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Kinase Crystal Miner: A Powerful Approach to Repurposing 3D Hinge Binding Fragments and its Application to Finding Novel Bruton Tyrosine Kinase Inhibitors. Prasenjit Mukherjee, Joerg Bentzien, Todd Bosanac, Wang Mao, Michael Burke, and Ingo Muegge J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.7b00213 • Publication Date (Web): 09 Aug 2017 Downloaded from http://pubs.acs.org on August 9, 2017

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Journal of Chemical Information and Modeling

Kinase Crystal Miner: A Powerful Approach to Repurposing 3D Hinge Binding Fragments and its Application to Finding Novel Bruton Tyrosine Kinase Inhibitors.

Prasenjit Mukherjee,$ Jörg Bentzien,# Todd Bosanac, Wang Mao, Michael Burke, and Ingo Muegge*,&

Boehringer Ingelheim Pharmaceuticals Inc., 900 Ridgebury Road, P.O. Box 368, Ridgefield, Connecticut 06877-0368, USA

*corresponding author: [email protected] phone (781) 296-6917

current addresses: & Alkermes, Inc., 852 Winter Street, Waltham, MA, USA, $

Gilead Sciences, 333 Lakeside Drive, Foster City CA; #Forma Therapeutics, 500 Arsenal Street, Suite 100, Watertown, MA, USA

1 ACS Paragon Plus Environment


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Abstract Protein kinases represent an important target class for drug discovery because of their role in signaling pathways involved in disease areas such as oncology and immunology. A key element of many ATPcompetitive kinase inhibitors is their hinge-binding motif. Here we describe Kinase Crystal Miner (KCM) a new approach developed at Boehringer Ingelheim (BI) that harvests the existing crystallographic information of kinase-inhibitor co-crystal structures from internal and external databases. About one thousand unique three-dimensional kinase inhibitor hinge binding motifs have been extracted from structures covering more than 180 different protein kinases. These hinge binding motifs along with their attachment vectors have been combined in the KCM for the purpose of scaffold hopping, kinase screening deck design, and interactive structure-based design. Prospective scaffold hopping using the KCM identified two potent and selective Bruton tyrosine kinase (BTK) inhibitors with hinge binding fragments novel to BTK.

Keywords: Structure Based Drug Design, Scaffold Hopping, Virtual Screening, Kinase, BTK, Modeling


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1 Introduction Protein kinases represent one of the most prevalent protein drug target classes playing a prominent role in discovering new therapies for oncology1-3 and other disease areas.4,

5

Protein

crystallography and structure-based drug design have played a crucial role in the discovery of new kinase therapies.6 Kinases use ATP to catalyze the phosphorylation of different substrate proteins and lipids.7 These modifications serve as critical recognition events in signaling pathways.8 There are over 500 protein kinases9 for which new disease state associations continue to be discovered every year supporting their entry into the current discovery portfolio of many pharmaceutical companies including Boehringer Ingelheim. The structural knowledge of the human protein kinome has increased significantly. In June 2017, we counted 358 PDB entries of unique human kinase sequences with publically available crystal structures belonging to Enzyme Commission class EC 2.7. (Supporting Information file 358_KINASE_ALL_PDB). Even after discounting mutants, variants, and crystallographic constructs there are more than 200 human kinases for which structures at atomic resolution are available today. The large and growing “Kinase Crystalome” offers a rich knowledge base that can be mined to generate structure-based design ideas transcending individual kinase targets. Kinase structures exhibit a bi-lobed structure with an N-terminal and a C-terminal lobe consisting primarily of beta sheets and alpha helices, respectively (Figure 1).10 The two lobes are connected by a linear region containing a three residue hinge sequence. The hinge forms part of the ATP substrate binding site. The adenine group of ATP forms key interactions with the backbone of these hinge residues. The majority of kinase inhibitors, but not all,11, 12 bind in the catalytic site.13, 14 Most of these kinase inhibitors contain a hinge binding motif forming key acceptor and donor interactions with the same hinge backbone atoms adenine interacts with thereby competitively displacing the substrate from the binding site.



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Figure 1: Top: Illustrating the structure of the overall kinase fold and highlighting the hinge area occupied by ATP and a typical amino-pyrimidine kinase inhibitor. Bottom left: KCM analysis of the distribution of the common amino-pyrimidine hinge binding fragment over prominent groups of kinases. Bottom right: Structural comparison of the 1st generation Bcr-Abl-kinase inhibitor imatinib and the 2nd generation inhibitor ponatinib.

Due to high similarity in shape and pharmacophore characteristics of ATP binding sites of kinases, identical hinge binding motifs can be observed in kinase inhibitors across different sub-families of the human kinome. For example, co-crystal structures of kinases with an inhibitor containing an amino-pyrimidine hinge binding motif exist within kinases in all major arms of the kinome (Figure 1). Other hinge binding moieties such as pyrazolo pyridines have been shown to be active across multiple kinases as well.15 Hinge binding motifs often form the central core of a kinase inhibitor and define the key part of the synthesis strategy. The replacement of hinge binding motifs can therefore provide an avenue to obtain intellectual property. More importantly, in some cases, hinge binding fragments alone or in combination with other parts of the inhibitor can provide selectivity over other kinases or their mutants.14, 16 For example, imatinib - a Bcr-Abl kinase inhibitor - forms a single interaction with the hinge through the pyridine acceptor. Imatinib forms an additional donor interaction with residue threonine 315 (Thr315), which is located just before the hinge and is known as the gatekeeper in kinase


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terminology (Figure 2). Treatment with imatinib in the clinic has resulted in several resistant mutations including one that converts Thr315 to an isoleucine also known as the T315I mutation.17 This mutation results in an electrostatic and steric mismatch in the area of the donor –NH of imatinib resulting in the lack of binding of the inhibitor to the mutant variant of Bcr-Abl kinase. Introducing a different hinge binding motif as well as a narrow acetylene linker led to the discovery of ponatinib - a second generation imatinib analog – that binds to the T315I mutant variant bypassing the larger isoleucine residue thereby circumventing resistance against the mutant.18 The imatinib-ponatinib example served as an inspiration for the Kinase Crystal Miner (KCM) introduced here. Researchers have always used the growing structural information about kinase-ligand interactions to gain new insights towards designing future kinase inhibitors.16 Curated kinase structure databases have been introduced,19, 20 kinase inhibitors have been classified based on the structures of inhibitor-kinase complexes,13 and pharmacophore information was derived from selected known hinge binding fragments to identify novel kinase inhibitors among internally or commercially available compounds.21 In addition, 600 hinge binding scaffolds have been extracted from public and Pfizer kinase structures and characterized based on their specific hinge interactions.22 KCM was implemented at BI to systematically mine kinase crystal structures available from internal and external sources to extract all fragments available with observed kinase hinge interactions at 3D atomic resolution. To this end, KCM generates a database of hinge binding fragments that is more comprehensive than what has been available in the literature before and distinguishes itself by providing experimentally observed attachment vectors essential to enable a seamless substitution and replacement. The hinge binding fragments along with the attachment vectors can be used interactively for structure-based design, virtual library enumeration, scaffold hopping exercises, and the creation of kinase-biased screening decks.



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Materials and Methods At the core of the KCM lies a MOE23 database with hinge-aligned kinase crystal structures, 2D ligand interaction maps, 3D site views with kinase sequence annotations, physicochemical descriptors of the hinge binding fragments that are stored for use in a Spotfire session. The steps for creating the MOE database can be accessed from a MOE installation at /moe/html/proteins/pdb_mdb.htm#kinDB. The standard MOE installation svl script /moe/lib/svl/run/dbupdate.svl

is used to generate an updated

database which connects to an in-house installation of PSILO24, a commercial product used as a repository of the crystallographic data. The PSILO installation contains the latest information from the Protein Data Bank (PDB) as well as in-house crystallographic data. Sequence patterns around the kinase catalytic site are used to identify a kinase structure and to align new structures thereby generating a global kinase alignment. The process was implemented in a Knime workflow, which is provided as Supporting Information (Kinase_Aligned_Deck_Generation.knwf). Structures without ligands in the hinge region or containing ligands with elements other than C, N, O, S, P, B, and halides were filtered out. Ligands were fragmented in 3D space using the fragmentation schemes FragmenterAll and RingChainRecap in Chemaxon.25 2D ligand interaction maps were generated using MOE. The smallest fragment making all observed hinge binding interactions is identified. In addition to traditional hydrogen bond interactions, weaker C-H···O bonds and halogen bonds with the hinge were considered as well. A total of 2251 kinase co-crystal structures from the PDB and private sources were mined leading to the 959 unique kinase hinge binding fragments including 767 unique kinase hinge binding fragments from the PDB.26 A list of the unique PDB fragments, their origin compounds, hinge interaction annotation, and calculated descriptors is provided as Supporting Information (UNIQUE_PUBLIC_PDBID.xlsx). These unique hinge binding fragments can now be used to perform substructure searches of internal and external compound databases to identify a list of testing-ready compounds. A Knime


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workflow was implemented to perform this search on BI’s internal compound database and the final list of compounds was stored in a MOE database. Internal database connection Knime nodes were utilized to pull the activity data from a panel of 60 biochemical kinase assays. An alignment-based filtering was carried out using the Cresset Forge Knime node.27 The input is a reference ligand structure, protein coordinates for use as an exclusion zone, and the ligands to be aligned. Using a maximum common substructure-based constraint the hinge region of the ligands was aligned and overlaid with that of the reference structure. A similarity score cutoff of 0.8 was applied giving equal weight to the shape and field components and soft van der Waals scaling was used for the protein exclusion zone.

Details of the workflow. Figure 2 illustrates the fragmentation workflow. Individual interaction patterns highlight which atom (number, element) of the ligand interacts with which atom and residue of the protein and the type of interaction that is observed. This information is collected and analyzed for the maximum number of interactions occurring with the residues of the hinge. Next the ligand is

fragmented in 3D space using a combination of fragmentation routines including RECAP,28 ring-chain and Chemaxon internal routines to generate the maximum number of unique fragments. The information on the attachment points where the disconnections occur during the fragmentation routine is also stored. Each of the fragments in 3D space is taken in the context of the binding site and a 2D ligand interaction diagram is generated to extract the interaction information as described above. As an example, Figure 2 shows a set of three fragments with attachment points (in brown) generated from the full ligand co-crystal structure. The first fragment is the benzofuran moiety with a single attachment point which upon fragmentation does not show any interactions with the protein. The second fragment, an indazole group with two attachment points, forms two interactions with the protein: one hydrogen bond donor and one hydrogen bond acceptor interaction. The third fragment is the amino-pyridine moiety which also forms a donor and an acceptor interaction with the protein. However, only the indazole moiety forms hydrogen bonding interactions with the hinge residues. The amino-pyrimidine 7 ACS Paragon Plus Environment


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moiety forms interactions with the methionine gatekeeper residue (Met 320) and the lysine residue (Lys 161) instead. Therefore, the indazole moiety is the relevant hinge binding fragment here. The information about the hinge binding fragment along with additional information mentioned in the first paragraph of this section is passed on to the output. This process is repeated for all co-crystal structures in the database. The protocol is written as a Knime workflow tool and allows for periodic updates of the database based on the latest crystallographic information available from private and public sources. The Knime workflow generates a Spotfire session as well as a MOE database containing the actual co-crystal structures for visual inspection.

Figure 2: Hinge binding fragment generation protocol. Top: Extracting the relevant 3D-information from the crystallographic databases. Middle: Fragmenting the ligand and identifying the hinge binding fragment. Bottom: Storing the hinge binding fragments in a database for Spotfire and MOE analysis.


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An exclusion-sphere clustering using Daylight fingerprints and a Tanimoto distance threshold of 0.7 was used for clustering. While the clustering may not be necessary for the fragments, it allows for a

convenient grouping of the much larger number of compounds that contain kinase hingebinding fragments. We used the reaction enumerator node in Pipeline Pilot29 to generate virtual compound libraries containing KCM hinge binding fragments for virtual screening purposes. Compound structures were minimized in Macromodel30 and docked into kinase crystal structures with Glide.31

Results and Discussion 3D fragmentation of ligands. Figure 3 illustrates why 3D fragmentation generates more relevant hinge binding fragments than an observation of 2D moieties might provide. Amino-pyrimidines are a common motif for hinge interactions in kinase inhibitors. However, examining three kinase co-crystal structures (JAK: PDB-4DOW; MAPK2: PDB-3KC3; MAPK2: PDB-3KAO) of amino-pyrimidine containing ligands reveals that the presence of such prominent motif does not always correspond to an actual hinge binding. Only in the JAK structure (4DOW) the amino-pyrimidine motif forms interactions with the hinge, but not in the two MAPK2 structures (3KC3, 3KAO). Rather, in the 3KC3 structure it is the hydroxyl-group that forms a single interaction with the backbone carbonyl of the H1 residue. In the 3KAO structure, there are two moieties that can form hydrogen bonding interactions with the protein. Here the indazole group forms hydrogen bond donor-acceptor interactions with the hinge motif. This example demonstrates that 3D information is essential to correctly identify the hinge binding fragment of kinase inhibitors and that 2D structural information alone may lead to wrong assumptions about what part of the inhibitor interacts with the hinge region.



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Figure 3: Kinase co-crystal structures with amino-pyrimidine containing ligands. Three examples of amino-pyrimidine containing kinase inhibitors are shown (JAK: PDB-4DOW; MAPK2: PDB-3KC3; MAPK2: PDB-3KAO). These examples illustrate the importance of using 3D-information to correctly identify the hinge binding fragment. The simple assumption that, if present in the ligand, it is always the aminopyrimidine moiety that acts as the hinge binder is not valid.

Figure 4 shows an example of how the hinge binding fragment is identified. The fragment needs to satisfy all hinge-ligand interactions established by the full molecule. If there are multiple fragments satisfying the interactions the fragment with the fewest heavy atoms is chosen. In the case of the tetrahydropyrrolo pyrazole inhibitor in Figure 4, the ligand forms three hydrogen bonding interactions with the three hinge residues. The pyrazole moiety of the 5,5 system donates a hydrogen bond to the backbone carbonyl of the H1 residues while the adjacent nitrogen accepts a hydrogen bond from the backbone NH of the H3 residue. The third hinge interaction occurs between the exocyclic NH of the ligand amide group and the carbonyl oxygen of the H3 residue. The ligand is fragmented in 3D space in the context of the protein. Fragment 1 has one disconnection point that breaks the piperidine carbonyl group. This fragment forms all the hinge interactions established by the parent ligand. Fragment 2 has two disconnection points and consists only of the central 5,5 moiety. This fragment only forms two of the three hinge interactions; it misses the exocyclic amine. Fragment 3 is another fragment satisfying all three hinge interactions. Fragments 1 and 3 both satisfy the maximum number of hinge interactions.


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Fragment 3 is the smaller of the two by heavy atom count and therefore is selected to be the hinge binding fragment.

Figure 4: Fragmentation of the CDK inhibitor (PDB ID: 2WPA) and identification of the hinge binding fragment.

Application of KCM. Spotfire and MOE databases have been chosen as front ends for the KCM tool (Figure 5). The user can perform substructure filtering or browse through individual hinge binding fragment clusters. Once a given cluster is selected the user can access individual cocrystal ligand structures (2D), view the 2D ligand interaction diagram for a given structure, view the ligand binding site of the co-crystal with kinase sequence annotations in 3D, analyze the distribution of kinase structures with a given hinge substructure across different families of the kinome and investigate conformational states regarding the orientation of the DFG loop or the alpha-C helix of these kinase structures. Descriptors are calculated for the hinge binding

fragments including ring/aromatic ring counts, fraction sp3, and the MOE globularity descriptor



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that could guide users to hinge binding fragments that are different from the typical aromatic and flat structures.

Figure 5: Spotfire frontend to KCM allowing for different analyses of the identified hinge binding fragments: 3D-view, 2D interaction maps, distribution over different kinase conformational states (DFG-in vs. DFG-out, Alpha-C helix in vs. Alpha-C helix out), distribution over the kinase crystalome, distribution of physical chemical properties.

Using less common hinge binding fragments to spawn ideas for structure-based design. A histogram showing the distribution of kinase hinge binding fragments is provided in Figure 6. The X-axis on the plot shows cluster numbers while the Y-axis shows the number of kinase crystal structures associated with each cluster. A cluster can consist of a single unique hinge binding fragment or contain multiple unique but closely related hinge binding fragments. In the current version a set of 2251 kinase co-crystal structures from public and private sources were mined leading to the identification of 959 unique kinase hinge binding fragments which could be further grouped into 836 clusters. There are only few clusters with fragments occurring in more than ten different structures. More interestingly, there is a large number of hundreds of fragments that occur only once. This finding suggests a large structural variety of chemical moieties identified by the KCM tool.


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Figure 6: Distribution of clustered fragment occurrences. Clusters capturing a single unique fragment are colored cyan while those capturing multiple related but unique hinge binding fragments are colored in magenta.

Figure 7 shows the top 10 most frequently occurring kinase hinge binding fragments identified. All of these fragments, with the exception of staurosporine, are either mono- or bicyclic aromatic systems that are planar, lacking sp3 character (fSP3) and three-dimensionality (Globularity). Among fragments occurring less often, we observe more structurally diverse hinge binders. The first example in Figure 8 (PDB ID: 3BV3) shows a less common hinge binding fragment where the hinge interaction occurs through the carbonyl oxygen of an exocyclic amide group. The second example in Figure 8 (PDB ID: 4EKL) shows a hinge binding fragment that has three dimensionality built in. One hinge interaction is occurring via a hydroxyl motif vectoring from the ring system via a stereo-chemical center. The third example captures a nontraditional hinge interaction. The hinge binding fragment in PDB ID: 3HLL forms two interactions with the hinge, a more traditional interaction with the carbonyl oxygen as acceptor and a second, less common halogen bond interaction between the bromine atom and the backbone carbonyl oxygen of the H1 residue.



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Figure 7: The top 10 most common hinge binding fragments in the database. The count represents the number of kinase structures, fSP3 stands for fraction of sp3 carbons, ring stands for the number of rings, aromatic ring denotes the number of aromatic rings and Globularity is a descriptor from MOE measuring the three-dimensionality of the fragment. The attachment points to the ligand are shown with “A” and the hinge interactions are shown using red dotted lines.


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Figure 8: Three examples showing less common hinge binding motifs. Top: a non-ring hinge binder; middle: a non-planar hinge binder; bottom: a non-traditional hinge binding interaction.

Using hinge binding fragments to generate hit finding libraries. Storing hinge binding fragments together with their observed attachment points allows the KCM user to perform hinge scaffold hopping tasks. Similar to commercial software that replaces 3D scaffolds based on fragment replacements32 the KCM user can perform kinase hinge-specific core replacements starting from a template structure obtained from crystallography or modeling (Figure 9). Starting from a kinase chemical series where one wishes to retain some non-hinge binding motifs, one can disconnect the desired moieties from the hinge binding fragment, use the attachment points of the hinge binding fragment database to enumerate onto the remaining 15 ACS Paragon Plus Environment


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non-hinge binding parts, perform an in-silico selection of desired candidate compounds via docking, model predictions, physical chemical property calculations, and then prioritize compounds for synthesis and biological testing. The fragments in the KCM are all crystallographically validated and have established chemistry. Therefore, synthesizing hits can be straightforward in most cases. Also hit-rates and the retention of properties associated with the starting templates (such as selectivity) are expected to be high. An example of this approach is given in the subsequent section.

Figure 9: KCM scaffold hopping workflow. The schema illustrates how to identify a new hinge binding motif connected to a selectivity anchor using KCM, hopping from one hinge binding scaffold to another.

From hinge binding fragments to testing ready compounds. The KCM was used to identify screening-ready compounds associated with hinge binding fragment as scaffold hopping hits. The goal was to evaluate the new hinge binding fragment hypotheses by screening available compounds before or instead of investing in the synthesis of novel compounds. Thus a kinasebiased deck of compounds was created from which subsets can be chosen for screening to identify starting points without investing chemistry resources (Figure 10a). To identify a suitable list of available compounds we split a ligand-kinase complex into the 3D ligand pose and the 16 ACS Paragon Plus Environment

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protein, the latter being used as a representation of the shape of the binding site. From the crystal structure the hinge binding fragment with attachment point(s) is identified. The hinge binding fragment is used to conduct a substructure search against a database of available compounds either from internal or external (e.g., commercial or academic) sources. This process is repeated for all ligand-kinase complex structures. In this manner, compounds are identified which share the hinge binding substructure and have substitutions at the same positions as specified by the attachment points. The compatibility of the attachment points is important because a molecule with a given hinge binding fragment but with different decorations from the reference compound may not be suitable for binding in a similar fashion to the kinase binding site. Here we would like to bias the selection of new hinge binding fragments to those that are as close to the reference fragment as possible. However, simply having the desired substructure and substitution pattern in a given ligand does not guarantee that it will bind to a kinase binding site. Therefore, additional filter steps are introduced.



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Figure 10: Kinase compound selection workflow. (a) Selecting ligands with a hinge binding substructure filtered based on activity and alignment criteria for the addition to a kinase biased screening deck. (b) Example of an AGC kinase co-crystal query used to identify ligands based on alignment and activity criteria.

The first filter step is an activity filter. The compounds identified through substructure matching of hinge binding fragments are checked against dose-response data from a panel of 60 biochemical kinase assays devised as follow-up to high throughput screening (HTS) single point assays. This assay panel is likely to capture higher chemical diversity than typical project assays, which will have higher density of data around fewer selected scaffolds. If a compound is found to be active in any of these assays (IC50

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