Structure-based macrocycle design in small-molecule drug discovery

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Structure-based macrocycle design in small-molecule drug discovery and simple metrics to identify opportunities for macrocyclization of small-molecule ligands Maxwell D. Cummings, and Sivakumar Sekharan J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jmedchem.8b01985 • Publication Date (Web): 12 Mar 2019 Downloaded from http://pubs.acs.org on March 12, 2019

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Journal of Medicinal Chemistry

Structure-based macrocycle design in small-molecule drug discovery and simple metrics to identify opportunities for macrocyclization of smallmolecule ligands

Maxwell D. Cummings*,† and Sivakumar Sekharan‡

Abstract Interest is growing in the use of macrocycles in pharmaceutical discovery. Macrocylization may provide a gateway to an expanded chemical space for smallmolecule drug discovery, and this could be beneficial in prosecuting difficult targets, e.g protein-protein interactions. Most, but not all, macrocycle drugs are derived from natural products. Studies on synthetic drug-like small-molecule macrocycles are limited, and our current perspective on macrocycle drugs is similarly limited. Following some background discussion, we review several examples of the structure-based design of synthetic macrocycles. Our perspective is that in conformationally suitable systems macrocycles are an analog class worthy of consideration. We then summarize an approach for the initial evaluation of molecules as candidates for macrocyclization.

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Section 1: Introduction The field of macrocycle drugs has emerged as a distinct area of interest for pharmaceutical researchers. Recent reviews covering known macrocycle drugs have fostered the idea that this promising molecular class is underexploited in drug discovery and worthy of further attention.1-5 One developing theme in the field is that standard small-molecule oral drug property rules (eg. Lipinski’s rule of five6) are somewhat relaxed (or modified) for macrocycle drugs, with these molecules residing in a “beyond rule of five” region of chemical space.1-5, 7 The apparent attractiveness of macrocyclic small-molecule drugs stems, at least in part, from the alluring idea that macrocycles represent an opportunity to find and develop smallmolecule drugs with properties well outside the conventional conception of druglikeness. This inarguably tantalizing idea is not entirely unfounded, but much work remains to adequately explore this whole area of drug science.

Contemporaneous with this ongoing coalescence of the field of “macrocycle drugs,” drug discovery scientists are being challenged by the new class of drug targets known as protein-protein interactions. Protein-protein interaction (PPI) targets for drug discovery are distinct from the classical enzyme-substrate or receptor-ligand interactions most typically targeted by small-molecule chemotherapeutics. While there are notable exceptions (eg. p53-HDM28), the 2 ACS Paragon Plus Environment

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interaction sites of PPI partners typically do not include the relatively small and concave surface pockets commonly observed for proteins that have evolved to bind natural small-molecules and that are exploited by many small-molecule drugs.9-11 Overall, this new class of protein targets appears to be less druggable when viewed in the light of “classical” small-molecule drug discovery. Although published data supportive of this contention seems (understandably) sparse, the success rate of screening small-molecule compound collections against these new targets may be lower than for more conventional targets.9-11 Nevertheless, biology implicates a growing number of PPIs as worthy targets for chemotherapeutic intervention, based on key roles in metabolism and/or disease.9, 10, 12 As this compelling yet challenging target class expands and matures, pharmaceutical researchers are exploring new molecular strategies for drug discovery aimed at these targets.

One developing theme of PPI-targeted drug discovery is that, because the protein interaction sites are large and lack clearly defined binding pockets, small-molecule ligands must be larger (eg. MW >500) to achieve affinity levels commensurate with therapeutic efficacy.1, 5, 13 Recent drug discovery examples in the PPI area encourage this thinking (eg. BCL-214). Driven in part, perhaps, by the stapled peptide macrocycles targeted at MDM2-p53, peptide-based drug discovery has also begun to expand its niche in small-molecule drug discovery. At the same 3 ACS Paragon Plus Environment


time, experience with “classical” targets (eg. HCV protease, HIV protease) also supports the contention that generic physicochemical property rules for oral drug discovery (eg. Lipinski’s rule of five6) offer some latitude15 . For better or worse,16 we have come to expect that some larger small-molecules are developable as oral drugs.

As “larger small-molecules” with some precedent of effectiveness in human therapeutics, macrocycles may have a role to play in this milieu - there is some theoretical underpinning to this assertion. Jacobson, Lokey and colleagues were groundbreakers in this area. Their computational and structural studies with cyclic peptides indicated that membrane permeability could be facilitated by conformational shifts involving significant changes in the chemical nature of the exposed surface of the peptides.17, 18 Such shifts were shown to be dependent on intramolecular transannular hydrogen bonds for these cyclic peptides. Other groups extended these ideas to broader analyses of small-molecules in druglike and beyond rule of five chemical space, including macrocycles. Kuhn et al.19 explored intramolecular hydrogen bonding in small-molecule drugs, and Alex et al.20 later extended this to beyond rule of five chemical space. More recently, Whitty and colleagues formalized the conformation/property shift phenomenon with the term “chameleonic behavior” as a guiding principle for molecular design in the 4 ACS Paragon Plus Environment

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macrocycle and beyond rule of five chemical space.21 Kihlberg et al. has also explored molecular properties of macrocycles and beyond rule of five smallmolecules,2, 22 and one of us collaborated with Kihlberg’s group on a study of the application of conformational analysis tools in conjunction with macrocycle property calculations.23 Still, much remains to be learned about the effects of macrocyclization on pharmaceutically relevant properties of small-molecules. Macrocyclization can have profound effects on the conformational space accessible to a molecule, serving to both lock in and lock out conformations. It is becoming increasingly apparent that the resultant reduced flexibility, altered molecular shape(s) and modified surface properties can impact pharmaceutically relevant properties (eg. stability, both on- and off-target binding affinity, membrane permeability) in many systems.

Our perspective is that several current areas of activity in drug discovery research converge on macrocycles. First, an apparently vast new class of therapeutic targets, protein-protein interactions, is emerging. It is accepted, justifiably or not, that oral small-molecule effectors for these targets may have to be larger and less “drug-like” than historical oral small-molecule drugs. Macrocyclization is one strategy that may be useful in improving the pharmaceutical properties of a larger small-molecule, thereby facilitating oral administration. Second, peptides are 5 ACS Paragon Plus Environment


obvious starting points for many target-based discovery efforts, and peptides are undergoing somewhat of a renaissance in small-molecule drug discovery.24 Peptides do, unfortunately, suffer from some drug developability challenges; one strategy applied in peptide-based drug discovery is peptide cyclization, leading to macrocyclic peptides.25, 26 Third, property analyses have shown that “beyond rule of five” “chemical space” is real and useful in drug development, and macrocyclization appears to be useful in exploiting this expanded space. Finally, recent analyses of approved drugs shows that oral drugs that lie outside typical rule of five bounds are enriched in macrocycles.1 Also noteworthy in this context, although beyond the scope of the present brief perspective, are technological advances in ring-closing metathesis chemistry,27, 28 a methodology that is fundamentally enabling in macrocycle synthesis.

Section 2: The origins of macrocycle drugs Besides containing macrocycles, to what chemical classes do macrocycle drugs belong? Where did current macrocycle drugs and drug candidates come from? How were they discovered? Whatever a “typical” or “normal” drug discovery process is, can it lead to a macrocycle drug? Since macrocycles are often discussed as a single chemotype in the context of drug discovery, and are 6 ACS Paragon Plus Environment

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considered attractive for some new protein targets, it seems reasonable to ponder thus as we seek to discover new macrocycle drugs.

A recent survey lists 68 marketed macrocycle drugs and 35 macrocycles in clinical development.2 Most of these molecules are either macrolides or cyclic peptides. Natural products of these and other chemical classes have traditionally been discovered through the application of iterative bioassay-guided fractionation of natural materials (eg. soil, plants),29, 30 ultimately arriving at the identification of a pure compound. Natural products are structurally distinct from synthetic smallmolecule drugs and small-molecule drug candidates, tending, for example, to contain more chiral centers and to be relatively oxygen rich and sulfur poor. 5, 29, 3138

The discovery path for a natural product-based drug is likewise distinct from

that of synthetic small-molecule drugs. Grasping this etiological difference seems apropos, as pharmaceutical researchers study current macrocycle drugs and seek new ones.

In the natural product-based drug discovery paradigm,29, 30 molecular structure is not a direct consideration during the initial hit or lead identification phase of drug discovery. Some focus or direction with respect to chemical structure may derive 7 ACS Paragon Plus Environment


from screening extracts from selected eg. species or locations, but the unknown active molecular species may be simple or complex. When a natural product-based program culminates in an approved drug, the final drug molecule is typically a component of the initial screening hit, or a very close analog of the active component of the initial screening hit mixture.

In the medicinal-chemistry-based drug discovery paradigm, early stage hit or lead identification is applied to known chemical matter, eg. a corporate compound collection, and the molecules being screened are pure and fully or largely characterized (chemically) in advance. When a medicinal chemistry-based drug discovery program culminates in an approved drug, the final drug is often chemically distant from the initial screening hit or lead, as hundreds to thousands of molecular analogs are designed, synthesized and tested on the optimization path from initial hit to final drug.

Natural products are often larger and typically are more complex (see above) than “drug-like” small-molecule drugs. Generally, the synthesis of natural products is more difficult than that of synthetic drug-like small-molecules.31 “Analoging” around a hit or lead, fundamental to modern medicinal chemistry-based drug 8 ACS Paragon Plus Environment

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discovery, is likely to be impractical if not essentially impossible with a natural product lead. Despite these challenges, the importance of natural products to human health and drug discovery cannot be overstated. Pharmaceuticals and drug discovery are rooted in natural products – historically, most drugs can be traced to a natural product origin.29, 34, 36 While there frequently is still a strong connection between new drugs and their natural product origin or inspiration, in recent times modern synthetic chemistry has usurped nature as the primary source of new leads for drug discovery.30, 32, 34, 39 In many settings, unless they are exquisitely potent, natural products or natural product-like molecules are likely to be de-prioritized when they arise as hits in a screening campaign (for reasons including excessive MW and synthetic accessibility). Thus, current pharmaceutical discovery efforts are largely focused on approaches that seem exclusive of the paradigm that has generated most known macrocycle drugs.

A small subset of the macrocyclic molecules reviewed by Kihlberg and colleagues,2 are described as “de novo designed” molecules. Unlike smallmolecule macrocycle drugs with natural product origins, these synthetic molecules arose from relatively recent medicinal chemistry-based drug discovery efforts, familiar to most drug hunters currently working in pharmaceutical discovery. In this traditional paradigm, iterative medicinal chemistry-based “analoging” can 9 ACS Paragon Plus Environment


include macrocyclization directed toward discovering a molecule with optimal properties for the intended therapeutic application.

In the following section we review examples of the rational design of smallmolecule macrocycles. In these cases, macrocyclization arose as a plausible route to addressing one or more drug development hurdles, and ultimately proved successful in advancing compounds toward clinical evaluation.

Section 3: Structure-based design of small-molecule macrocycles - Example 1: HCV protease Treatment of HCV infection has improved dramatically in the past several years. Five small-molecule inhibitors of the NS3 protease have been approved as drugs since 2011, and three of these are macrocyclic small-molecules. This recent advance for HCV patients is a striking example of designed macrocycles having great positive impact on human life. Retrospectively, the story of the early days HCV NS3 protease inhibitor-based drug discovery is enlightening, and relevant to both peptide-based discovery and macrocycles.


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Researchers from Boehringer Ingelheim have described their early work on HCV NS3 protease drug discovery, arriving at a macrocyclic tetrapeptide inhibitor that subsequently served as molecular template for many other research groups.40-42 This design process began with the observation that hydrolysis products of selected peptide substrates acted as inhibitors of the NS3 protease. Peptide truncation studies, depeptidization through incorporation of non-natural amino acids and elaboration of sidechains with synthetic substituents gave potent inhibitors. Unfortunately these molecules were limited by poor biopharmaceutical properties, consistently lacking activity in cell-based assays. NMR- and computational chemistry-guided structural studies led to additional depeptidization strategies, among them rigidification through macrocyclization. Emerging from a clear and rational structure-based foundation, macrocyclization proved to be an important molecular design advance in this peptide-based drug discovery effort.

During the course of their program to optimize a substrate-based inhibitor of HCV NS3 protease into a drug, the Boehringer Ingelheim group applied NMR studies to understand peptide rigidification upon binding to the protease. One result of this work42 was the observation of the close proximity of two sidechains of a peptide inhibitor when bound to the protease. (While they are not the molecules studied in the original work from the Boehringer Ingelheim group, the comparison of two 11 ACS Paragon Plus Environment


NS3 protease-bound inhibitors in Figure 1 highlights this feature.) Previous studies from the Fairlie group on peptide macrocycles had provided structural insights and guidelines on macrocyclization of protease substrates,43 and application of this approach led the Boehringer Ingelheim group to the discovery of a macrocyclic variant of their peptide-based scaffold.41 Some of the initial macrocyclic inhibitors arising from this effort maintained and in some cases showed slightly improved enzyme inhibition. Most importantly, a subset of these macrocycles were the first NS3 protease inhibitors to show antiviral activity in the cell-based replicon assay.42

Figure 1. Overlay of HCV NS3 protease-bound inhibitors shows the alkyl macrocycle linker of Simeprevir (orange color-by-atom) occupying the region 12 ACS Paragon Plus Environment

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between the two alkyl sidechain moieties of Boceprevir (green color-by-atom), similar to the original observation40-42 that initiated research into macrocyclic inhibitors of NS3 protease (see text for discussion); overlay based solely on protein atoms (not shown) from the complex structures (Simeprevir PDB ID 3KEE44; Boceprevir PDB ID 3LOX45).

These early studies paved the way for the subsequent extensive research into macrocyclic inhibitors of HCV NS3 protease. As the HCV protease inhibitor field matured, both the initial and later alternative macrocyclization schemes were employed with peptide-based molecules by many pharmaceutical industry discovery groups,46-53 eventually leading to the discovery of several FDAapproved drugs. Efforts at Janssen (initiated at Tibotec, in collaboration with Medivir) in this area led to the discovery of Simeprevir, the first macrocyclic NS3 inhibitor to be approved by the FDA for HCV therapy (Figure 1).54-56

Macrocyclization has been explored as a drug design strategy for other proteases. James and colleagues studied the entropic effect of macrocyclization on a peptide inhibitor of the aspartic protease penicillopepsin, concluding that partial rigidification was responsible for a significant enhancement in inhibitor potency.57 13 ACS Paragon Plus Environment


Fairlie and colleagues have been pioneers on many fronts in this field, and have reviewed protease crystal structures and macrocyclic peptide inhibitors of proteases.43, 58 These reports highlight how macrocyclization can enforce the extended conformation required for peptide binding in protease active sites. Thus, macrocyclization seems suited to broad application in peptide-based proteasetargeted drug discovery (see also e.g. Table 1).

Section 3: Structure-based design of small-molecule macrocycles - Example 2: Kinase inhibitors Kinase inhibitor-based small-molecule drug discovery emerged in the late 1980s and has since been a consistently active and productive area of drug discovery, yielding more than two dozen FDA-approved drugs59 and a wealth of scientific literature. The three-dimensional structures of kinase-inhibitor complexes have been extensively studied and thoroughly reviewed.60-63 Given the level of activity in the kinase field and the recent interest in macrocycles in drug discovery, it is perhaps not surprising that macrocyclization has found application in the kinase inhibitor field. However, as one of us noted in a recent publication,64 an in-depth analysis of kinase inhibitor binding modes and macrocyclization is unprecedented. Specifically, the U-shaped binding mode frequently observed for kinase inhibitors 14 ACS Paragon Plus Environment

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has not been widely recognized as a general phenomenon with broad applicability to the design of macrocyclic small-molecule kinase inhibitors.

A recent survey listed four macrocyclic kinase inhibitors in clinical development, including the JAK2/FLT3 inhibitor Pacritinib.2 Here we briefly summarize some aspects of Pacritinib macrocycle design, and note a few additional kinase systems that illustrate the applicability of macrocyclization to kinase inhibitor-based drug discovery.

Figure 2. Overall macrocycle design strategy that led to the discovery of Pacritinib. A modification of the TOC figure and Figure 1 from ref.65 Reproduced with permission from Journal of Medicinal Chemistry. Copyright 2012 American Chemical Society.



In discovering Pacritinib, William and colleagues initiated their effort with a phenylaminopyrimidine screening hit that showed a promising kinase activity profile. They noted the congested patent space around this chemotype, a potentially prohibitive issue at the early stage of a drug discovery effort.65 To address this challenge, a combination of modeling with available 3D structures of kinase-inhibitor complexes, small-molecule conformational analysis and automated docking results led to a macrocyclization design scheme (Figure 2). While not explicitly described as a “U-shaped conformation,” in this design work William and colleagues exploited the U-shaped conformation predicted for their initial phenylaminopyrimidine screening hit in their subsequent macrocycle designs (Figure 2). Pursuit of this general approach proved fruitful, yielding multiple clinical candidates. Macrocycle linker characteristics including length, chemical nature and rigidity were all shown to be relevant to both kinase affinity and selectivity, and also allowed modulation of cLogP. Exocyclic substituents on a macrocycle linker heteroatom were also useful in modulating kinase affinity and selectivity, as well as affecting cLogP and solubility.65, 66

Johnson and colleagues at Pfizer described their work on ALK inhibitors, with the crystal structure of a non-macrocyclic inhibitor complex providing a foundation for macrocycle design.67 These authors explicitly noted that bound linear inhibitors 16 ACS Paragon Plus Environment

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adopted a U-shaped conformation, positioning the two terminal inhibitor moieties in close proximity to each other. As with the Pacritinib study, the macrocycle linker was useful in modulating both kinase affinity and selectivity, and CNS availability was also modulated by linker variation. Notably, lipophilic efficiency was a critical metric during compound optimization.67 This effort led to the discovery of a clinical candidate with improved kinase selectivity, enhanced resistance and ADME profiles as well as the desired CNS availability.68 This designed macrocyclic kinase inhibitor, lorlatinib, was recently approved by the U.S. FDA for second- or third-line treatment of (ALK)-positive metastatic nonsmall cell lung cancer.69 ,

In describing a complex with the spleen tyrosine kinase Syk, the authors observed that bound imatinib (Gleevec) adopts a relatively compact “U-shaped” or “cis” conformation, in contrast to the more extended conformation observed originally in the Abl complex.70 A U-shaped conformation was also observed for a covalent analog of imatinib bound to JNK3.71

Overall, then, some small-molecule kinase inhibitors have been observed to adopt a U-shaped conformation when bound at the kinase hinge region. This specific 17 ACS Paragon Plus Environment


shape feature has been exploited for designing purely synthetic macrocyclic kinase inhibitors. These observations have been strictly isolated, on a case-by-case basis. Prior to a recent publication from one of us,64 it has not previously been formally recognized that this phenomenon may be general and represent a foundation for a broadly applicable kinase inhibitor design approach. Results reported to date for designed macrocyclic kinase inhibitors establish that such molecules can offer advantages in the areas of kinase affinity and selectivity, ADME properties, CNS availability and patentability. Thus, macrocyclic analogs of synthetic smallmolecule kinase inhibitors represent a viable approach for kinase inhibitor-based drug discovery.

Section 3: Structure-based design of small-molecule macrocycles - Example 3: HCV polymerase In the early-to-mid 2000’s research into hepatitis C viral proteins surged, as direct acting antiviral agents for HCV therapy gained interest. As part of a multi-faceted drug discovery effort targeting HCV, our group at Tibotec (now Janssen) explored inhibitors of the viral polymerase enzyme. At the time this protein was being intensively studied as a target for HCV therapy, and various data had established the presence of multiple druggable allosteric sites on the viral enzyme. One such 18 ACS Paragon Plus Environment

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site was known to bind a series of indoles and related benzimidazoles, and our group used public information around these compounds to launch a new drug discovery program aimed at overcoming the developability challenges for the known compounds.44, 72

Ultimately this approach yielded an efficacious indole-based macrocycle with an improved pharmaceutical profile.73

Figure 3. Structure-based design of a macrocyclic HCV NS5B polymerase inhibitor. Overlay of public structures 2BRK74 (green color-by-atom), 2BRL74 (cyan color-by-atom) and 2DXS75 (purple color-by-atom); likely regions for 19 ACS Paragon Plus Environment


macrocyclization highlighted with shaded background spheres; designed macrocycle from 4DRU44 shown in orange-color-by-atom; protein surfaces from the respective complexes shown in grey; superpositions based strictly on protein backbone atoms.

The published indole/benzimidazole polymerase inhibitors showed promising levels of enzyme inhibition and antiviral activity, but were hampered by structural features and/or physicochemical properties problematic for drug development.44, 72 Thus, we found ourselves in a situation frequently encountered in early drug discovery: a promising lead molecule or chemotype emerges, but with one or more undesirable features. At the time, the enzyme had already been extensively characterized. As part of our background research we had compiled a data set of the available 3D structures of NS5B polymerase–inhibitor complexes.74, 75 The single inhibitors display flexible polar moieties projecting away from the binding surface toward bulk solvent, from two distinct regions of the common core binding element (Figure 3). Overlay of all three structures offered a striking perspective, suggestive of cyclization between two solvent-exposed moieties to form a macrocycle (Figure 3). Further analysis and modeling based on these three public 3D structures led us to postulate that macrocyclization of the known compounds would lead to macrocyclic analogs that maintained all of the binding interactions 20 ACS Paragon Plus Environment

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observed for the non-macrocyclic parents.

We also expected the new

macrocycles to have altered physicochemical property profiles.1, 5 Pursuing these ideas, we designed and synthesized several different macrocyclic “linkers” that appeared to fit our overall strategy for targeting this site on the polymerase. In this case macrocyclization led to the discovery of potent inhibitors with improved oral bioavailability and liver distribution,76 the latter property being key for a hepatitis chemotherapeutic.44, 72 Application of this approach led our research program to a clinical candidate relatively rapidly.77

Section 3: Structure-based design of small-molecule macrocycles – Additional examples and summary We have described three cases in some detail. Further detailed review is beyond the scope of the present overview. Prior to summarizing this section, Table 1 lists a few additional examples that may be of interest to some readers.

Table 1. Additional examples of structure-based design of small-molecule macrocycles.



protein target

Factor XIa

Factor VIIa

HIV-1 protease

β-secretase

BCL-6

p53-MDM2

macrocycle details generic linker optimized to form specific intramolecular hydrogen bond; improved inhibitory and anticoagulant potency, and better selectivity versus related proteases optimization of macrocycle led to improved inhibitory and anticoagulant potency, and better selectivity versus related proteases peptidic P1-P3 sidechain-cyclized macrocycles with improved affinity and antiretroviral potency cross-linking of P1-P3 sidechains and additional optimization yields BACE-1 inhibitor with promising activity in Alzheimer's disease-related mouse model macrocyclization to favor binding conformation; high affinity inhibitors for a relatively new PPI target computational method-based approach to discovery of novel, non-peptidic macrocycles with modest "lead-like" affinities

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The macrocycle design examples outlined above are founded on 3D structural data. One or more observed small-molecule binding modes indicated that two ends or moieties of the bound small-molecule ligand could be connected, with the new macrocyclic molecule maintaining the bound conformation and binding interactions observed for the non-macrocyclic parent. This is essentially structurebased design. In the most typical small-molecule structure-based drug design 22 ACS Paragon Plus Environment

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(SBDD) scenario, 3D information about a protein-ligand complex is used to design new small-molecule ligands with increased binding affinities through added or modified binding interactions. In this macrocycle design variation of SBDD, 3D information guides ligand modification to form a macrocycle (c.f. eg. Figure 3). The aim of this type of structure-based macrocycle design effort could be to alter or add intermolecular binding interactions to improve binding affinity or selectivity, as in the most typical application of SBDD. Other objectives may include improved affinity through rigidification (decreased entropic penalty of binding), altered physicochemical properties, altered tissue distribution including CNS penetration, enhanced proteolytic stability (especially for peptidic molecules) and new intellectual property based on molecular novelty (references noted above).

Section 4: Identification of opportunities for the structure-based design of new macrocycles In the preceding sections we have outlined some aspects of the current status of macrocyclic small-molecules in drug discovery. Interest in macrocycles for drug discovery has been increasing. Macrocycles are conceptually attractive because they may provide access to an expanded (“beyond rule of 5”) chemical space for small-molecule drug discovery, which in turn may be advantageous for drug 23 ACS Paragon Plus Environment


discovery targeting protein-protein interactions. Macrocycle drugs and clinical compounds are largely natural products or cyclic peptides – a few rationally designed macrocycles in clinical development or on the market are more similar to typical synthetic small-molecule drugs. The discovery paths for natural products and synthetic drugs are very different. Only a few of the macrocycles in clinical development are based on a molecular design approach where an identifiable nonmacrocycle “parent” molecule gave rise, through iterative design, synthesis and testing, to a macrocyclic analog. We outlined representative examples of precisely this scenario, wherein structure-based design led to the discovery of macrocyclic analogs derived from non-macrocyclic “parent” small-molecule ligands. Furthermore, in these cases the resulting macrocyclic analogs were shown to represent advances in their respective drug discovery areas. To summarize, in these cases one or more 3D structures of relevant protein-ligand complexes provided the foundation for the structure-based design of a macrocyclic analog.

If macrocycles are indeed of interest for small-molecule drug discovery, then we can postulate that sources of new macrocycles are also of interest. The study of new macrocycles may lead to further insights into the properties of such molecules, and may open new avenues of drug discovery. In small-molecule drug discovery in pharmaceutical research, opportunities to apply a structure-guided approach to 24 ACS Paragon Plus Environment

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macrocycle design are not uncommon. 3D structure-enabled projects frequently yield bound ligand conformations that seem consistent with or pre-disposed toward macrocyclization.

In principle, of course, any small-molecule can be (macro-)cyclized. Bound smallmolecule ligand conformations will fall somewhere on the spectrum ranging from “linear and maximally extended” to “partially folded and slightly or somewhat Cshaped” to “folded back on itself and U-shaped.” In a drug discovery context where 3D structural information becomes available for a small-molecule chemotype of interest, drug discovery scientists exploit this information toward various ends including improved affinity, alternative physicochemical properties and novelty (e.g. defensible intellectual property). For bound small-molecules that are somewhat folded back upon themselves, macrocyclization represents a feasible approach that may address one or more of these common drug discovery objectives.

In the macrocycle design examples detailed above, the original non-macrocyclic “parent” molecules tend toward “partially folded and C-shaped” to “folded and Ushaped.” From these examples we can distill a simple algorithm that facilitates the 25 ACS Paragon Plus Environment


detection of bound ligand conformations that appear well-suited for modification into macrocycles. Thus, for any pair of atoms within a bound ligand, we can consider the through-space distance between the two atoms and the number of bonds comprising the shortest through-bond path between the same two atoms. If the through-space distance is relatively short for a given through-bond path then this is indicative of a compact or folded ligand conformation, and the atom pair represents candidate positions for intramolecular connection to form a macrocycle. This simple approach can serve to identify small-molecule conformations that appear to be consistent with, or pre-organized for, macrocyclization.

Figure 4. Examples of bound ligands showing a conformational pre-disposition to macrocyclization. C-shaped or folded conformations of protein-bound smallmolecule ligands showing one or more atom-atom pairs with relatively short atomatom through-space distances for the corresponding through-bond paths (see text; distances in Å; PDB ID’s (left to right): 4P38,84 3KJS,85 2XU4,86 4FZ787).


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Figure 4 shows examples of ligands and conformations that can be identified with this kind of analysis,88 consistent with the idea that relatively simple metrics can identify bound small-molecules that show some conformational pre-disposition toward macrocyclization. Our preliminary analysis of the full PDB89 (www.rcsb.org) indicates a rich vein to mine for such small-molecule structures (Figure 4; additional results not shown).

In the overall process of macrocyclic

drug discovery, identification of such starting points is one of the first and, arguably, one of the easiest, of many steps in this challenging process.

When a candidate molecule has been selected as the foundation for a macrocycle, designing the macrocyclic connection is the next step. In some cases, connection schemes to consider may be dictated by the protein-ligand system. For example, in the HCV protease system described above, connection of two hydrophobic alkyl sidechains that bind in close proximity to each other and contact a hydrophobic region of the enzyme binding site mandated a relatively small hydrophobic linker (protein not shown, but see Figure 1). Overlays with related protein-ligand complex structures may also be suggestive. Visual inspection of the smallmolecule and likely macrocyclization connection points along with the 3D structure of the complex with the target protein will assuredly lead to ideas for possible connection schemes in many protein-ligand systems. Typical interactive 27 ACS Paragon Plus Environment


SBDD involving overlays and molecule building, cut-and-paste strategies and small-molecule conformational analysis will find application in this macrocycle design context. Several of the major molecular modeling software packages (eg. CCG,90 Openeye,91 Schrodinger92) have utilities or protocols that can be applied to the construction of macrocycle linkers, and specific tools for macrocycle linker construction have started to emerge.93 Alternatively, this part of the structurebased macrocycle design process can be viewed as a pharmacophoric search problem, and relevant computational tools can be brought to bear. We recently described the application of the pharmacophore search tool CSD-Crossminer94 to this problem,95 and other researchers have also begun to address this problem with a pharmacophore search-based approach.96

Section 5: Conclusion Historically, most macrocyclic drugs have been natural products and peptides. Purely synthetic macrocyclic small-molecule drugs are rare but not unknown, and interest in this area is being driven by multiple factors. Difficult new targets including protein-protein interactions, interest in expanded chemical space beyond Rule of Five limits for small-molecule drug discovery, advances in synthetic chemistry technology as well as developments in drug formulation and delivery are 28 ACS Paragon Plus Environment

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all driving or enabling exploration of synthetic small-molecule macrocycles in drug discovery.

The PDB89 contains more than 145,000 3D protein structures, including more than 26,000 unique protein-bound ligands. The CSD97 (www.ccdc.cam.ac.uk) is approaching 1,000,000 small-molecule entries. These vast treasures of 3D structural information are powerfully enabling in many aspects of small-molecule drug discovery. Our personal experience over decades of pharmaceutical research has been that in structure-enabled drug discovery programs, macrocycle-like conformations are often observed for non-macrocycle small-molecule ligands bound to their protein targets. In this brief perspective we have outlined several cases exemplifying the use of 3D structural information in the design of synthetic small-molecule macrocycles that advanced drug discovery efforts. We then went on to describe one approach to the systematic identification, and prioritization, of macrocycle-like conformations of small-molecules. Our primary interest is in analyzing protein-ligand complexes, but the method is also applicable to smallmolecule crystal structures. Overall, our goal is to highlight the great potential we see for the application of SBDD to the design and discovery of new smallmolecule macrocycles. Structure-based analysis indicates that there are many opportunities for macrocyclization in the set of protein-ligand complexes currently 29 ACS Paragon Plus Environment


available at the PDB. This may be useful in studies aimed at gaining general understanding of how macrocyclization alters molecular properties. Finally, we encourage readers to consider structure-based design of macrocycles as one approach to overcoming molecular property challenges in small-molecule drug discovery.

Author information Tel: 215-628-6269 [email protected] †

Janssen Research and Development, LLC, Welsh and McKean Roads, Spring

House, PA 19477, USA. [email protected] 215-628-6269

‡

Cambridge Crystallographic Data Centre, 252 Nassau St, Princeton, NJ 08542,

USA.

Biographies Max Cummings is a Computational Chemist at Janssen R&D in Pennsylvania, working on drug discovery in various therapeutic areas. He received his Ph.D. in Biochemistry in 1996 from the University of Alberta, Canada, applying computational docking to molecular recognition problems in the areas of ubiquitin 30 ACS Paragon Plus Environment

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protein-protein interactions and bacterial toxin receptor binding. Dr. Cummings worked at SynPhar (now NAEJA), Edmonton, Canada, from 1988-1996, and at SmithKline Beecham (now GSK), King of Prussia, USA, from 1997-2000. In 2000 he joined 3-Dimensional Pharmaceuticals, Exton, USA, which later become part of Johnson & Johnson. In 2007 he moved to Tibotec BVBA, a J&J company, in Mechelen, Belgium, and in 2011 returned to the Janssen R&D site in Spring House, USA. Sivakumar Sekharan is a Research and Applications Scientist at the Cambridge Crystallographic Data Centre (CCDC) in New Jersey. He received his Ph.D. in Theoretical Chemistry in 2007 at the University of Duisburg-Essen, Germany, where he applied ab initio QM methods to the study of mammalian photoreceptors. Following postdoctoral fellowships at the Max-Planck Institute for Polymer Research and Emory University, Dr. Sekharan joined the Chemistry department at Yale University in 2012 as an Associate Research Scientist where he applied homology modeling, QM/MM methods and MD simulations to the study of olfactory receptors and GPCR’s. In 2015 he joined Cloud Pharmaceuticals, applying artificial intelligence-based methods to drug design. Since 2016 he has been at the CCDC working at the interface between research, software development and user services.



Acknowledgements The authors appreciate the review and comments as well as the ongoing support of Dr. Jason Cole (CCDC) and Dr. Renee L. DesJarlais (Janssen R&D). We also appreciate the extensive constructive comments of two of the Reviewers, many of which were incorporated into the final version of our manuscript.

Abbreviations used PPI, protein-protein interaction; p53, tumor suppressor p53; HDM2, human double minute 2 homolog; MDM2, mouse double minute 2 homolog; MW, molecular weight; BCL-2, B-cell lymphoma 2 protein; HCV, hepatitis C virus; HIV, human immunodeficiency virus; NS3, non-structural protein 3; NS5b, non-structural protein 5b (RNA polymerase); NMR, nuclear magnetic resonance; FDA, (U.S.) Food and Drug Administration; JAK2, Janus kinase 2; FLT3, fms-like tyrosine kinase 3; ALK, anaplastic lymphoma kinase; CNS, central nervous system; ADME, absorption distribution metabolism and excretion; Syk, spleen tyrosine kinase; Abl, Abelson murine leukemia viral oncogene homolog 1; JNK3, c-Jun Nterminal kinase 3; BCL-6, B-cell lymphoma 6 protein; SBDD, structure-based drug design; 3D, three dimensional; PDB, RCSB protein data bank (www.rcsb.org); CSD, Cambridge structural database (www.ccdc.cam.ac.uk). 32 ACS Paragon Plus Environment

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tetraazatetracyclo[19.3.1.1(2,6).1(8,12)]heptaco sa1(25),2(26),3,5,8(27),9,11,16,21,23-decaene (SB1317/TG02), a potent inhibitor of cyclin dependent kinases (CDKs), Janus kinase 2 (JAK2), and fms-like tyrosine kinase-3 (FLT3) for the treatment of cancer. J. Med. Chem. 2012, 55, 169-196. (67) Johnson, T. W.; Richardson, P. F.; Bailey, S.; Brooun, A.; Burke, B. J.; Collins, M. R.; Cui, J. J.; Deal, J. G.; Deng, Y. L.; Dinh, D.; Engstrom, L. D.; He, M.; Hoffman, J.; Hoffman, R. L.; Huang, Q.; Kania, R. S.; Kath, J. C.; Lam, H.; Lam, J. L.; Le, P. T.; Lingardo, L.; Liu, W.; McTigue, M.; Palmer, C. L.; Sach, N. W.; Smeal, T.; Smith, G. L.; Stewart, A. E.; Timofeevski, S.; Zhu, H.; Zhu, J.; Zou, H. Y.; Edwards, M. P. Discovery of (10R)-7-amino-12-fluoro-2,10,16-trimethyl15-oxo-10,15,16,17-tetrahydro-2H-8,4-(m etheno)pyrazolo[4,3-h][2,5,11]benzoxadiazacyclotetradecine-3-carbonitrile (PF-06463922), a macrocyclic inhibitor of anaplastic lymphoma kinase (ALK) and c-ros oncogene 1 (ROS1) with preclinical brain exposure and broad-spectrum potency against ALK-resistant mutations. J. Med. Chem. 2014, 57, 4720-4744. (68) Zou, H. Y.; Li, Q.; Engstrom, L. D.; West, M.; Appleman, V.; Wong, K. A.; McTigue, M.; Deng, Y. L.; Liu, W.; Brooun, A.; Timofeevski, S.; McDonnell, S. R.; Jiang, P.; Falk, M. D.; Lappin, P. B.; Affolter, T.; Nichols, T.; Hu, W.; Lam, J.; Johnson, T. W.; Smeal, T.; Charest, A.; Fantin, V. R. PF-06463922 is a potent and



selective next-generation ROS1/ALK inhibitor capable of blocking crizotinibresistant ROS1 mutations. Proc. Natl. Acad. Sci. U. S. A. 2015, 112, 3493-3498. (69) https://www.fda.gov/Drugs/InformationOnDrugs/ApprovedDrugs/ucm625027.htm (70) Atwell, S.; Adams, J. M.; Badger, J.; Buchanan, M. D.; Feil, I. K.; Froning, K. J.; Gao, X.; Hendle, J.; Keegan, K.; Leon, B. C.; Muller-Dieckmann, H. J.; Nienaber, V. L.; Noland, B. W.; Post, K.; Rajashankar, K. R.; Ramos, A.; Russell, M.; Burley, S. K.; Buchanan, S. G. A novel mode of Gleevec binding is revealed by the structure of spleen tyrosine kinase. J. Biol. Chem. 2004, 279, 55827-55832. (71) Zhang, T.; Inesta-Vaquera, F.; Niepel, M.; Zhang, J.; Ficarro, S. B.; Machleidt, T.; Xie, T.; Marto, J. A.; Kim, N.; Sim, T.; Laughlin, J. D.; Park, H.; LoGrasso, P. V.; Patricelli, M.; Nomanbhoy, T. K.; Sorger, P. K.; Alessi, D. R.; Gray, N. S. Discovery of potent and selective covalent inhibitors of JNK. Chem. Biol. 2012, 19, 140-154. (72) Cummings, M. D.; Lin, T. I.; Hu, L.; Tahri, A.; McGowan, D.; Amssoms, K.; Last, S.; Devogelaere, B.; Rouan, M. C.; Vijgen, L.; Berke, J. M.; Dehertogh, P.; Fransen, E.; Cleiren, E.; van der Helm, L.; Fanning, G.; Nyanguile, O.; Simmen, K.; Van Remoortere, P.; Raboisson, P.; Vendeville, S. Discovery and early development of TMC647055, a non-nucleoside inhibitor of the hepatitis C virus NS5B polymerase. J. Med. Chem. 2014, 57, 1880-1892. 46 ACS Paragon Plus Environment

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(73) Clinical development of this compound was suspended for business-related reasons. (74) Di Marco, S.; Volpari, C.; Tomei, L.; Altamura, S.; Harper, S.; Narjes, F.; Koch, U.; Rowley, M.; De Francesco, R.; Migliaccio, G.; Carfi, A. Interdomain communication in hepatitis C virus polymerase abolished by small molecule inhibitors bound to a novel allosteric site. J. Biol. Chem. 2005, 280, 29765-29770. (75) Ikegashira, K.; Oka, T.; Hirashima, S.; Noji, S.; Yamanaka, H.; Hara, Y.; Adachi, T.; Tsuruha, J.; Doi, S.; Hase, Y.; Noguchi, T.; Ando, I.; Ogura, N.; Ikeda, S.; Hashimoto, H. Discovery of conformationally constrained tetracyclic compounds as potent hepatitis C virus NS5B RNA polymerase inhibitors. J. Med. Chem. 2006, 49, 6950-6953. (76) The nature of the macrocycle linker was shown to have profound effects on oral bioavailability, clearance, liver microsomal stability, liver/plasma partitioning and total liver accumulation. These results are discussed in detail in ref. 72 and references therein. (77) TMC647055 progressed into Phase 2 clinical trials. Development was discontinued for strategic reasons. (78) Corte, J. R.; Fang, T.; Osuna, H.; Pinto, D. J.; Rossi, K. A.; Myers, J. E., Jr.; Sheriff, S.; Lou, Z.; Zheng, J. J.; Harper, T. W.; Bozarth, J. M.; Wu, Y.; Luettgen, J. M.; Seiffert, D. A.; Decicco, C. P.; Wexler, R. R.; Quan, M. L. Structure-based 47 ACS Paragon Plus Environment


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lymphoma 6 (BCL6) binders and optimization to high affinity macrocyclic inhibitors. J. Med. Chem. 2017, 60, 4386-4402. (83) Estrada-Ortiz, N.; Neochoritis, C. G.; Twarda-Clapa, A.; Musielak, B.; Holak, T. A.; Domling, A. Artificial macrocycles as potent p53-MDM2 Inhibitors. ACS Med. Chem. Lett. 2017, 8, 1025-1030. (84) Scott, J. S.; deSchoolmeester, J.; Kilgour, E.; Mayers, R. M.; Packer, M. J.; Hargreaves, D.; Gerhardt, S.; Ogg, D. J.; Rees, A.; Selmi, N.; Stocker, A.; Swales, J. G.; Whittamore, P. R. Novel acidic 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) inhibitor with reduced acyl glucuronide liability: the discovery of 4-[4-(2-adamantylcarbamoyl)-5-tert-butyl-pyrazol-1-yl]benzoic acid (AZD8329). J. Med. Chem. 2012, 55, 10136-10147. (85) Schormann, N.; Velu, S. E.; Murugesan, S.; Senkovich, O.; Walker, K.; Chenna, B. C.; Shinkre, B.; Desai, A.; Chattopadhyay, D. Synthesis and characterization of potent inhibitors of Trypanosoma cruzi dihydrofolate reductase. Bioorg. Med. Chem. 2010, 18, 4056-4066. (86) Hardegger, L. A.; Kuhn, B.; Spinnler, B.; Anselm, L.; Ecabert, R.; Stihle, M.; Gsell, B.; Thoma, R.; Diez, J.; Benz, J.; Plancher, J. M.; Hartmann, G.; Banner, D. W.; Haap, W.; Diederich, F. Systematic investigation of halogen bonding in protein-ligand interactions. Angew. Chem. Int. Ed. Engl. 2011, 50, 314-318.



(87) Kuglstatter, A., Slade, M. Crystal structure of spleen tyrosine kinase complexed with 6-((1R,2S)-2-Amino-cyclohexylamino)-4-(6-ethyl-pyridin-2ylamino)-pyridazine-3-carboxylic acid amide. (88) The details of this and related analyes will be published elsewhere. (89) Berman, H. M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T. N.; Weissig, H.; Shindyalov, I. N.; Bourne, P. E. The protein data bank. Nucleic Acids Res 2000, 28, 235-242. (90) www.chemcomp.com (91) www.eyesopen.com (92) www.schrodinger.com (93) Wagner, V.; Jantz, L.; Briem, H.; Sommer, K.; Rarey, M.; Christ, C. D. Computational macrocyclization: from de novo macrocycle generation to binding affinity estimation. ChemMedChem 2017, 12, 1866-1872. (94) Korb, O.; Kuhn, B.; Hert, J.; Taylor, N.; Cole, J.; Groom, C.; Stahl, M. Interactive and versatile navigation of structural databases. J. Med. Chem. 2016, 59, 4257-4266. (95) Sekharan, S.; Sykes, R.; Sanschagrin, P.; Cummings, M. In Simple metrics to identify opportunities for macrocyclization of small-molecule ligands, 256th ACS National Meeting & Exposition, Boston, 2018; American Chemical Society: Boston, 2018; pp COMP-227. 50 ACS Paragon Plus Environment

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(96) Scoffin, R.; Bauer, M.; Mackey, M.; Sciammetta, S.; Tedesco, G. In Rapid and accessible in silico macrocycle design, 2018; American Chemical Society: 2018; pp COMP-226. (97) Groom, C. R.; Bruno, I. J.; Lightfoot, M. P.; Ward, S. C. The cambridge structural database. Acta Crystallogr. B Struct. Sci. Cryst. Eng. Mater. 2016, 72, 171-179.



TOC Figure


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Structure-based macrocycle design in small-molecule drug discovery

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