratory output have allowed for a substantial increase in synthesized compounds, but this has not led to an increase in marketed drugs. When this analysis is taken together with the top production reactions discussed above, as well as the population frequencies in Figure 5 and Figure 7, we conclude that the volume of chemistry within the pharmaceutical industry has greatly increased over the years, and only a few 4451



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reactions are used in high frequency which probably restricts the products that have been made. Investments into these areas of chemical space have not led to an increase in pharmaceutical productivity as measured by new drugs to the market. It should not be interpreted that these areas of chemical space are poor choices to find new drugs, as we find no evidence to support this argument. There are certainly many complicated factors that play a significant role in the output of new drugs (e.g., rules and regulations, payers and pricing, differentiation from current therapies, etc.). Synthetic chemistry is just one piece of this puzzle. However, it is a fair question to challenge whether or not such a substantial investment in these areas fully exploits the medicinal chemist’s toolbox and if coverage of a more diverse chemical space would provide new and different opportunities to face the emerging targets of the pharmaceutical industry at present. It should not be forgotten that the medicinal chemistry toolbox includes computational tools to make better compounds faster as well.

Figure 11. Historical evolution of boron-based cross-coupling partners.

through hydroboration to render alkyl boronate esters, thus adding much greater flexibility and diversity in reagent choice. Advances in potassium trifluoroborate salts also offer several advantages over boronic acid nucleophiles, most notably an increased stability and chemoselectivity for alkyl-based coupling partners.49,50 Many trifluoroborate salts are also now commercially available. Also, the introduction of MIDAboronates (now commercially available as well) offers the unique opportunity to employ iterative cross-coupling reactions, modeled closely to automatic iterative peptide coupling processes.51,52 Outside of synthetic innovation, technology improvements within synthetic chemistry have also played an important role, such as laboratory automation, microwave heating,53 and the routine incorporation of high-throughput and chiral chromatography which have led to faster and better routes to the end products.54,55 Chiral supercritical fluid chromatography (SFC) may serve as an illustrative example. Several reaction schemes examined in this study targeted the racemic compounds but then relied on chiral SFC for the final separation. Very few asymmetric reactions were identified in our analysis of Journal of Medicinal Chemistry manuscripts in order to obtain end products, perhaps because the chiral SFC would allow access to all stereoisomers upon a successful separation. Aside from improvements on established chemical transformations (amide bond coupling, Suzuki coupling) and technology development (microwaves and chromatography columns), incorporation of new synthetic methodologies (e.g., found past the year 2000) was also observed in our analysis, albeit with much less frequency as those reactions in Figure 1 (e.g., 238 in our sample), but many of these are not used very frequently or at all in the last diversification step. It appears that we are only tapping into a limited number of available synthetic methodologies and new horizons for these methodologies are waiting to be found.

lation). In a recent example where complex synthetic organic chemistry and biological need intersect in this fashion, Boger and colleagues have published synthetic routes to novel analogs of vancomycin that demonstrate superiority against vancomycin resistant strains.70 What is notable in this paper is also that the late stage transformations are done without protecting groups on a relatively synthetically accessible intermediate, thus highlighting that practical solutions to the problem of protecting group manipulation can be identified for complex structures. Also of interest is the use of bioorganic transformations on late stage compounds, which may indeed point to the next transformation in organic chemistry that fits the needs outlined above (e.g., biocatalysis that can tolerate polar functionality and chemical diversity). Other important papers in the field should also be noted which stress the potential impact of protecting-group free chemistry on complex natural products.71,72 Indeed a heavy reliance on protecting group strategies exists in both medicinal chemistry (where Boc protection was the most widely used) and natural product synthesis (where silyl protecting groups were the most widely used). Future development of reagents and conditions that are mild, chemoselective, and tolerable to a wide array of functional groups will certainly have a significant impact in both fields and transform the current practices. Others have tackled the problem of synthesis innovation in industry with initiatives focused on developing practical applications of new synthetic methodology in collaboration with academia. In a recent article by GSK, the authors analyzed the reaction types used in array chemistry within GSK Centres of Excellence for Drug Discovery (CEDDs).73 The authors concluded (similar to our findings) that medicinal chemists are only tapping into a small amount of synthetic procedures, mainly due to time required to explore new reaction conditions versus the value of any given target that can be made. As a consequence of this study and others, GSK initiated collaborative relationships with the Engineering and Physical Sciences Research Council academia in order to expand the diversity scope of chemistry used in array chemistry. The authors point out that academia and industry have diverging interests, and one significant challenge of collaborations of this type is to “marry the pure research perspective of academia with the applied research expertise of industry to genuinely add new robust reactions to those available to medicinal chemists”. The solution to the challenges of medicinal chemists was also recently highlighted by Nussmaumer where he stated “the appreciation and promotion of synthetic chemistry expertise in drug discovery: complex chemistry should not be excluded, and close collaboration with synthesis experts should be encouraged.”74 It is not only the collaboration with synthesis experts but also with compound suppliers. A recent study claimed that technology innovations might lead to the end of synthesis,75,76 demonstrating that multiple unique classes of small molecules can be made using the same fully automated process (including the elusive C−C bond forming reactions with commercially available building blocks). The authors of this work stressed that the technology aimed to put the “emphasis back where it belongs, on richly diverse natural-product, natural-product-like, and druglike molecules,” highlighting the gap in current medicinal chemistry toolboxes and reinforcing the drumbeat of “more natural product chemistry”. While this paper may have been somewhat deliberately provocative, it has challenged those in the field to question whether or not this reality may come to bear. Do

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CONCLUSIONS We have found that a limited number of reactions dominate the chemical landscape of modern medicinal chemistry based on an analysis of the medicinal chemistry literature at two time points (1984 and 2014). The most common reactions used in 1984 are still used in 2014, with a few exceptions (increase of Suzuki−Miyaura chemistry over the years, increase in amide bond formations, and decrease in heterocyclic synthesis). Impact (as gauged by frequency of use) is slow to occur for many recent innovative chemistry breakthroughs such as ringclosing metathesis, C−H bond activation, selective fluorination, biocatalysis, etc. However, this is only one measure of impact. If indeed an important biologically active molecule was synthesized or a route significantly improved with any of these methods that would not have been made in a previous era, then this alone is an impact in itself. Overall it appears that a few reactions in medicinal chemistry laboratories are very heavily used at the expense of others. As a result, some areas in “chemical space” (e.g., products from Suzuki−Miyaura coupling, amide formation) are densely occupied with structurally similar compounds. As an explicit example, we have shown a bias toward para−para and ortho−para biphenylic substitutions and highlight that such molecules will be shape similar according to simple PMI calculations. Much has been made recently about the need to shift away from sp2like molecules or to venture into new chemical modalities such as macrocycles in order to tackle the new era of medicinal chemistry drug targets. We recognize the merits of chemical novelty and new scaffolds for many reasons (e.g., differentiation from competition as perhaps the most obvious) and believe that much can be done to improve the outlook. We provide three recommendations from our findings: (a) identify more expedient ways that modern synthetic methodologies can impact medicinal chemistry, (b) expand the current arsenal of tools to access less populated space independent of the novelty of reaction type (e.g., careful consideration of holes in chemical space such as more Suzuki−Miyaura couplings covering ortho− ortho space), and (c) educating medicinal chemists who are new to the field to have a strong rationale behind almost all designed compounds and selecting the most appropriate routes, not the most expedient routes. That said, autonomy, innovation, and creativity are all, without a doubt, important factors to succeed in the difficult trade of drug discovery, where serendipity is known to play a role.77 On top of all this, integration of computational methods can be a powerful way to aid the medicinal chemist in drug design. In doing so, it will allow for the creation of corporate and commercial collections which should serve as a source for many different projects and targets. A limited arsenal of medicinal chemistry reactions may narrow the available chemistry space to structurally similar compounds which spill over to perhaps (unwanted) biased 4455



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screening collections. The increased availability of commercial reagents for these reaction types and the chemoselectivity amplifies the bias for these reactions. Metaphorically speaking, it appears that the current practice of medicinal chemistry is placing heavy bets on only a few spaces on the roulette wheel, whereas other spaces remain untouched. The lack of expansion into these spaces comes perhaps without sufficient justification other than the perception that it may be harder to populate with large numbers of compounds. Perhaps a jackpot is in store for these heavy bets. However, those who might venture a wager on a different space may find themselves walking away from the table as a single winner without having to share their winnings with all others at the table.

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applications in medicinal chemistry and drug design, including granted patents on clinical candidates. Jonas Boström is an Associate Professor at the University of Gothenburg (Sweden), currently holding a Principal Scientist position at AstraZeneca in the CVMD iMed. He obtained a M.S. in Chemistry at the University of Gothenburg in 1996 and a Ph.D. in Computational Medicinal Chemistry in 2000 at the Royal Danish School of Pharmacy (Copenhagen, Denmark). After a short spell at H. Lundbeck A/S he joined AstraZeneca. Jonas has gained knowledge of most aspects of preclinical drug discovery from his 15 years in the pharmaceutical industry. Among other things, this has resulted in 15 patent specifications, including 10 candidate drugs. Current research interest includes combining new technology, informatics, and science in innovative ways to tackle the challenging tasks in drug discovery.

GENERAL EXPERIMENTAL SECTION

Data extraction from journals was done manually (n = 125 per year and categorized into reaction types. (See Supporting Information for expanded data sets.) Each reaction type was counted only once per manuscript to give an overall frequency score represented in Figures 1−3. For Figure 2, the production step was considered as the step that led to the final test compounds. A few manuscripts were left out where this could not be easily identified; thus, for 1984, n = 114, and for 2014 n = 118. The IBEX database was employed as previously described using substructure searhcing.1 PMI calculations involved using the methods described previously by Sauer and Schwarz.7,8 The public portal online version of Dictionary of Natural Products was used with substructure searching features, and the counts of numbers of molecules found were tabulated. Analysis of compounds published in Journal of Medicinal Chemistry was taken from SciFinder40 by setting a search query to Journal of Medicinal Chemistry and by unique volume number and then collecting the tally of unique compounds.

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ACKNOWLEDGMENTS

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ABBREVIATIONS USED

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REFERENCES

The authors thank Mark Duggan and Peter Bernstein for valuable discussions.

9-BBN, 9-borabicyclo[3.3.1.]nonane; AZ, AstraZeneca; Boc, tert-butoxycarbonyl; ADME, absorption, distribution, metabolism, and excretion; B2Pin2, bis(pinacolato)diboron; CRO, contract research organization; HWE, Horner−Wadsworth− Emmons; MIDA, N-methyliminodiacetic acid; PET, photoelectron transfer; PMI, principle moment of inertia; SAR, structure−activity relationship; SPR, structure−property relationship

ASSOCIATED CONTENT

S Supporting Information *

(1) Brown, D. G.; Gagnon, M. M.; Boström, J. Understanding our love affair with p-chlorophenyl: present day implications from historical biases of reagent selection. J. Med. Chem. 2015, 58, 2390− 2405. (2) Lajiness, M. S.; Maggiora, G. M.; Shanmugasundaram, V. Assessment of consistency of medicinal chemists in reviewing sets of compounds. J. Med. Chem. 2004, 47, 4891−4896. (3) Sternbach, L. H. The benzodiazepine story. J. Med. Chem. 1979, 22, 1−6. (4) Patridge, E.; Gareiss, P.; Kinch, M. S.; Hoyer, D. An analysis of FDA-approved drugs: natural products and their derivatives. Drug Discovery Today 2015, DOI: 10.1016/j.drudis.2015.01.009. (5) Lombardino, J. G.; Lowe, J. A., III. The role of the medicinal chemist in drug discovery − then and now. Nat. Rev. Drug Discovery 2004, 3, 853−862. (6) Roughley, S. D.; Jordan, A. M. The medicinal chemist’s toolbox: an analysis of reactions used in the pursuit of drug candidates. J. Med. Chem. 2011, 54, 3451−3479. (7) Sauer, W. H. B.; Schwarz, M. K. Molecular shape diversity of combinatorial libraries: a prerequisite for broad diversity. J. Chem. Inf. Model. 2003, 43, 987−1003. (8) OEChem Toolkits. http://www.eyesopen.com/oechem-tk (accessed Sep 9, 2015). (9) Paul, F.; Patt, J.; Hartwig, J. F. Palladium-catalyzed formation of carbon-nitrogen bonds. Reaction intermediates and catalyst improvements in the hetero cross-coupling of aryl halides and tin amides. J. Am. Chem. Soc. 1994, 116, 5969−5970. (10) Guram, A. S.; Buchwald, S. L. Palladium-catalyzed aromatic aminations with in situ generated aminostannanes. J. Am. Chem. Soc. 1994, 116, 7901−7902. (11) Guram, A. S.; Rennels, R. A.; Buchwald, S. L. A simple catalytic method for the conversion of aryl bromides to arylamines. Angew. Chem., Int. Ed. Engl. 1995, 34, 1348−1350.

The Supporting Information is available. . The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jmedchem.5b01409. Manuscripts and classifications of reactions, expanded PMI plots for biphenyls, and libraries used for Figure 8 (PDF)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: 484-639-4153. Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest. Biographies Dean G. Brown is currently Director of Discovery and Preclinical Sciences at AstraZeneca within the Neurosciences group. He obtained a B.S. in Chemistry at Abilene Christian University (Abilene, TX) and a Ph.D at the University of Minnesota (Minneapolis) in Organic Chemistry. He has over 18 years experience in the industry with AstraZeneca. Dean has been responsible for building many new scientific programs in both neuroscience and infection, several of which have resulted in successful transition to clinical trials. His scientific interests are in lead generation, library design, synthetic chemistry, and applications of computational chemistry. Dean is listed as an author or coauthor on more than 40 publications and patent 4456



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