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Structural approaches to obtain kinase selectivity
Review
Structural approaches to obtain kinase selectivity Richard A. Norman1, Dorin Toader2 and Andrew D. Ferguson3 1
Discovery Sciences, AstraZeneca, Mereside, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK Oncology iMED, AstraZeneca, 35 Gatehouse Drive, Waltham, MA 02451, USA 3 Discovery Sciences, AstraZeneca, 35 Gatehouse Drive, Waltham, MA 02451, USA 2
One of the grand challenges in kinase drug discovery is the design of small-molecule inhibitors with selectivity profiles that will ultimately be efficacious in the clinic. Current medicinal chemistry strategies make heavy use of structural, biophysical and computational approaches to achieve this multi-faceted goal. Here we review structure-based approaches underlying the development of several molecules that are currently in clinical trials, including the cMet inhibitor ARQ197 and the Bcr–Abl inhibitor ponatinib. We highlight the challenge posed by the emergence of resistance mutants and discuss promising lead generation strategies to obtain selective inhibitors of protein and lipid kinases such as targeting of specific sites, the use of fragment-based approaches and new chemical probes based on metal complexes. Protein kinases and inhibitor classes Human protein kinases control a plethora of signal transduction networks that are crucial in the regulation of critical cellular processes, including cell growth, metabolism and division [1]. Dysregulation of these pathways has been shown to be a causative factor in human disease, making protein kinases important targets for drug discovery for the pharmaceutical industry. The catalytic activity of protein kinases is mediated by ATP, which binds in a cleft between the N- and C-terminal lobes of a single domain (Figure 1a–c). Because the primary sequence and three-dimensional structures of kinases are similar, the development of selective inhibitors that exhibit minimal off-target activity can be challenging. Three main classes of kinase inhibitors (Types I, II and III) have been defined. Type I inhibitors target the active conformation of the kinase and directly compete with ATP binding (Figure 1a). The majority of reported kinase inhibitors are Type I, making the identification of novel intellectual property difficult. Type II inhibitors access an induced-fit hydrophobic pocket adjacent to the ATP-binding site (Figure 1b). This pocket is formed by a change in the conformation of the DFG motif (located at the start of the activation loop) from an active DFG-in conformation to an inactive DFG-out conformation that has lower affinity for ATP [2]. Inhibitors targeting the DFG-out conformation do not compete directly with ATP binding, and hence cellular potency and selectivity may be easier to obtain [3]. Type III inhibitors tend to be more selective than Types I and II, Corresponding author: Norman, R.A. ([email protected])
because they are ATP-noncompetitive and bind exclusively to sites outside the ATP-binding site (Figure 1c). Here we present several examples of structure-based approaches utilising crystallographic, biophysical and computational methods to rationally develop selective inhibitors, many of which have now reached the clinic. We also highlight some specific lead generation strategies that have been applied in the development of selective kinase inhibitors. Targeting the ATP-binding site Casein kinase II alpha (CK2a) is a constitutively active serine/threonine kinase that is involved in a variety of pathways essential for the maintenance of cellular homeostasis. A new class of highly selective, orally available CK2a inhibitors from Cylene Pharmaceuticals, exemplified by CX4945, recently entered Phase I clinical trials for advanced solid tumours and multiple myeloma. The high-resolution crystal structures of human CK2a in complex with CX4945 and two analogues, CX5011 and CX5279, revealed the structural determinants of the exquisite selectivity of this scaffold, which is driven by an intricate series of direct and water-mediated interactions with CK2a [4,5]. This example illustrates how the primary sequence, shape, electrostatics and flexibility of the ATP-binding site must be considered when designing inhibitor selectivity, and that determining whether water molecules should be displaced or exploited into forming bridging interactions between the inhibitor and the protein can be very challenging. Several methodologies for characterising water molecules have been developed and are reviewed extensively by Huggins et al. [6]. In particular, the work carried out at Schro¨dinger Inc. highlights the importance of understanding the water structure within the ATP-binding site of kinases when designing selective inhibitors. Using a computational method called WaterMap, which calculates the desolvation energy of the receptor, the locations and thermodynamic properties of water molecules were predicted for four different kinase systems. This information allowed the rationalisation of previously unexplained kinase inhibitor selectivity and structure–activity relationships [7]. The design of inhibitors that target the phosphoinositide 3-kinases (PI3K) family has been particularly challenging given the high degree of primary sequence homology shared among the ATP-binding sites of the four PI3K isoforms (a, b, g and d). Although inhibitor-bound structures for the a- and b-isoforms have not been described in the literature, the
0165-6147/$ – see front matter ß 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.tips.2012.03.005 Trends in Pharmacological Sciences, May 2012, Vol. 33, No. 5
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Figure 1. Examples of the three main classes of kinase inhibitors. The protein kinase is shown in grey, with a blue glycine-rich loop (G-loop), an orange activation loop (Aloop) and the side chains of the DFG motif shown as sticks. The key hydrophobic residue in the DFG motif is labelled. Inhibitors and a semi-transparent representation of their van der Waals surfaces are shown in magenta. (a) Type I inhibitors: CK2a bound to CX4945. The inhibitor is bound in the ATP-binding site in the deep cleft between the N- and C-terminal lobes. The A-loop is in a DFG-in conformation (DWG-in in CK2a) and the aC-helix adopts an ‘in’ conformation. (b) Type II inhibitors: Abl bound to Gleevec (imatinib). The inhibitor is bound in the ATP-binding site and extends into the selectivity pocket, causing the A-loop to adopt a DFG-out conformation. The aC-helix adopts an ‘in’ conformation. (c) Type III inhibitors: MEK1 bound to PD318088 and ATP (shown in green). The inhibitor binds in an allosteric pocket adjacent to the ATP-binding site. The A-loop is in a DFG-in conformation and the aC-helix adopts an ‘out’ conformation.
availability of crystal structures of inhibitor-bound g- and disoforms [8,9] has facilitated the development of selective inhibitors. Following the discovery of the PI3K inhibitor GDC-0941, which is somewhat selective for PI3Ka, Heffron et al. at Roche utilised the PI3Ka crystal structure, along with a PI3Kb homology model developed from the PI3Kd crystal structure, to design potent and selective PI3Ka compounds [10]. Differences in sequences at the solventexposed periphery of the ATP-binding site of the kinase were exploited. This work led to identification of a thienopyrimidine scaffold with >100-fold selectivity for PI3Ka over PI3Kb, PI3Kg and PI3Kd. Selectivity can be rationalised by the formation of a key backbone interaction that was suggested by the homology models. This approach was also used to engineer selectivity into the distinct benzoxepin scaffold. A potentially more generalised methodology for attaining selectivity might involve exploitation of differences in the electrostatic potential between the PI3K isoforms in specific regions of the binding pocket rather than targeting of specific kinase backbone interactions. An interesting bioinformatics approach for the rational design of selective kinase inhibitors was recently developed at the University of Zu¨rich [11]. This group defined the ATP-binding site residues for human kinases using structure and sequence-based techniques, leading to the development of ‘kinase selectivity potential networks’. These networks can be used to elaborate optimisation strategies for the generation of selective kinase inhibitors. In addition, a computational approach named profileQSAR was described by a group at Novartis [12]. The technique is based on the idea that the ATP-binding sites of kinases can be approximately described as linear (or nonlinear) combinations of interactions with conserved features related to type, but differing in ‘magnitude’. Predicting the activity of a compound against a new kinase is 274
the result of using previously measured pIC50 values against other kinases for that compound by generating a matrix of Bayesian prediction. Going beyond the ATP-binding site Recent analyses of the spatial arrangement patterns of residues in active and inactive kinases identified a highly conserved spatial motif of four residues in the ATP-binding site that together form a hydrophobic spine (Figure 2a). An intact conformation of this regulatory spine is an underlying structural feature of all kinases in their active conformation and disruption of this arrangement leads to the inactive conformation [13]. ArQule recently described a systematic approach for targeting the regulatory spine in the development of a non-ATP competitive inhibitor (ARQ197) of met proto-oncogene (c-Met) that is currently in Phase III clinical trials for non-small-cell lung cancer. ARQ197 shows exquisite selectivity against a panel of 230 human kinases, of which only Fms-like tyrosine kinase 4 (Flt4), p21-activated kinase 3 (PAK3), pim-1 oncogene (PIM1) and calcium/calmodulin-dependent protein kinase II delta (CAMKIId) are inhibited to any significant degree [14]. The crystal structure of c-Met in complex with ARQ197 shows that inhibitor binding results in the rearrangement of key catalytic residues in the ATP-binding pocket (Figure 2b). The activation loop adopts a DFG-out conformation and the aC-helix is pushed out compared to the active conformation, leading to the formation of a nonpolar pocket that is incompatible with ATP binding [15]. Follow-up studies by Eathiraj et al. involved the construction of models for a range of inactive kinases that were subsequently screened in silico to identify potential inhibitors. ARQ523 and its more potent analogue ARQ069 were identified as inhibitors of fibroblast growth factor receptor 2 (FGFR2) and inhibited only nine out of 96
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Figure 2. Disrupting the kinase regulatory spine. The protein kinase is shown in grey and the four residues that form the regulatory spine are shown as sticks with a yellow semitransparent representation of their van der Waals surfaces. Inhibitors and a semi-transparent representation of their van der Waals surfaces are shown in magenta. (a) Protein kinase A (PKA) bound to ATP (shown in green). PKA is in the active conformation and displays an intact regulatory spine in which the side chains of L95, L106, Y164 and F185 form a hydrophobic stack that is mediated by van der Waals interactions. F185 is in the DFG-in conformation and the aC-helix adopts an ‘in’ conformation. (b) cMet bound to ARQ197. cMet is in an inactive conformation and displays a disrupted regulatory spine in which the side chains of M1131, L1142, H1202 and F1223 do not interact with each other. F1223 packs against the inhibitor and is in the DFG-out conformation. The aC-helix also adopts an ‘out’ conformation. (c) CDK2 bound to JWS648 and two molecules of the fluorophore 8-anilino-1-naphthalene sulfonate (ANS) (shown in pink). JWS648 binds in the ATP-binding site and the two ANS molecules bind in an allosteric pocket that extends from the DFG region to above the aC-helix. CDK2 is in the inactive conformation and has a disrupted regulatory spine in which the side chains of L55, L66, H125 and F146 are prevented from forming a hydrophobic stack by one of the bound ANS molecules. The aC-helix adopts a conformation that is incompatible with binding to the CDK2 cyclin partner cyclin A. (d) CDK8 bound to cyclin C (shown in light purple) and Nexavar (sorafenib). CDK8 is in an inactive conformation and displays a disrupted regulatory spine in which the side chains of L70, L81, H149 and M174 are prevented from forming a hydrophobic stack by the inhibitor. M174 is in the DFG-out conformation (DMG-out in CDK8).
human kinases, four of which are representatives of the FGFR kinase family. ARQ069 was further characterised by biochemical and biophysical methods and displayed slow-off rate kinetics suggesting inhibition of inactive forms of FGFR1 and FGFR2. The crystal structure of ARQ069 in complex with FGFR1 shows a distinct conformation of the glycine-rich loop in which interactions between the inhibitor and residue F489 stabilise the inactive conformation [16]. The development of Gleevec (imatinib), the first marketed drug to access the DFG-out conformation of Abelson tyrosine kinase (Abl), and the structural elucidation of its binding mode [17] led to a search for compounds targeting induced-fit binding pockets in other kinases that are known to adopt a DFG-out conformation [18]. A comparison of the structures of Gleevec, Nexavar (sorafenib) and BIRB-796 in complex with Abl, v-raf murine sarcoma viral
oncogene homologue B1 (b-Raf) and mitogen-activated protein kinase 14 (p38a), respectively, led to the design and synthesis of eight hybrid molecules based on these scaffolds. Enzymatic inhibition data for these hybrids and other known inhibitors provided insight in to which inhibitor substituents and regions of the kinase were essential for achieving potency and selectivity [19]. Namboodiri et al. at Locus Pharmaceuticals determined the binding modes of Gleevec and Nexavar in p38a, and showed that the binding modes were similar to those previously observed in Abl and b-Raf. Biophysical evidence of a faster off-rate for Gleevec compared to Nexavar, coupled with an analysis of the solvent accessible surface area of the ligand, suggested that these factors appear to guide selectivity [20]. One of the main challenges in developing Type II kinase inhibitors remains the determination of crystal structures 275
Review in the DFG-out conformation, or at least a reliable prediction of which kinases are able to adopt this state. This has led to the development of computational approaches that are able to convert known DFG-in structures into accurate and specific DFG-out models [21,22]. These approaches could facilitate screening of large virtual libraries against kinases for which a DFG-out structure has not been described, although it is probable that crystallographic confirmation of the hits will be required. The cyclin-dependent kinases (CDKs) are serine/threonine kinases that, together with their cyclin partners, control cell cycle progression and have been implicated in various diseases. Until recently, CDKs were considered difficult to target with small molecules because structures of CDKs in their active and inactive states showed that the activation loop adopts an exclusively DFG-in conformation [23]. However, recent studies demonstrate that CDK2 can be targeted by small molecules that access an allosteric pocket adjacent to the ATP-binding site that extends from the DFG region to above the aC-helix [23] (Figure 2c). The published structure of the ternary complex between CDK8, Cyclin C and Nexavar was the first to show a DFG-out conformation (DMG-out in CDK8) for a CDK in complex with a small-molecule inhibitor [24] (Figure 2d). This encouraging result shows that kinases for which Type II inhibition was previously believed to be unattainable can undergo DFG motif rearrangements, opening the door to the design of more potent and selective kinase inhibitors. The most prominent example of highly selective Type III inhibitors are the mitogen-activated protein kinase (MEK) inhibitors PD334581 [25] and AZD6244 (ARRY-142886, selumetinib) [26]. Despite evidence suggesting that MEK-like pockets exist in other kinases [27], second-generation Type III inhibitors have not yet entered the clinic. Tackling resistance mutants A resistance mutant is defined as a mutant form of a kinase that displays diminished sensitivity to inhibitors of the wild-type kinase. Overcoming drug resistance has emerged as the greatest challenge of kinase drug discovery against existing targets [28]. The mechanisms of resistance to small-molecule protein kinase inhibitors have been described in an extensive review [29]. Recent progress in this area is highlighted below. The ability to generate mutant forms of aurora kinase A (Aur A) has allowed investigation of the structural basis of MLN8054 selectivity [30]. This work led to identification of a new conformation of the activation loop of Aur A kinase, termed DFG-up. The sequence requirement of the DFG-up conformation is only available in a fraction of kinases, and thus potentially allows for the design of selective inhibitors. Since the launch of imatinib, many resistance mutant kinases have been identified in the clinic. Structural biology has been instrumental in deciphering the molecular drivers for resistance to imatinib. Of the numerous clinically observed Bcr–Abl kinase mutations, the T315I, E255K and M315T mutations account for more than 60% of clinical cases [28]. The gatekeeper T315I mutation has proven to be difficult to overcome. A recent review describes the third generation T315I mutant Bcr–Abl kinase inhibitors [31]. Ponatinib (AP24534), a pan-Bcr–Abl 276
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inhibitor with low nM potency in Ba/F3 cells expressing Bcr–Abl T315I, shows small steric clashes in the co-crystal structure in complex with Bcr–AblT315I [32]. To understand the reduced activity of ponatinib against mutant Bcr–Abl, scientists at ARIAD overlaid the crystal structures of ponatinib bound to both native Bcr–Abl and the Bcr–Abl T315I mutant. The main difference was a conformational change in the N- and C-terminal kinase lobes in the Bcr–Abl T315I mutant associated with a slight outward shift of the inhibitor. Although this movement leads to reduced potency against Bcr–Abl T315I, it also facilitates optimal engagement of hydrophobic moieties of the inhibitor, and thus crucially salvages the binding affinity for the mutant [33]. Over a decade ago it was recognised that a subgroup of human kinases had a conserved cysteine residue in the ATP-binding site that could be targeted by reactive compounds to form covalent adducts [34]. These irreversible inhibitors offer potential for increased potency and selectivity over their reversible counterparts and, importantly, possibility to overcome resistance mechanisms as described for the T790M–L858R double-mutant form of epidermal growth factor receptor (EGFR) [35]. Work by Cohen et al. describes a bioinformatics approach to identify two selectivity filters, a threonine and a cysteine, at key positions in the ATP site of p90 ribosomal protein S6 kinase (RSK), which led to the design of an irreversible inhibitor that selectively targets RSK1 and RSK2 in mammalian cells [36]. Obtaining selectivity through fragment-based approaches Fragment-based drug discovery techniques have been effective method for the development of small-molecule inhibitors against protein kinases. The application of crystallographic techniques to guide growing strategies from an initial fragment lead is now firmly established [37]. However, given their low molecular weight and often weak potency, evaluation of fragment selectivity within the context of the primary biochemical assay remains to be fully established [38,39]. A recent article by researchers at GlaxoSmithKline explores this question in detail and presents a general strategy for evaluating fragment selectivity [40]. In this study, the primary screening data for a kinasefocused screening set against a panel of 30 protein kinases are presented. The authors emphasise the importance of detecting both kinase activity inhibition and target engagement during the high-throughput screen, as well as the application of biochemical assay formats that do not rely on fluorescent readouts, because false-positives can often arise from optical compound interference. It is essential to progress as many fragment hits as possible to a secondary direct-binding biophysical assay, typically surface plasmon resonance (SPR) or NMR, because it is difficult to prioritise fragment hits based solely on ligand efficiency. Substructure searches can then be used to generate structure–activity relationship (SAR) data around the initial fragment hits and to understand how these fragments are bound in crystal structures other kinases. Only validated, chemically tractable binders are subjected to crystallography.
Review As expected, numerous fragment hits were identified from this screen and many were shown to be conventional hinge-binders. However, fragments hits containing selective hinge-binding elements may not have selectivity beyond these interactions, whereas selective inhibitors can more readily be developed from apparently unselective hinge-binding starting points. In conclusion, the selectivity profiles of these initial fragment hits often resembled those of more traditional optimised compounds, suggesting that it should be possible to understand kinase selectivity using a rigorous screening cascade. An interesting technique to achieve kinase selectivity using a fragment-based lead generation method termed ‘tethering’ was recently described by Sunesis Pharmaceuticals [41]. In this study, the development of a potent and highly selective inhibitor of pyruvate dehydrogenase kinase isozyme 1 (PDK1), which binds the DFG-out conformation, is systematically outlined. Tethering utilises the formation of reversible disulfide bonds between an engineered cysteine residue in the protein target and thiolcontaining fragments, which facilitates the identification of low-affinity fragment binders by mass spectrometry. Using an E166C mutant of PDK1, a diaminopyrimidine (DAP) moiety that was previously known to act as the hinge-binding element, was introduced and the crystal structure was determined. A screen was then performed against a library of thiol-containing fragments to search for fragments that bind in the adaptive binding site of PDK1. The relative position of the initial pyridinone hit from the DAP moiety was subsequently modified by introducing various alkyl linkers. Once the optimal linker length had been defined, further increases in potency were obtained by replacing the DAP moiety with purine mimetics as the hinge-binding group. With the methoxyaminopyrimidine hinge-binder, the pyridinone element was then optimised, leading to a highly selective compound with single-digit nanomolar potency. The crystal structure of PDK1 in complex with this inhibitor shows that the cyclic urea group is positioned in the ATP-binding site and as expect, interacts with the hinge region, whereas the fragments identified by the tethering technique are placed in the allosteric DFG-out pocket. New chemical probes A novel approach for obtaining highly selective protein kinase inhibitors has been developed by Meggers et al. [42]. This strategy involves the synthesis of octahedral metal complexes that contain ruthenium (II) or iridium (III). Incorporating these metals into the design of small-molecule kinase inhibitors provides an opportunity to access distinct regions of chemical space that cannot be accessed by traditional organic compounds alone. In this work, stable octahedral metal complexes form the basis for the development of a series of six proof-of-concept inhibitors that are derived from staurosporine, termed octasporines. The authors argue that the octahedral coordinated metals in these octasporines are positioned in a ‘hot spot’ within the ATP-binding pocket that is not too close to the hinge, positioned just at the solvent interface. Although these molecules are conventional ATP-competitive binders, their unique shape and rigidity facilitate specific interactions
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with the glycine-rich loop, which in turn drives potency and selectivity against a panel of protein kinases, including glycogen synthase kinase 3 beta (GSK3b), PAK1, PIM1, death-associated protein kinase 1 (DAPK1), myosin light chain kinase (MLCK) and vascular endothelial growth factor receptor 3 (VEGFR3/FLT4). The first compound, L-OS1, is highly selective for GSK3b (IC50 value of 0.9 nM), and the crystal structure of the complex shows that the rutheniumcoordinated monodentate axial CO ligand that is oriented perpendicular to the pyridocarbazole moiety interacts extensively with the glycine-rich loop of the kinase. Modifications primarily at this position (and others) appear to convert the selectivity profile of the octasporine scaffold, as exemplified by OS4, to be highly selective for DAPK1 (IC50 value of 2.0 nM). As with GSK3b in complex with LOS1, the crystal structure of OS4 bound to DAPK1 revealed extensive interactions with the glycine-rich loop. Taken together, these initial results suggest that potency and selectivity can be rationally engineered into the octasporine scaffold by targeting specific interactions with the normally flexible glycine-rich loops of protein kinases. An extension of this concept was recently applied in the development of a highly photocytotoxic iridium complex [43]. This compound is a potent inhibitor of the vascular endothelial growth factor receptor kinases (VEGFRs), inhibiting VEGFR3 with an IC50 value of 42 nM. Concluding remarks In this review, we focused on some of the recent advances in achieving kinase selectivity achieved using structure-based design and computational tools. Some of the most striking examples include obtaining selectivity between PI3K isoforms and identification of the CK2a inhibitor CX4945. The use of metal complexes in the design of small-molecule kinase inhibitors may provide an opportunity to achieve selectivity by accessing specific conformations of the glycinerich loop found in different kinases. It is arguable that targeting of the ATP-binding pocket is the best approach for achieving selectivity as opposed to allosteric inhibition [44]. However, the CDK2 and PDK1 examples highlighted above suggest that linking and further modification of the structure of initial fragment hits is a viable method for accessing allosteric regions that were previously not fully understood. The crystal structure of cMet in complex with ARQ197 shows that the inhibitor recognises and selectively inhibits the autoinhibited conformation of cMet, which led to the identification of a novel, nonpolar pocket that is incompatible with ATP binding. The applicability of this method of inhibition is exemplified by the successful design of a series of selective FGFR tyrosine kinase family inhibitors that target a similar pocket in FGFR1 and FGFR2. Achieving selective inhibition of kinases has been viewed as one of the highest hurdles in developing kinase inhibitor therapeutics. The challenge involves both identification of inhibitors that inhibit a single kinase and gaining an understanding the cellular phenotype associated with selective inhibition. Chemical tools are needed to address the latter and such tools will need profiling for the level of specificity they achieve [45]. Although achieving single kinase selectivity with an inhibitor may still remain elusive, being able to define and control the number 277
Review and classes of kinases inhibited by a particular molecular entity will continue to be the main objective of medicinal chemistry. This approach is consistent with the emerging concept of multiple kinase inhibitors [46], for which ‘striking the right balance’ requires tools to design the desired selectivity profile. Although not discussed in detail here, the importance of understanding protein–inhibitor binding kinetics should not be underestimated in addressing these challenges. A recent review by Holdgate and Gill [47] describes a variety of kinetic concepts and metrics, and highlights their potential impact on the drug discovery process. References 1 Manning, G. et al. (2002) The protein kinase complement of the human genome. Science 298, 1912–1934 2 Liu, Y. and Gray, N.S. (2006) Rational design of inhibitors that bind to inactive kinase conformations. Nat. Chem. Biol. 2, 358–364 3 Mol, C.D. et al. (2004) Structural insights into the conformational selectivity of STI-571 and related kinase inhibitors. Curr. Opin. Drug Discov. Dev. 7, 639–648 4 Ferguson, A.D. et al. (2011) Structural basis of CX-4945 binding to human protein kinase CK2. FEBS Lett. 585, 104–110 5 Battistutta, R. et al. (2011) Unprecedented selectivity and structural determinants of a new class of protein kinase CK2 inhibitors in clinical trials for the treatment of cancer. Biochemistry 50, 8478–8488 6 Huggins, D.J. et al. (2012) Rational approaches to improving selectivity in drug design. J. Med. Chem. 55, 1424–1444 7 Robinson, D.D. et al. (2010) Understanding kinase selectivity through energetic analysis of binding site waters. Chem. Med. Chem. 5, 618–627 8 Vadas, O. et al. (2011) Structural basis for activation and inhibition of class I phosphoinositide 3-kinases. Sci. Signaling 4, 1–12 9 Berndt, A. et al. (2010) The p110d structure: mechanisms for selectivity and potency of new PI(3)K inhibitors. Nat. Chem. Biol. 6, 117–124 10 Heffron, T. et al. (2011) Rational design of phosphoinositide 3-kinase a inhibitors that exhibit selectivity over the phosphoinositide 3-kinase b isoform. J. Med. Chem. 54, 7815–7833 11 Huang, D. et al. (2010) Kinase selectivity potential for inhibitors targeting the ATP binding site: a network analysis. Bioinformatics 26, 198–204 12 Martin, E. et al. (2011) Profile-QSAR: a novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity. J. Chem. Inf. Model. 51, 1942–1956 13 Taylor, S.S. and Kornev, A.P. (2011) Protein kinases: evolution of dynamic regulatory proteins. Trends Biochem. Sci. 36, 65–77 14 Munshi, N. et al. (2010) ARQ 197, a novel and selective inhibitor of the human c-Met receptor tyrosine kinase with antitumor activity. Mol. Cancer Ther. 9, 1544–1553 15 Eathiraj, S. et al. (2011) Discovery of a novel mode of protein kinase inhibition characterised by the mechanism of inhibition of human mesenchymal-epithelial transition factor (c-Met) protein autophosphorylation by ARQ 197. J. Biol. Chem. 286, 20666–20676 16 Eathiraj, S. et al. (2011) A novel mode of protein kinase inhibition exploiting hydrophobic motifs of auto-inhibited kinases: discovery of ATP independent inhibitors of fibroblast growth factor receptor (FGFR). J. Biol. Chem. 286, 20677–20687 17 Schindler, T. et al. (2000) Structural mechanism for STI-571 inhibition of Abelson tyrosine kinase. Science 289, 1938–1942 18 Gray, N.S. (2006) Rational design of inhibitors that bind to inactive kinase conformations Nat. Chem. Biol. 2, 358–364 19 Dietrich, J. et al. (2010) The design, synthesis, and evaluation of 8 hybrid DFG-out allosteric kinase inhibitors: a structural analysis of the binding interactions of Gleevec, Nexavar, and BIRB-796. Bioorg. Med. Chem. 18, 5738–5748 20 Namboodiri, H.V. et al. (2010) Analysis of imatinib and sorafenib binding to p38a compared with c-Abl and b-Raf provides structural insights for the understanding the selectivity of inhibitors targeting the DFG-out form of protein kinases. Biochemistry 49, 3611–3618
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21 Kufareva, I. and Abagyan, R. (2008) Type-II kinase inhibitor docking, screening, and profiling using modified structures of active kinase states. J. Med. Chem. 51, 7921–7932 22 Xu, M. et al. (2011) Predicting inactive conformations of protein kinases using active structures: conformational selection of Type-II inhibitors. PLoS ONE 6, e22644 23 Betzi, S. et al. (2011) Discovery of a potential allosteric ligand binding site in CDK2. ACS Chem. Biol. 6, 492–501 24 Schneider, E.V. et al. (2011) The structure of CDK8/CycC implicates specificity in the CDK/Cyclin family and reveals interaction with a deep pocket binder. J. Mol. Biol. 412, 251–266 25 Ohren, J.F. et al. (2004) Structures of human MAP kinase kinase 1 (MEK1) and MEK2 describe novel noncompetitive kinase inhibition. Nat. Struct. Mol. Biol. 11, 1192–1197 26 Yeh, T. et al. (2007) Biological characterization of ARRY-142886 (AZD6244), a potent, highly selective mitogen-activated protein kinase kinase 1/2 inhibitor. Clin. Cancer Res. 13, 1576–1583 27 Tecle, H. et al. (2009) Beyond the MEK-pocket: can current MEK kinase inhibitors be utilized to synthesize novel type III NCKIs? Does the MEK-pocket exist in kinases other than MEK? Bioorg. Med. Chem. Lett. 19, 226–269 28 Bikker, J.A. (2009) Kinase domain mutations in cancer: implications for small molecule drug design strategies. J. Med. Chem. 52, 1493–1509 29 Maly, D.J. (2010) Biochemical mechanisms of resistance to smallmolecule protein kinase inhibitors. ACS Chem. Biol. 5, 121–138 30 Dodson, C.A. et al. (2010) Crystal structure of an Aurora-A mutant that mimics Aurora-B bound to MLN8054: insights into selectivity and drug design. Biochem. J. 427, 19–28 31 Lu, X.Y. et al. (2011) Recent developments in the third generation inhibitors of Bcr-Abl for overriding T315I mutation. Curr. Med. Chem. 18, 2146–2157 32 O’Hare, T. et al. (2009) AP24534, a Pan-BCR-ABL inhibitor for chronic myeloid leukemia, potently inhibits the T315I mutant and overcomes mutation-based resistance. Cancer Cell 16, 401–412 33 Zhou, T. et al. (2011) Structural mechanism of the pan-BCR-ABL inhibitor ponatinib (AP24534): lessons for overcoming kinase inhibitor resistance. Chem. Biol. Drug Des. 77, 1–11 34 Singh, J. et al. (1997) Structure-based design of a potent, selective, and irreversible inhibitor of the catalytic domain of the ErbB receptor subfamily of protein tyrosine kinases. J. Med. Chem. 40, 1130–1135 35 Singh, J. et al. (2011) The resurgence of covalent drugs. Nat. Rev. Drug Discov. 10, 307–317 36 Cohen, M.S. et al. (2005) Structural bioinformatics-based design of selective, irreversible kinase inhibitors. Science 308, 1318–1321 37 Murray, C.W. and Blundell, T.L. (2010) Structural biology in fragmentbased drug design. Curr. Opin. Struct. Biol. 20, 497–507 38 Chen, Y. and Shoichet, B.K. (2009) Molecular docking and ligand specificity in fragment-based inhibitor discovery. Nat. Chem. Biol. 5, 358–364 39 Barelier, S. et al. (2010) Ligand specificity in fragment-based drug design. J. Med. Chem. 53, 5256–5266 40 Bamborough, P. et al. (2011) Selectivity of kinase inhibitor fragments. J. Med. Chem. 54, 5131–5143 41 Erlanson, D.A. et al. (2011) Discovery of a potent and highly selective PDK1 inhibitor via fragment-based drug discovery. Bioorg. Med. Chem. Lett. 21, 3078–3083 42 Feng, L. et al. (2011) Structurally sophisticated octahedral metal complexes as highly selective protein kinase inhibitors. J. Am. Chem. Soc. 133, 5976–5986 43 Kastl, A. et al. (2012) Dual anticancer activity in a single compound: visible-light-induced apoptosis by an antiangiogenic iridium complex. Chem. Commun. 48, 1863–1865 44 Cox, K.J. et al. (2011) Tinkering outside the kinase ATP box: allosteric (type IV) and bivalent (type V) inhibitors of protein kinases. Future Med. Chem. 3, 29–43 45 Cohen, P. (1999) The development and therapeutic potential of protein kinase inhibitors. Curr. Opin. Chem. Biol. 3, 459–465 46 Morphy, R. (2010) Selectively nonselective kinase inhibition: striking the right balance. J. Med. Chem. 53, 1413–1437 47 Holdgate, G.A. and Gill, A.L. (2011) Kinetic efficiency: the missing metric for enhancing compound quality? Drug Discov. Today 16, 910–913
Structural approaches to obtain kinase selectivity Richard A. Norman1, Dorin Toader2 and Andrew D. Ferguson3 1
Discovery Sciences, AstraZeneca, Mereside, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK Oncology iMED, AstraZeneca, 35 Gatehouse Drive, Waltham, MA 02451, USA 3 Discovery Sciences, AstraZeneca, 35 Gatehouse Drive, Waltham, MA 02451, USA 2
One of the grand challenges in kinase drug discovery is the design of small-molecule inhibitors with selectivity profiles that will ultimately be efficacious in the clinic. Current medicinal chemistry strategies make heavy use of structural, biophysical and computational approaches to achieve this multi-faceted goal. Here we review structure-based approaches underlying the development of several molecules that are currently in clinical trials, including the cMet inhibitor ARQ197 and the Bcr–Abl inhibitor ponatinib. We highlight the challenge posed by the emergence of resistance mutants and discuss promising lead generation strategies to obtain selective inhibitors of protein and lipid kinases such as targeting of specific sites, the use of fragment-based approaches and new chemical probes based on metal complexes. Protein kinases and inhibitor classes Human protein kinases control a plethora of signal transduction networks that are crucial in the regulation of critical cellular processes, including cell growth, metabolism and division [1]. Dysregulation of these pathways has been shown to be a causative factor in human disease, making protein kinases important targets for drug discovery for the pharmaceutical industry. The catalytic activity of protein kinases is mediated by ATP, which binds in a cleft between the N- and C-terminal lobes of a single domain (Figure 1a–c). Because the primary sequence and three-dimensional structures of kinases are similar, the development of selective inhibitors that exhibit minimal off-target activity can be challenging. Three main classes of kinase inhibitors (Types I, II and III) have been defined. Type I inhibitors target the active conformation of the kinase and directly compete with ATP binding (Figure 1a). The majority of reported kinase inhibitors are Type I, making the identification of novel intellectual property difficult. Type II inhibitors access an induced-fit hydrophobic pocket adjacent to the ATP-binding site (Figure 1b). This pocket is formed by a change in the conformation of the DFG motif (located at the start of the activation loop) from an active DFG-in conformation to an inactive DFG-out conformation that has lower affinity for ATP [2]. Inhibitors targeting the DFG-out conformation do not compete directly with ATP binding, and hence cellular potency and selectivity may be easier to obtain [3]. Type III inhibitors tend to be more selective than Types I and II, Corresponding author: Norman, R.A. ([email protected])
because they are ATP-noncompetitive and bind exclusively to sites outside the ATP-binding site (Figure 1c). Here we present several examples of structure-based approaches utilising crystallographic, biophysical and computational methods to rationally develop selective inhibitors, many of which have now reached the clinic. We also highlight some specific lead generation strategies that have been applied in the development of selective kinase inhibitors. Targeting the ATP-binding site Casein kinase II alpha (CK2a) is a constitutively active serine/threonine kinase that is involved in a variety of pathways essential for the maintenance of cellular homeostasis. A new class of highly selective, orally available CK2a inhibitors from Cylene Pharmaceuticals, exemplified by CX4945, recently entered Phase I clinical trials for advanced solid tumours and multiple myeloma. The high-resolution crystal structures of human CK2a in complex with CX4945 and two analogues, CX5011 and CX5279, revealed the structural determinants of the exquisite selectivity of this scaffold, which is driven by an intricate series of direct and water-mediated interactions with CK2a [4,5]. This example illustrates how the primary sequence, shape, electrostatics and flexibility of the ATP-binding site must be considered when designing inhibitor selectivity, and that determining whether water molecules should be displaced or exploited into forming bridging interactions between the inhibitor and the protein can be very challenging. Several methodologies for characterising water molecules have been developed and are reviewed extensively by Huggins et al. [6]. In particular, the work carried out at Schro¨dinger Inc. highlights the importance of understanding the water structure within the ATP-binding site of kinases when designing selective inhibitors. Using a computational method called WaterMap, which calculates the desolvation energy of the receptor, the locations and thermodynamic properties of water molecules were predicted for four different kinase systems. This information allowed the rationalisation of previously unexplained kinase inhibitor selectivity and structure–activity relationships [7]. The design of inhibitors that target the phosphoinositide 3-kinases (PI3K) family has been particularly challenging given the high degree of primary sequence homology shared among the ATP-binding sites of the four PI3K isoforms (a, b, g and d). Although inhibitor-bound structures for the a- and b-isoforms have not been described in the literature, the
0165-6147/$ – see front matter ß 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.tips.2012.03.005 Trends in Pharmacological Sciences, May 2012, Vol. 33, No. 5
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Figure 1. Examples of the three main classes of kinase inhibitors. The protein kinase is shown in grey, with a blue glycine-rich loop (G-loop), an orange activation loop (Aloop) and the side chains of the DFG motif shown as sticks. The key hydrophobic residue in the DFG motif is labelled. Inhibitors and a semi-transparent representation of their van der Waals surfaces are shown in magenta. (a) Type I inhibitors: CK2a bound to CX4945. The inhibitor is bound in the ATP-binding site in the deep cleft between the N- and C-terminal lobes. The A-loop is in a DFG-in conformation (DWG-in in CK2a) and the aC-helix adopts an ‘in’ conformation. (b) Type II inhibitors: Abl bound to Gleevec (imatinib). The inhibitor is bound in the ATP-binding site and extends into the selectivity pocket, causing the A-loop to adopt a DFG-out conformation. The aC-helix adopts an ‘in’ conformation. (c) Type III inhibitors: MEK1 bound to PD318088 and ATP (shown in green). The inhibitor binds in an allosteric pocket adjacent to the ATP-binding site. The A-loop is in a DFG-in conformation and the aC-helix adopts an ‘out’ conformation.
availability of crystal structures of inhibitor-bound g- and disoforms [8,9] has facilitated the development of selective inhibitors. Following the discovery of the PI3K inhibitor GDC-0941, which is somewhat selective for PI3Ka, Heffron et al. at Roche utilised the PI3Ka crystal structure, along with a PI3Kb homology model developed from the PI3Kd crystal structure, to design potent and selective PI3Ka compounds [10]. Differences in sequences at the solventexposed periphery of the ATP-binding site of the kinase were exploited. This work led to identification of a thienopyrimidine scaffold with >100-fold selectivity for PI3Ka over PI3Kb, PI3Kg and PI3Kd. Selectivity can be rationalised by the formation of a key backbone interaction that was suggested by the homology models. This approach was also used to engineer selectivity into the distinct benzoxepin scaffold. A potentially more generalised methodology for attaining selectivity might involve exploitation of differences in the electrostatic potential between the PI3K isoforms in specific regions of the binding pocket rather than targeting of specific kinase backbone interactions. An interesting bioinformatics approach for the rational design of selective kinase inhibitors was recently developed at the University of Zu¨rich [11]. This group defined the ATP-binding site residues for human kinases using structure and sequence-based techniques, leading to the development of ‘kinase selectivity potential networks’. These networks can be used to elaborate optimisation strategies for the generation of selective kinase inhibitors. In addition, a computational approach named profileQSAR was described by a group at Novartis [12]. The technique is based on the idea that the ATP-binding sites of kinases can be approximately described as linear (or nonlinear) combinations of interactions with conserved features related to type, but differing in ‘magnitude’. Predicting the activity of a compound against a new kinase is 274
the result of using previously measured pIC50 values against other kinases for that compound by generating a matrix of Bayesian prediction. Going beyond the ATP-binding site Recent analyses of the spatial arrangement patterns of residues in active and inactive kinases identified a highly conserved spatial motif of four residues in the ATP-binding site that together form a hydrophobic spine (Figure 2a). An intact conformation of this regulatory spine is an underlying structural feature of all kinases in their active conformation and disruption of this arrangement leads to the inactive conformation [13]. ArQule recently described a systematic approach for targeting the regulatory spine in the development of a non-ATP competitive inhibitor (ARQ197) of met proto-oncogene (c-Met) that is currently in Phase III clinical trials for non-small-cell lung cancer. ARQ197 shows exquisite selectivity against a panel of 230 human kinases, of which only Fms-like tyrosine kinase 4 (Flt4), p21-activated kinase 3 (PAK3), pim-1 oncogene (PIM1) and calcium/calmodulin-dependent protein kinase II delta (CAMKIId) are inhibited to any significant degree [14]. The crystal structure of c-Met in complex with ARQ197 shows that inhibitor binding results in the rearrangement of key catalytic residues in the ATP-binding pocket (Figure 2b). The activation loop adopts a DFG-out conformation and the aC-helix is pushed out compared to the active conformation, leading to the formation of a nonpolar pocket that is incompatible with ATP binding [15]. Follow-up studies by Eathiraj et al. involved the construction of models for a range of inactive kinases that were subsequently screened in silico to identify potential inhibitors. ARQ523 and its more potent analogue ARQ069 were identified as inhibitors of fibroblast growth factor receptor 2 (FGFR2) and inhibited only nine out of 96
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Figure 2. Disrupting the kinase regulatory spine. The protein kinase is shown in grey and the four residues that form the regulatory spine are shown as sticks with a yellow semitransparent representation of their van der Waals surfaces. Inhibitors and a semi-transparent representation of their van der Waals surfaces are shown in magenta. (a) Protein kinase A (PKA) bound to ATP (shown in green). PKA is in the active conformation and displays an intact regulatory spine in which the side chains of L95, L106, Y164 and F185 form a hydrophobic stack that is mediated by van der Waals interactions. F185 is in the DFG-in conformation and the aC-helix adopts an ‘in’ conformation. (b) cMet bound to ARQ197. cMet is in an inactive conformation and displays a disrupted regulatory spine in which the side chains of M1131, L1142, H1202 and F1223 do not interact with each other. F1223 packs against the inhibitor and is in the DFG-out conformation. The aC-helix also adopts an ‘out’ conformation. (c) CDK2 bound to JWS648 and two molecules of the fluorophore 8-anilino-1-naphthalene sulfonate (ANS) (shown in pink). JWS648 binds in the ATP-binding site and the two ANS molecules bind in an allosteric pocket that extends from the DFG region to above the aC-helix. CDK2 is in the inactive conformation and has a disrupted regulatory spine in which the side chains of L55, L66, H125 and F146 are prevented from forming a hydrophobic stack by one of the bound ANS molecules. The aC-helix adopts a conformation that is incompatible with binding to the CDK2 cyclin partner cyclin A. (d) CDK8 bound to cyclin C (shown in light purple) and Nexavar (sorafenib). CDK8 is in an inactive conformation and displays a disrupted regulatory spine in which the side chains of L70, L81, H149 and M174 are prevented from forming a hydrophobic stack by the inhibitor. M174 is in the DFG-out conformation (DMG-out in CDK8).
human kinases, four of which are representatives of the FGFR kinase family. ARQ069 was further characterised by biochemical and biophysical methods and displayed slow-off rate kinetics suggesting inhibition of inactive forms of FGFR1 and FGFR2. The crystal structure of ARQ069 in complex with FGFR1 shows a distinct conformation of the glycine-rich loop in which interactions between the inhibitor and residue F489 stabilise the inactive conformation [16]. The development of Gleevec (imatinib), the first marketed drug to access the DFG-out conformation of Abelson tyrosine kinase (Abl), and the structural elucidation of its binding mode [17] led to a search for compounds targeting induced-fit binding pockets in other kinases that are known to adopt a DFG-out conformation [18]. A comparison of the structures of Gleevec, Nexavar (sorafenib) and BIRB-796 in complex with Abl, v-raf murine sarcoma viral
oncogene homologue B1 (b-Raf) and mitogen-activated protein kinase 14 (p38a), respectively, led to the design and synthesis of eight hybrid molecules based on these scaffolds. Enzymatic inhibition data for these hybrids and other known inhibitors provided insight in to which inhibitor substituents and regions of the kinase were essential for achieving potency and selectivity [19]. Namboodiri et al. at Locus Pharmaceuticals determined the binding modes of Gleevec and Nexavar in p38a, and showed that the binding modes were similar to those previously observed in Abl and b-Raf. Biophysical evidence of a faster off-rate for Gleevec compared to Nexavar, coupled with an analysis of the solvent accessible surface area of the ligand, suggested that these factors appear to guide selectivity [20]. One of the main challenges in developing Type II kinase inhibitors remains the determination of crystal structures 275
Review in the DFG-out conformation, or at least a reliable prediction of which kinases are able to adopt this state. This has led to the development of computational approaches that are able to convert known DFG-in structures into accurate and specific DFG-out models [21,22]. These approaches could facilitate screening of large virtual libraries against kinases for which a DFG-out structure has not been described, although it is probable that crystallographic confirmation of the hits will be required. The cyclin-dependent kinases (CDKs) are serine/threonine kinases that, together with their cyclin partners, control cell cycle progression and have been implicated in various diseases. Until recently, CDKs were considered difficult to target with small molecules because structures of CDKs in their active and inactive states showed that the activation loop adopts an exclusively DFG-in conformation [23]. However, recent studies demonstrate that CDK2 can be targeted by small molecules that access an allosteric pocket adjacent to the ATP-binding site that extends from the DFG region to above the aC-helix [23] (Figure 2c). The published structure of the ternary complex between CDK8, Cyclin C and Nexavar was the first to show a DFG-out conformation (DMG-out in CDK8) for a CDK in complex with a small-molecule inhibitor [24] (Figure 2d). This encouraging result shows that kinases for which Type II inhibition was previously believed to be unattainable can undergo DFG motif rearrangements, opening the door to the design of more potent and selective kinase inhibitors. The most prominent example of highly selective Type III inhibitors are the mitogen-activated protein kinase (MEK) inhibitors PD334581 [25] and AZD6244 (ARRY-142886, selumetinib) [26]. Despite evidence suggesting that MEK-like pockets exist in other kinases [27], second-generation Type III inhibitors have not yet entered the clinic. Tackling resistance mutants A resistance mutant is defined as a mutant form of a kinase that displays diminished sensitivity to inhibitors of the wild-type kinase. Overcoming drug resistance has emerged as the greatest challenge of kinase drug discovery against existing targets [28]. The mechanisms of resistance to small-molecule protein kinase inhibitors have been described in an extensive review [29]. Recent progress in this area is highlighted below. The ability to generate mutant forms of aurora kinase A (Aur A) has allowed investigation of the structural basis of MLN8054 selectivity [30]. This work led to identification of a new conformation of the activation loop of Aur A kinase, termed DFG-up. The sequence requirement of the DFG-up conformation is only available in a fraction of kinases, and thus potentially allows for the design of selective inhibitors. Since the launch of imatinib, many resistance mutant kinases have been identified in the clinic. Structural biology has been instrumental in deciphering the molecular drivers for resistance to imatinib. Of the numerous clinically observed Bcr–Abl kinase mutations, the T315I, E255K and M315T mutations account for more than 60% of clinical cases [28]. The gatekeeper T315I mutation has proven to be difficult to overcome. A recent review describes the third generation T315I mutant Bcr–Abl kinase inhibitors [31]. Ponatinib (AP24534), a pan-Bcr–Abl 276
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inhibitor with low nM potency in Ba/F3 cells expressing Bcr–Abl T315I, shows small steric clashes in the co-crystal structure in complex with Bcr–AblT315I [32]. To understand the reduced activity of ponatinib against mutant Bcr–Abl, scientists at ARIAD overlaid the crystal structures of ponatinib bound to both native Bcr–Abl and the Bcr–Abl T315I mutant. The main difference was a conformational change in the N- and C-terminal kinase lobes in the Bcr–Abl T315I mutant associated with a slight outward shift of the inhibitor. Although this movement leads to reduced potency against Bcr–Abl T315I, it also facilitates optimal engagement of hydrophobic moieties of the inhibitor, and thus crucially salvages the binding affinity for the mutant [33]. Over a decade ago it was recognised that a subgroup of human kinases had a conserved cysteine residue in the ATP-binding site that could be targeted by reactive compounds to form covalent adducts [34]. These irreversible inhibitors offer potential for increased potency and selectivity over their reversible counterparts and, importantly, possibility to overcome resistance mechanisms as described for the T790M–L858R double-mutant form of epidermal growth factor receptor (EGFR) [35]. Work by Cohen et al. describes a bioinformatics approach to identify two selectivity filters, a threonine and a cysteine, at key positions in the ATP site of p90 ribosomal protein S6 kinase (RSK), which led to the design of an irreversible inhibitor that selectively targets RSK1 and RSK2 in mammalian cells [36]. Obtaining selectivity through fragment-based approaches Fragment-based drug discovery techniques have been effective method for the development of small-molecule inhibitors against protein kinases. The application of crystallographic techniques to guide growing strategies from an initial fragment lead is now firmly established [37]. However, given their low molecular weight and often weak potency, evaluation of fragment selectivity within the context of the primary biochemical assay remains to be fully established [38,39]. A recent article by researchers at GlaxoSmithKline explores this question in detail and presents a general strategy for evaluating fragment selectivity [40]. In this study, the primary screening data for a kinasefocused screening set against a panel of 30 protein kinases are presented. The authors emphasise the importance of detecting both kinase activity inhibition and target engagement during the high-throughput screen, as well as the application of biochemical assay formats that do not rely on fluorescent readouts, because false-positives can often arise from optical compound interference. It is essential to progress as many fragment hits as possible to a secondary direct-binding biophysical assay, typically surface plasmon resonance (SPR) or NMR, because it is difficult to prioritise fragment hits based solely on ligand efficiency. Substructure searches can then be used to generate structure–activity relationship (SAR) data around the initial fragment hits and to understand how these fragments are bound in crystal structures other kinases. Only validated, chemically tractable binders are subjected to crystallography.
Review As expected, numerous fragment hits were identified from this screen and many were shown to be conventional hinge-binders. However, fragments hits containing selective hinge-binding elements may not have selectivity beyond these interactions, whereas selective inhibitors can more readily be developed from apparently unselective hinge-binding starting points. In conclusion, the selectivity profiles of these initial fragment hits often resembled those of more traditional optimised compounds, suggesting that it should be possible to understand kinase selectivity using a rigorous screening cascade. An interesting technique to achieve kinase selectivity using a fragment-based lead generation method termed ‘tethering’ was recently described by Sunesis Pharmaceuticals [41]. In this study, the development of a potent and highly selective inhibitor of pyruvate dehydrogenase kinase isozyme 1 (PDK1), which binds the DFG-out conformation, is systematically outlined. Tethering utilises the formation of reversible disulfide bonds between an engineered cysteine residue in the protein target and thiolcontaining fragments, which facilitates the identification of low-affinity fragment binders by mass spectrometry. Using an E166C mutant of PDK1, a diaminopyrimidine (DAP) moiety that was previously known to act as the hinge-binding element, was introduced and the crystal structure was determined. A screen was then performed against a library of thiol-containing fragments to search for fragments that bind in the adaptive binding site of PDK1. The relative position of the initial pyridinone hit from the DAP moiety was subsequently modified by introducing various alkyl linkers. Once the optimal linker length had been defined, further increases in potency were obtained by replacing the DAP moiety with purine mimetics as the hinge-binding group. With the methoxyaminopyrimidine hinge-binder, the pyridinone element was then optimised, leading to a highly selective compound with single-digit nanomolar potency. The crystal structure of PDK1 in complex with this inhibitor shows that the cyclic urea group is positioned in the ATP-binding site and as expect, interacts with the hinge region, whereas the fragments identified by the tethering technique are placed in the allosteric DFG-out pocket. New chemical probes A novel approach for obtaining highly selective protein kinase inhibitors has been developed by Meggers et al. [42]. This strategy involves the synthesis of octahedral metal complexes that contain ruthenium (II) or iridium (III). Incorporating these metals into the design of small-molecule kinase inhibitors provides an opportunity to access distinct regions of chemical space that cannot be accessed by traditional organic compounds alone. In this work, stable octahedral metal complexes form the basis for the development of a series of six proof-of-concept inhibitors that are derived from staurosporine, termed octasporines. The authors argue that the octahedral coordinated metals in these octasporines are positioned in a ‘hot spot’ within the ATP-binding pocket that is not too close to the hinge, positioned just at the solvent interface. Although these molecules are conventional ATP-competitive binders, their unique shape and rigidity facilitate specific interactions
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with the glycine-rich loop, which in turn drives potency and selectivity against a panel of protein kinases, including glycogen synthase kinase 3 beta (GSK3b), PAK1, PIM1, death-associated protein kinase 1 (DAPK1), myosin light chain kinase (MLCK) and vascular endothelial growth factor receptor 3 (VEGFR3/FLT4). The first compound, L-OS1, is highly selective for GSK3b (IC50 value of 0.9 nM), and the crystal structure of the complex shows that the rutheniumcoordinated monodentate axial CO ligand that is oriented perpendicular to the pyridocarbazole moiety interacts extensively with the glycine-rich loop of the kinase. Modifications primarily at this position (and others) appear to convert the selectivity profile of the octasporine scaffold, as exemplified by OS4, to be highly selective for DAPK1 (IC50 value of 2.0 nM). As with GSK3b in complex with LOS1, the crystal structure of OS4 bound to DAPK1 revealed extensive interactions with the glycine-rich loop. Taken together, these initial results suggest that potency and selectivity can be rationally engineered into the octasporine scaffold by targeting specific interactions with the normally flexible glycine-rich loops of protein kinases. An extension of this concept was recently applied in the development of a highly photocytotoxic iridium complex [43]. This compound is a potent inhibitor of the vascular endothelial growth factor receptor kinases (VEGFRs), inhibiting VEGFR3 with an IC50 value of 42 nM. Concluding remarks In this review, we focused on some of the recent advances in achieving kinase selectivity achieved using structure-based design and computational tools. Some of the most striking examples include obtaining selectivity between PI3K isoforms and identification of the CK2a inhibitor CX4945. The use of metal complexes in the design of small-molecule kinase inhibitors may provide an opportunity to achieve selectivity by accessing specific conformations of the glycinerich loop found in different kinases. It is arguable that targeting of the ATP-binding pocket is the best approach for achieving selectivity as opposed to allosteric inhibition [44]. However, the CDK2 and PDK1 examples highlighted above suggest that linking and further modification of the structure of initial fragment hits is a viable method for accessing allosteric regions that were previously not fully understood. The crystal structure of cMet in complex with ARQ197 shows that the inhibitor recognises and selectively inhibits the autoinhibited conformation of cMet, which led to the identification of a novel, nonpolar pocket that is incompatible with ATP binding. The applicability of this method of inhibition is exemplified by the successful design of a series of selective FGFR tyrosine kinase family inhibitors that target a similar pocket in FGFR1 and FGFR2. Achieving selective inhibition of kinases has been viewed as one of the highest hurdles in developing kinase inhibitor therapeutics. The challenge involves both identification of inhibitors that inhibit a single kinase and gaining an understanding the cellular phenotype associated with selective inhibition. Chemical tools are needed to address the latter and such tools will need profiling for the level of specificity they achieve [45]. Although achieving single kinase selectivity with an inhibitor may still remain elusive, being able to define and control the number 277
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