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Dual Kinase-Bromodomain Inhibitors in Anticancer Drug Discovery: A Structural and Pharmacological Perspective Miniperspective Luca Carlino and Giulio Rastelli* Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy ABSTRACT: Protein kinases play crucial roles in several cell transformation processes and are validated drug targets for many human diseases, including cancer. Nevertheless, most tumors have eluded the effects of inhibition of a single kinase by activating resistance mechanisms and/or alternative pathways and escape mechanisms. In recent years, multitarget approaches directed toward inhibition of kinases and targets of different families have received increasing attention. In particular, co-targeting kinases and bromodomain epigenetic reader proteins has rapidly emerged as a promising approach to cancer drug development. In this manuscript, we will review the recent discoveries that led to the identification and optimization of dual kinase/bromodomain inhibitors. We will analyze and compare the structural features required for dual inhibition and comment on the potential of this approach in anticancer drug discovery. Moreover, we will introduce computational approaches useful for the identification of dual kinase/ bromodomain inhibitors and generate ad hoc pharmacophore and docking models.
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INTRODUCTION Cancer has become one of the leading causes of death worldwide, with 8.2 million cancer related deaths in 2012 and new cases expected to rise to 22 million in the next 2 decades.1 Despite the considerable progress that has been made in cancer therapy, fighting this disease remains a major challenge. In fact, more effective therapeutic approaches are still needed to increase the arsenal of “weapons” at our disposal. In 2002, Cohen defined protein kinases as the “targets of the twenty-first century” based on their involvement in most aspects of cell function and aberrant growth.2 Protein kinases represent one of the largest protein families in the entire human genome.3 They are involved in intracellular signaling processes, catalyzing the transfer of the γ-phosphate of ATP to downstream protein substrates.4 Kinase activity is regulated by phosphorylation of specific residues involved in the catalytic reaction and is crucial for cellular growth and differentiation.5 Protein kinases are considered the main actors in several cell transformation processes and human pathologies, including cancer, inflammation, neurological and endocrine disorders, immunodeficiency, and cardiovascular diseases.6 Structurally, protein kinases exist in an “on” state, in which the protein displays full phosphorylation capability and a conserved three-dimensional structure with an accessible active site, and an “off” state, in which the protein is inactive and adopts different conformational states depending on the mechanism by which the active site is blocked.7−9 Protein kinases are formed by two distinct lobes connected by a flexible © 2016 American Chemical Society
hinge region. The N-lobe (N-terminal domain) is composed of five-stranded β-sheets and one α helix (αC helix), whereas the C-lobe (C-terminal domain) is mainly composed of α-helices. The active site is located between the two lobes and contains the ATP and substrate binding pockets. Traditionally, the development of kinase inhibitors has been strongly focused on the identification of ATP competitive (type I) inhibitors.10,11 Although many potent type I ligands have been identified, some of which are on the market, focusing on the ATP site proved to have major limitations such as drug resistance due to mutations or the activation of alternative pathways, poor selectivity among kinases due to the high conservation of the ATP binding site, and inhibitor displacement as a result of high intracellular ATP concentrations.12 These disadvantages are only partially avoided by the development of new generations of ATP competitors that extend into additional cavities in proximity to the ATP-binding pocket, such as type II inhibitors, which bind to an inactive conformation in which the DFG motif is flipped outward (DFG-out conformation).11,13,14 Furthermore, truly allosteric compounds targeting allosteric pockets in proximity to the ATP site (type III inhibitors) or other inhibitors that stabilize the protein in an inactive conformation through binding to allosteric sites distal to the ATP binding pocket (type IV inhibitors) have been reported.12,15−18 However, despite the Received: March 24, 2016 Published: August 25, 2016 9305
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Figure 1. Chemical structures of kinase inhibitors, BET inhibitors, and dual kinase/BET inhibitors.
huge investments and the large arsenal at our disposal, fighting cancer with kinase inhibitors is still severely hampered by the fact that most tumors can escape from inhibition of a single kinase.19 This is mainly due to resistance mechanisms, such as the mutation of the target, the activation of surrogate kinases, or the modulation of pathway components.10,20−22 Cancer resistance mechanisms are associated with known protein kinase inhibitors23 but may also arise from drugs that hit newer
anticancer targets, such as bromodomain epigenetic reader proteins (BRDs). For instance, mechanisms leading to BRD inhibitor resistance in leukemia stem cells and in triple-negative breast cancer cells (TNBCs) have been previously reported.24−26 In leukemia stem cells, resistance may arise through cancer cell adaptation processes that are facilitated by inactivation of the polycomb repressive complex 2 (PRC2) as well as by the presence of a subpopulation of cells with 9306
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structural similarity among kinases, developing intrafamily polypharmacological drugs able to selectively bind desired combinations of kinases is difficult and generally prone to offtarget effects and side effects.27
intrinsically increased expression of the WPT/β-catenin pathway. In TNBC, resistance to BRD inhibitors has not been fully explained, although epigenetic mechanisms have been described.24−26 Newer approaches in drug discovery, comprising drugs able to hit multiple targets, have been proposed as possible solution to these problems. Polypharmacological approaches include the concomitant inhibition of targets involved in the same or in multiple disease pathways.19,27−29 In both cases, rational polypharmacological approaches require a thorough understanding of the disease pathway and target interconnections, which is difficult to achieve and thus remains a major challenge.28 In the past years, co-targeting kinases and BRDs has emerged as a promising approach to cancer drug development. In this manuscript, we will review the recent discoveries that led to the identification and optimization of dual kinase/BRD inhibitors. We will analyze and compare the structural features required for dual inhibition and comment on the potential of this approach in anticancer drug discovery. Moreover, we will introduce computational approaches useful for the identification of dual kinase/BRD inhibitors and generate ad hoc pharmacophore and docking models.
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BROMODOMAINS: STRUCTURES AND INHIBITORS BRDs have recently been discovered as druggable targets in tumorigenesis and inflammatory diseases.41−43 In vivo, gene transcriptional activation/repression is regulated by modifications to chromatin fibers. Covalent modifications of histones, the basic unit of chromatin, are involved in the so-called epigenetic code, being responsible for the control of chromatin fiber compactness.42 Proteins involved in the regulation of this code are classified according to their function: “writers” are proteins that form the code by attaching the covalent flags, such as histone acetyltransferases (HATs) and histone methyltransferases (HMTs); “erasers” are enzymes that remove the covalently bound histone marks from the histones, for example, histone deacetylases (HDACs) and histone demethylases;44 and finally, “readers” are proteins able to read the histone code without introducing any modification to the covalently bound flags, such as plant homeodomains (PHDs) and members of the royal family of methyl-lysine-binding domains.42 BRDs belong to the “readers” class and specifically interact with ε-Nacetylated lysine residues of histone complexes without introducing any modification to the covalently bound flag present on the substrate.41,45 BRDs fine-tune the activity of transcriptional regulators, chromatin modulators, and chromatin modifying enzymes through surface protein−protein interactions, and for this reason they are considered relevant targets in drug discovery.46−49 BRDs are grouped into eight subfamilies representing 61 diverse BRDs from 46 different proteins.45 The crystal structures of more than 40 BRD-containing proteins have been solved and deposited in the Protein Data Bank (PDB). Although their primary sequences share low similarity, all BRDs share a conserved three-dimensional structure, consisting of four α-helices (αZ, αA, αB, and αC) and two loops that contribute to substrate specificity (the BC loop and the ZA loop).43 Only three residues (two tyrosine residues and one asparagine) together with a network of structural water molecules forming the so-called ZA channel are conserved features of BRDs and mandatory hot spots for substrate recognition and binding.47 Although their involvement in nuclear protein in testis (NUT) midline carcinoma (NMC) was demonstrated in 2001, 50 members of the BRD and extraterminal (BET) domain family (BRD2, BRD3, BRD4, and BRDT), a BRD subfamily group that shows two different N-terminal tandem BRDs (BD1 and BD2), received considerable attention in cancer drug discovery only recently.41,48,51,52 The translocation of genes that involve NUT and BRD4 or BRD3 encodes a BRD4/3-NUT protein that blocks the cellular differentiation and inactivates the p53 protein.53 Moreover, BRD4-NUT inhibitors (described below) favor epithelial differentiation, tumor reduction, and survival in BRD4-NUT xenograft mice.54 In 2011, Sims et al. performed gene expression profiling in LP-1 (human myeloid leukemia) and Raji (Burkitt lymphoma) cell lines treated with known BET inhibitors, demonstrating that the most down-regulated gene was that for c-MYC, a well-known transcription factor involved in several human malignancies, such as Burkitt lymphoma (BL) and acute myeloid leukemia (AML).55
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INTRAFAMILY POLYPHARMACOLOGY IN PROTEIN KINASES Multitarget inhibition of cancer-associated kinases (intrafamily polypharmacology) is an established strategy to improve the efficacy and clinical outcome of targeted therapies. Several wellknown kinase inhibitors are known to inhibit more than one kinase.30 One example is the well-known anticancer drug imatinib (1, STI-571, Gleevec,31 Figure 1), which was released on the market in 2001. This molecule, initially developed to selectively inhibit BCR-ABL for the treatment of chronic myeloid leukemia (CML), was later found to inhibit two related tyrosine kinases: c-Kit for the treatment of gastrointestinal stromal tumor (GIST) and the platelet-derived growth factor receptors (PDGFRs) for the treatment of dermatofibroma sarcoma protuberans.32 In fact, several clinically relevant multitarget kinase inhibitors did not result from rational polypharmacological approaches, and in most cases their multitarget activity was discovered only accidentally.30 Examples of marketed drugs showing intrafamily polypharmacology are dasatinib (2, BMS-354825, Sprycel,33 Figure 1), another ABL-BCL inhibitor which also inhibits SRC family tyrosine kinases (used against CML and especially for phenotypes resistant to 1), and sunitinib (3, SU11248, Sutent,34 Figure 1), which is recognized as one of the most promiscuous multikinase inhibitors.30,35 Moreover, vandetanib (4, ZD6474, Zactima,36 Figure 1) is another example of an intrafamily polypharmacological drug. This compound inhibits vascular endothelial growth factor receptor 2 (VEGFR-2), EGFR, and ErbB2.32 In 2010, Shokat et al. designed a compound (5, pp12137 Figure 1) with dual phosphoinositide 3-kinase (PI3K) and mammalian target of rapamycin (mTOR) inhibitory activity.37 PI3K is involved in several diverse cellular functions, such as cell growth, survival and migration, metabolism, and intracellular vesicular transport,38−40 whereas mTOR is responsible of the feedback loop activation that inhibits PI3K.37 Today, several compounds showing dual PI3K/ mTOR inhibitory activity are under evaluation in clinical trials.19 Other examples of kinase inhibitors resulting from intrafamily polypharmacology approaches have been reported.30 However, considering the high sequence and 9307
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Figure 2. (A) Crystal structure of 10 bound to CDK2 (PDB code 4KD1). 10 is represented as light green sticks, while the most important residues are represented as gray sticks. The figure also shows the generated pharmacophore model of 10 inside CDK2 represented as spheres and dots. The hydrogen bond acceptor, donor, aromatic and hydrophobic features are colored in red, blue, brown, and green, respectively. (B) Crystal structure of 10 bound to BRDT (PDB code 4KCX). 10 is represented as light green sticks, while the most important residues are shown as light blue sticks. (C) Crystal structure of 10 bound to BRD4 (PDB code 4O70). 10 is represented as light green sticks, while the most important residues are shown as light green sticks. Water molecules are represented as ball and sticks. Hydrogen bonds are represented as yellow dashed lines, and nonpolar hydrogen atoms are omitted for clarity.
The first small molecules specifically designed as BET-family selective inhibitors were reported by Knapp et al.54 and Tarakhovsky et al.56 in 2010. The authors identified a benzodiazepine based inhibitor (6, iBET56 in Figure 1) able to confer protection against bacteria induced sepsis and a thienodiazepine-based inhibitor (7, (+)-JQ154 in Figure 1) able to induce squamous differentiation and growth arrest in a BRD4-dependent NMC cell line. The crystal structures of 6 and 7 in complex with BRD4 were also described.54,56 In 2011, Nicodeme et al. reported another small molecule nanomolar inhibitor of the BET bromodomain family (8, GW841819X,57 Figure 1) containing a benzodiazepine scaffold.57 More recently, several BET inhibitors have been published and evaluated as potential anticancer agents,51 indicating that BRD inhibitors are endowed with significant therapeutic potential.43,49
example, both JAK kinases and BRD4 demonstrated key roles in multiple myeloma models.58,59 Moreover, the Fms-related tyrosine kinase 3 (FLT3) and BRD4 are considered important targets in AML.60 In 2014, Bhalla et al. reported a synergistic lethal effect on AML cultured cells as well as AML stem/blast progenitor cells (BPCs) expressing FLT3-ITD mutations by co-treatment with 7 and known FLT3 inhibitors such as quizartinib (AC220).61,62 Likewise, synergistic effects (in vitro lethality and in vivo activity) of 7 and ibrutinib (PCI-32765),63 a covalent inhibitor of Bruton tyrosine kinase (BTK), against mantle cell lymphoma (MCL) were reported.64 Interestingly, it was demonstrated that co-treatment with 7 and ibrutinib has higher efficacy, compared to the treatment with each agent alone, in immune-depleted mice engrafted with human MCL. In the same article, the authors reported for the first time that co-treatment with 7 and palbociclib (PD-0332991),65 a known cyclin dependent kinase 4/6 (CDK4/6) selective inhibitor, is synergistically lethal against MCL cultured cells that display in vitro resistance to ibrutinib.64 Zhou et al. observed synergistic effects in growth inhibition and induction of apoptosis of HeLa and H1792 (small-cell lung cancer) cell lines after co-treatment
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SYNERGY BETWEEN KINASE AND BROMODOMAIN INHIBITORS Interestingly, members of the kinase and BET families are known to be involved in the same disease pathways. For 9308
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Figure 3. Different binding types identified by Schönbrunn et al. inside BRD4.78 BRD4 is colored according to the inhibitor binding type. BRD4 bound to a type N inhibitor is colored light green. BRD4 bound to type PZA/ZA inhibitors is colored dark blue, whereas BRD4 bound to type I inhibitors is colored dark yellow. This choice has been made to underline the three different binding types that kinase inhibitors might show inside BRDs. (A) Crystal structure of compound 7 inside BRD4 (BD1) (PDB code 3MXF). The ligand is represented as black sticks. (B) Crystal structure of compound 11 inside BRD4 (BD1) (PDB code 4O76). The ligand is represented as green sticks. (C) Crystal structure of compound 14 inside BRD4 (BD1) (PDB code 4O7F). The ligand is represented as purple sticks. (D) Crystal structure of compound 13 inside BRD4 (BD1) (PDB code 4O74). The ligand is shown as blue sticks. (E) Crystal structure of compound 15 inside BRD4 (BD1) (PDB code 4CFK). The compound is represented as orange sticks. (F) Crystal structure of compound 16 inside BRD4 (BD1) (PDB code 4O72). The ligand is shown as yellow sticks. Nonpolar hydrogen atoms are omitted for clarity. Conserved water molecules are represented as ball and sticks, whereas hydrogen bonds are represented as yellow dashed lines.
with i-CDK966 (a selective inhibitor of CDK9 protein) and 7, which is responsible for down-regulation of the c-MYC gene.66 Moreover, Baker et al. found that the combinatorial treatment with 7 and known CDK inhibitors, such as flavopiridol (9,
HMR-1275,67 Figure 1) or dinaciclib (10, SCH-727965,68 Figure 1), enhances osteosarcoma (OS) cell death up to 50% more than any of those drugs alone.69 Moreover, they described the improvement of the OS cells response to the anthracycline 9309
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Table 1. BRDs and Protein Kinase Inhibitory Activity Data of the Compounds Discussed in This Articlea bromodomain activity BRD4 (BD1), μM compd 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
IC50, μM 0.032 0.035 0.015 18 18.7 0.13 0.29 0.025 13 12.43 1.0 2.5
Kd, μM
crystal structure other BETs
targeted kinases (IC50, nM)
type
BRD2/3 BRDT
0.123 ± 0.018 0.164 ± 0.010 0.037 ± 0.003
3.424 ± 0.132 3.546 ± 0.178 0.079 ± 0.003
BRDT BRDT BRDT BRDT BRDT BRDT BRD2/3 BRDT BRDT
9.02 0.241 0.277
1.742 ± 0.076 4.6 20
BRDT BRDT
5.7 21 19 10
BRDT BRDT BRDT BRDT
ZA N N N PZA ZA I I I PZA PZA N I I PZA ZA ZA PZA ZA I I I I I
CDK1 (30), CDK2 (170), CDK4 (100) CDK1 (3), CDK2 (1), CDK5 (1), CDK9 (4) JAK2 (6.25), RET (169), FLT3 (17) JAK2 (6), RET (17), FLT3 (25) PLK1 (0.8), PLK2 (3.5), PLK3 (39) p38α, p38β (25) PI3Kα (2370), PI3Kβ (420), PI3Kδ (1530) DNA-PK (14), PI3K (5000), mTOR (1700) p38α (50), p38β (100) RSK (45), RSK3 (18), RSK4 (15), RSK3 (18), RSK2 (24), RSK1 (31) PLK1 (0.87), PLK2 (5), PLK3 (56) EGFR (44), Erbb2 (8730), Erbb4 (24200) PI3Kα (34), PI3Kγ (158), mTOR (280), DNA-PK (9) PI3Kα (714), PI3Kδ (27), PI3Kγ (1170) MPS1 (35) PYK2 (11), FAK (1.5) mTOR (8), DNA-PK (410), PI3Kδ (100) VEGFR2 (6.3), pan-kinase p38α, p38β (15.2) p38 (50), p38β (500) p38 (140), c-RAF (23), RET, SRC Syk (17), BTK GSKα (28), GSKβ (94) BRAF, p38α, LOK
BRD4 3P5O 3MXF 2YEL 4O71 4O70 4O76 4O73 4O74 4O7F 4CFK 4O72 4O77
4O78 4O7B 4O7E 4O75 4O7A 4O7C
kinase
3BLR 4KD1 4JI9 4JI9b 2RKU 4FA2b 1E7V 1E7Vb 3ZS5b 5D9K 3FC2
3FZR 4JT5 3CIF 4FA2b 3ZS5 3ZS5b 3PIY 1Q4Lb 3ZS5b
ref 56 54 57 78, 68, 78, 78, 78, 78, 84 78, 78, 85, 85, 90 95 95 85, 85, 85, 78, 78, 85, 78, 78, 78, 78,
109 78 85, 110 85, 110 85, 111 112 113 85, 114 86 115
116 117 118 119 112 112 120 121 122, 123 124
a The table also reports the binding type according to the classification of Schönbrunn et al.,78 the targeted kinases, and the crystal structure PDB codes. bCrystal structures with very similar cocrystallized ligand.
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antitumor antibiotic doxorubicin (Adriamycin)70 when cotreated with 7. Considering the side effects shown by treatment with doxorubicin,71 therapeutic strategies aimed at reducing its dose while achieving the same level of in vivo activity definitely showed improved tolerability.69 The authors also discovered that the 7 anti-OS activity is c-MYC independent despite the already reported connection between BET inhibition and cMYC suppression in multiple models.69 Finally, synergistic effects between BET inhibitors and inhibitors targeting the PI3K pathway in different tumor types have been recently described.72−74 Overall, these findings indicate that a combination therapy based on kinase and BET inhibitors may provide significant therapeutic benefit.74 Considering the side effects shown by several approved protein kinase inhibitors,75 a specific combination of kinase and BET inhibitors might reduce the kinase inhibitor dose needed to achieve the same pharmacological effect. Moreover, such combinations may help to combat drug resistance, which is a major issue in patients treated with protein kinase inhibitors. Despite the significant therapeutic relevance of combination therapies, several potential advantages of a targeted therapy based on a single drug that hits multiple targets over single-targeted or combination therapy have been described.27−29 Although combination therapy is more extensively explored in the clinic, both approaches are potentially able to yield drugs or drug combinations with improved safety and efficacy profiles.
DUAL KINASE/BROMODOMAIN INHIBITORS In 2013, Schönbrunn et al. demonstrated that 10 (Figure 1), a well-known CDK2 inhibitor, interacts with BRDs; these data indicated for the first time that a new generation of BRD inhibitors could be rationally designed by using the chemical space of kinase inhibitors.76 Following these discoveries, the rational identification of dual kinase/BRD inhibitors has emerged as a promising interfamily polypharmacology approach against cancer and inflammatory diseases. Compound 10 has recently advanced to phase III clinical trials for the treatment of refractory chronic lymphocytic leukemia due to its selectivity for CDK1, CDK2, CDK5, and CDK9.77 The molecule acts on a broad spectrum of human cancers both in vitro and in vivo; moreover, 10 has a better in vivo therapeutic index compared to other CDK inhibitors.68 The crystal structure of 10 in complex with CDK2 was released in 2013 (PDB code 4KD1).76 The dual inhibitor binds in the ATP binding pocket of CDK2 (type I inhibitor). Within the structure, the pyrazopyrimidine hydrogen-bonds to the backbone of Leu83 of the hinge region, whereas the hydroxyethyl group interacts with the side chain of the conserved Lys33 (Figure 2A). Furthermore, the pyridine N-oxide ring is partially solvent exposed, and the nitroxy group interacts with the side chain of Lys89 and with the backbone carbonyl group of Ile10 through a water-mediated hydrogen bond. The ethyl group is located in the back pocket of the cavity forming extensive hydrophobic and alkyl−aryl interactions with the side chain of 9310
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1). Most compounds displayed an IC50 in the middle or middle to low micromolar range on both proteins. Two of them showed an IC50 in the low micromolar range. Compounds 11 (TG101209)80 and 12 (TG101348, fedratinib)81 are known inhibitors of JAK2.80,81 Compound 13 (BI2536),82 a wellknown Polo-like kinase 1 (PLK1) inhibitor with antitumor activity against relapsed or refractory AML and non-small-cell lung cancer,82,83 showed an IC50 comparable with those of 7 and 8 on both epigenetic targets (Table 1).78 Importantly, the authors defined three main binding modes on the basis of the interactions established by the hinge-binding group and BRD4 (BD1) (Figure 3).78 Compounds interacting with Asn140 were classified as type N binders (three compounds). Figure 3A and Figure 3B show the binding modes of 7 and 11, respectively, taken as representatives of type N binders. Compounds interacting with Pro82 and the ZA channel or with the ZA channel alone were classified as type PZA and ZA, respectively (five compounds). Figure 3C and Figure 3D show the binding modes of 13 and 14 (SB251527),78 respectively, taken as representatives of this class. Finally, compounds in which the hinge-binding group is not involved in binding interactions were classified as type I (six compounds). Figure 3E and Figure 3F show the binding modes of compounds 15 (LY294002)84 and 16 (NU7441),78 respectively, used as representatives. At the same time, Knapp et al. independently reported that 10 known kinase inhibitors were also active on BRD proteins.85 Remarkably, four of these were also reported by Schönbrunn et al. (11, 12, 13, and 17 (SB202190)78). Their BRD4 (BD1) inhibitory activity was confirmed by AlphaScreen assays using the temperature shift assay (ΔTm), and the AlphaScreen dose− response experiments indicated that 12, 13, and 18 (BI-D1870 a RSK inhibitor)86 are the most active compounds against BRD4 (BD1), having IC50 values in the nanomolar range. Moreover, binding constants determined with isothermal titration calorimetry showed that 11, 12, 13, and 19 (BI6727)85 (Figure 1 and Table 1) have the best Kd values. Finally, the authors demonstrated that 12 and 13 suppress cMYC expression through BET inhibition in multiple myeloma cells.85 The BRD4 (BD1) cocrystal structures determined by Knapp et al. for the most active compounds 12 and 13 show a binding pattern similar to those of the crystal structures solved by Schönbrunn et al. (PDB codes 4O74, 4O76, and 4O73).78,85 The binding of compound 13 is characterized by the presence of a hydrogen bond between the carbonyl group of the 2-amino-6-oxodihydropteridine ring and the side chain of Asn140 of BRD4 (BD1) (Figure 3D). The carbonyl group interacts with Tyr97, i.e., the second BRDs conserved residue, through a hydrogen bond with a conserved water molecule present in the ZA channel. The aminopyrimidine moiety interacts with Pro82 (WPF shelf) through a conserved water molecule located at the entrance of the ZA channel. Finally, the 5-ethyl moiety located on the pteridinone group interacts with Leu92, Leu94, and Tyr139 (Figure 3D). In the complex with the PLK1 kinase, the aminopyrimidine of 13 interacts with the hinge (type I kinase inhibitor), whereas the carbonyl group of the pteridinone moiety interacts with the side chain of Lys82 and the backbone of Asp194 via two water-mediated hydrogen bonds (PDB code 2RKU).87 The methylpiperidine of 13 is solvent exposed in both targets. Compound 12, a drug that recently entered phase III clinical trials for myelofibrosis,88 interacts with the epigenetic target by adopting a binding mode similar to those of 7 and 8. Similar to 8, 12 displays bidentate interactions between the aminopyridine
Phe80, the gatekeeper residue of CDK2 (Figure 2A). Interestingly, the β1 and β2 sheets of the N-lobe are adapted to the small ligand, allowing more extensive hydrophobic interactions involving the side chains of residues Ile10 and Val18.76 When tested against a panel of 24 BRDs, 10 showed activity mainly on the BET-BRDs subfamily (BRD2, BRD3, BRD4, BRDT).76 Crystal structures of 10 in complex with BRDT (PDB code 4KCX) and with BRD4 (PDB code 4O70) have been reported (Figure 2B and Figure 2C).76,78 Analysis of these crystal structures shows that the ligand can adopt two different binding modes inside BET-BRDs. In both structures 10 binds in the AcK pocket, i.e., the pocket in which the acetylated lysine of the BRDs substrate interacts with BET proteins. However, in the case of BRDT (BD1), three hydrogen bond interactions mediate the binding with 10 (Figure 2B). Two of them are formed between the pyrazopyrimidine group of the ligand and the backbone of Asp57 (one of the two being water-mediated) located in the ZA channel, whereas the third is established by the nitroxy group of the ligand and the side chain of the conserved residue Asn109 located in the BC loop. Hydrophobic contacts are formed with the side chain of Phe52, which belongs to the conserved WPF shelf (Figure 2B), with Val56, and with Leu63 and Ile115, located on the ZA loop and on the first turn of the αC helix, respectively. Finally, the hydroxyethyl and the ethyl groups of the drug are solvent exposed.76 On the contrary, 10 binds BRD4 (BD1) by forming two hydrogen bonds with the side chain of Asn140 (Asn109 in BRDT (BD1)), and the nitroxy group interacts with the backbone of Ile146 (Ile115 in BRDT (BD1)). The ethyl moiety is directed deep inside the cavity, whereas the hydroxyethyl group is exposed to the solvent at the entrance of the ZA channel (Figure 2C).78 In the latter structure, 10 adopts a binding mode that is similar to those observed for 7 (Figure 3A) and 8 in complex with the BRD4 (BD1) protein (PDB codes 3MXF and 2YEL, respectively).54,57 On the other hand, differences can be noted by comparing the crystal structure of BRDT (BD1) in complex with 10 and the structure of BRDT (BD1) bound to the well-known selective inhibitor 7 (PDB code 4FLP).79 In fact, 7 interacts with all BET-BRD subfamily members through strong hydrogen bond interactions between the 1,4,5-triazole ring and the conserved Asn109 (Asn140 in BRD4 (BD1)) and Tyr66 (Tyr97 in BRD4 (BD1)) residues (water-moleculemediated ZA channel), whereas the rest of the compound is mainly involved in hydrophobic contacts (Figure 3A).54,79 The different binding modes of 10 in BRDT (BD1) and in BRD4 (BD1) are not apparently reflected by differences in BRD inhibitory activity. Indeed, the compound displays an IC50 in the middle to low micromolar range for both targets (Table 1), as opposed to the nanomolar activity shown by 7 and 8.54,57,76 On the basis of these pieces of evidence, in 2014, Schönbrunn et al. carried out a cocrystallization screening campaign using the kinase inhibitor libraries from Selleck Chemicals (277 compounds) and Glaxo Smith Kline (published kinase inhibitor set, 304 compounds).78 The screen was performed on BRD4 (BD1), selected as a representative member of the BET-BRDs. Of 377 cocrystal structures that were obtained, 194 were analyzed. Among them, 14 crystal structures (Table 1) exhibited interactions of the tested compounds inside the AcK pocket. IC50 values against BRD4 (BD1) and BRDT (BD1) were determined using differential scanning fluorimetry (DSF) and the AlphaScreen assay (Table 9311
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structural similarity between the morpholinothienopyranone derivatives and 15 and considering the similar binding mode displayed by compounds 15, 21, and 22 in the PI3K binding site,94 these compounds are likely to display a similar binding mode with the epigenetic target. This is confirmed by the docking experiments described below. Therefore, 21 and 22 are likely to interact with BRD4 (BD1) similarly to 15, i.e., with the 1,4-dioxane group and the ethyl acetate moiety exposed to solvent.
hinge-binding moiety and the amide group of Asn140 side chain, whereas the other amino group present in the compound hydrogen-bonds with Pro82. In 2015, Fletcher et al. prepared a focused library starting from the most active hit found by Schönbrunn and Knapp groups.89 Through structure-based modification of 13, the authors identified a new inhibitor with 7-fold increased binding affinity for BRD4 and only slightly reduced affinity for PLK1. The increased affinity was rationalized with docking, which provided a binding pattern similar to that of 13 (Figure 3D). The 7-fold improvement in activity was ascribed to the substitution of the cyclopentyl moiety with a 3-bromobenzyl group on the pteridinone scaffold, which shows higher flexibility and allows the compound to reach the WPF shelf of BRD4 (BD1). According to the computational models obtained, the authors were able to rationalize structure−activity relationships around the structure of 13, leading to new selective nanomolar BRD4 inhibitors or dual PLK1/BRD4 inhibitors.89 In 2015, Schürer et al. identified a 4-aminoquinazoline compound 20 (287090 in Figure 1) as a new dual EGFR/BRD4 inhibitor endowed with nanomolar activity on EGFR and low micromolar activity on BRD4 (BD1) (Table 1).90 Remarkably, lapatinib-induced kinome reprogramming ErbB2-positive breast cancer cells are known to be suppressed by the combination of lapatinib91 with 7.92 In light of this information, Schürer et al. carried out a virtual screening campaign and selected 24 compounds as potential dual EGFR/BRD4 inhibitors.90 AlphaScreen assays and differential scanning fluorimetry (DSF) experiments performed on the selected compounds showed that several compounds were active on BRD4, and one of them (compound 20) showed dual EGFR/BRD4 inhibitory activity. Docking and molecular dynamics suggested a potential binding mode for this dual inhibitor. Compound 20 is predicted to bind in the AcK pocket of the epigenetic target. In the complex, the hinge binding group of the compound interacts with Asn140 (type N binder), the Ile146 side chain is involved in hydrophobic interactions, and the 2-aryloxyethylamino moiety is partially solvent exposed. In EGFR, compound 20 is predicted to interact with the hinge region of the kinase (ATP binding pocket, type I inhibitor), showing the typical binding pattern of other well-known 4-aminoquinazoline-based EGFR inhibitors such as lapatinib.90 In 2014 another known PI3K inhibitor, compound 15 in Figure 1, has been reported as a dual kinase/BRD ligand.84 The compound, based on a chromen-4-one scaffold, showed inhibitory activity against three members of the BETs family (BRD2, BRD3, BRD4). The resolution of the crystal structure of BRD4 (BD1) in complex with 15 (PDB code 4CFK) demonstrated that the compound binds into the AcK pocket. The morpholino group binds the hinge residue of the PI3K kinase (Val882), whereas it is solvent exposed in BRD4 (BD1) (Figure 3E).84,93 According to the Schönbrunn classification, this compound belongs to type I binders (Table 1). In the epigenetic target, the carbonyl group of the chromene scaffold forms water-mediated hydrogen bonds with Asn140 and Tyr97 residues (Figure 3E).84 On the basis of the similarity with 15, a compound library comprising 41 morpholinothienopyranone derivatives was synthesized and tested against PI3K.94 Most compounds inhibited PI3K with nanomolar activities, and more importantly, two of them (compounds 21 (SF2523)95 and 22 (SF2535)95 in Figure 1) also inhibited BRD4 (BD1) with nanomolar activities (Table 1).95−97 Considering the high
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COMPUTATIONAL APPROACHES FOR THE DESIGN OF DUAL KINASE/BRD LIGANDS: PHARMACOPHORE MODELING AND DOCKING Considering the large amount of structural information already available on kinases and kinase inhibitors and the growing evidence that kinases and BRDs are suitable and worthy of special consideration for polypharmacology approaches, ligandbased and structure-based computational approaches may be useful to aid the rational identification of more potent dual kinase/BRD inhibitors. Ligand-based approaches are usually related to the identification of active compounds with a certain degree of structural similarity to known ligands. Pharmacophore modeling is another well-known ligand-based approach, which is based on the identification of key structural features responsible for biological activity of a ligand. In the development of a pharmacophore model, binding site information derived from cocrystallized complexes can be incorporated to generate structure-based pharmacophores. Structure-based approaches, e.g., molecular docking, can be used to identify putative hit compounds for selected targets through virtual screening approaches. Moreover, docking can be used for the optimization of already known ligands (hit to lead optimization). Molecular dynamics may help improve conformational sampling in virtual screening. Likewise, more accurate freeenergy-based scoring functions can be used to improve binding free energy predictions. Interestingly, ligand-based and structure-based methods may be combined to provide more robust results. Such combination offers the possibility of taking advantage of the peculiar features and strengths of each approach toward the obtainment of possible candidates for polypharmacology.98 Pharmacophore Models. The construction of pharmacophore models may be a suitable approach for the identification of new dual kinase/BRD putative inhibitors. According to the three different binding types described by Schönbrunn et al. (Figure 3), the three pharmacophore models described below have been built using the Phase software implemented in the Schrödinger suite.99,100 The generated pharmacophores can be useful for the identification of new hit compounds through pharmacophore virtual screening and are available upon request to authors. Type N Binders. Type N binders are compounds in which the kinase hinge binding moiety interacts with the conserved Asn residue located in the BRDs ZA loop (Figure 3B). Superposition of the BRD4 (BD1) crystal structures shows that compounds belonging to this class (four compounds in Table 1) have good overlap. Taking into consideration the binding mode of the most active N-type BRD4 (BD1) binder (compound 11 in Table 1, PDB code 4O76) as the query structure, a pharmacophore model with four key features was constructed (Figure 4A). These comprise one hydrogen bond acceptor, one donor, and one aromatic and one hydrophobic 9312
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hydrogen bond acceptors, one hydrogen bond donor, and two hydrophobic features (Figure 4B). The two acceptor moieties are likely more relevant than the donor, being present in the majority of the compounds of this class (Figures 1, 3C, and 3D), whereas the hydrophobic features are common to all derivatives. PZA/ZA binders include compounds 9, 13, 14, 18, 19, 23 (AZ-3146),85 24 (PF431396),85 25 (PP242),85 26 (GW612286X),78 and 27 (SB284847BT).78 Compound 9, which is one of the less active inhibitors in the presented data set (Table 1), is the only compound of this class that matches only one feature of the pharmacophore (the hydrogen bond acceptor region, Figure 4B). Type I Binders. Type I binders do not interact with the epigenetic target with their kinase hinge binding group (11 compounds in Table 1). The pharmacophore model generated from the most active compound of this class (compound 16) cocrystallized with BRD4 (BD1) (PDB code 4O72) shows three key features, i.e., a hydrogen bond acceptor, a hydrogen bond acceptor/donor, and an aromatic feature (Figure 4C). All compounds belonging to this class (i.e., 15, 16, 17, 21, 22, 28 (SB203580),78 29 (SB610251B),78 30 (fostamatinib),78 31 (SB409514),78 and 32 (SB614067R)78) fit the generated pharmacophore model (Figure 4C). Overall, the generated pharmacophores encode the main structural features required for each type of binder. These pharmacophores can be improved by adding excluded volume features based on the three-dimensional positions of residues forming the AcK binding site of BRD4, defined as spatial regions off-limits to the ligands. The use of excluded volumes is exemplified for N-type binders in Figure 4D. The pharmacophores can be used to help the identification of dual kinase/ BET inhibitors starting from the kinase inhibitors chemical space. Furthermore, kinase-based pharmacophores, such as the one proposed in Figure 2A, and the BRD pharmacophores described above (Figure 4) can be used in combination to allow the identification of potential dual kinase/BRD inhibitors from a wider chemical space. Finally, the pharmacophore models may be useful to classify already known dual kinase/BET inhibitors and may be used for ligand optimization. Docking. Considering that both protein kinase and BRD crystal structures are known, docking methods can be used to predict binding modes and can aid in the identification of dual ligands. Docking can also be used to predict the binding mode of the dual kinase/BET inhibitors for which a crystal structure in complex with the epigenetic target has not yet been determined (i.e., 18, 21, 22, 23, 24, 25, 28). Docking experiments performed using the Glide software101 with default settings and the crystal structure of BRD4 (BD1) in complex with the most active dual inhibitor of the data set (PDB code 4O74) indicate that the tested compounds overlap fairly well with the cocrystallized reference ligands, reproducing the mandatory interactions inside BRD4 (BD1) according to the three binding types described above (Figure 5 and Table 1). Therefore, docking may aid in the identification of putative binding modes in BET-BRDs. Virtual screenings made with docking could also help the identification of new classes of BET inhibitors. In recent years, several examples of successful virtual screening campaigns performed on BRD4 have been described.102−105 The first virtual screening investigation specifically directed toward the identification of dual kinase/BRD inhibitors was reported in 2015 by the Schürer group.90 They proposed a multistep virtual screening workflow consisting of the following: (i) identi-
Figure 4. Pharmacophore models. (A) Pharmacophore model obtained considering the binding geometries of compound 11 inside BRD4 (BD1). 11 is represented as green sticks, whereas 7 is represented as black sticks. The hydrogen bond donor, acceptor, aromatic and hydrophobic features are shown in blue, red, brown, and green, respectively. (B) Pharmacophore model generated considering the binding geometries of compound 13 inside BRD4 (BD1). 13 and 14 are shown in blue and purple, respectively. The hydrogen bond donor, acceptor, and hydrophobic features are shown in blue, red/ orange (second acceptor moiety), and green, respectively. (C) Pharmacophore model carried out considering the binding geometries of compound 16 inside BRD4 (BD1). Compounds 15, 16, and 29 are shown in orange, yellow, and gray sticks, respectively. The hydrogen bond donor, acceptor, and aromatic features are shown in blue, red, and brown, respectively. (D) Refined “N type binder” pharmacophore model with excluded volume features after consideration of the residues forming the AcK binding site of BRD4. In all panels nonpolar hydrogen atoms are omitted for clarity.
feature. Both the acceptor and the donor are required to establish interactions with Asn140 of BRD4 (BD1), and the aromatic and the hydrophobic features are present in all cocrystallized compounds belonging to this group, such as compounds 10, 11, and 12 (Figure 4A). The BETs selective ligand 7 matches the pharmacophore model, although it does not have a donor group in proximity of Asn140 (Figures 3A and 4A). This lack of bidentate interaction with Asn140 is compensated for by a second acceptor group located on the tetrazole ring that is engaged in a water-mediated hydrogen bond with Tyr97 (Figure 3A), i.e., the second conserved hot spot among BRDs. Type PZA/ZA Binders. According to the second binding type described by Schönbrunn et al., compounds of this class (10 compounds in Table 1) have the kinase hinge binding moiety interacting with Pro82 of the WPF shelf and/or with conserved water molecules located at the entrance of the ZA channel (Figure 3C and Figure 3D). The pharmacophore model generated for this class, built on the most active PZA/ZA compound 13 cocrystallized with BRD4 (BD1) as a query structure (PDB code 4O74), shows five key features, i.e., two 9313
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Figure 5. Docking results for selected dual kinase/BRD ligands for which a crystal structure inside BRD4 is not available. As explained in Figure 4, BRD4 is colored according to the inhibitor binding type. BRD4 bound to type PZA/ZA inhibitors is colored dark blue, whereas BRD4 bound to type I inhibitors is colored dark yellow. This choice has been made to underline the three different binding types that kinase inhibitors adopt inside BRDs. The compounds are overlapped to the reference crystal structure. Compound 13 is represented as blue sticks (A−D). Compound 15 is shown in orange (E, F). Compounds 23 (A), 18 (B), 24 (C), 25 (D), 28 (E), 21 (F), and 22 (F) are shown in cyan, brown, pink, magenta, light brown, light cyan, and salmon, respectively. Water molecules are displayed as ball and sticks, and nonpolar hydrogen atoms are omitted for clarity.
fication of potential EGFR inhibitors based on known active compounds through a statistical model trained on thousands of EGFR inhibitors and hundreds of thousands of kinase decoys (ligand-based approach); (ii) docking of the selected compounds on several BRD4 crystal structures (structurebased approach); and (iii) selection of compounds for biological assays based on docking scores and physicochemical properties. Molecular dynamics simulations were also applied
to explain the difference in binding affinity of compound 20 for BRD4 (BD1) and EGFR, concluding that the chemical optimization of 20 can lead to the generation of new inhibitors with comparable BRD4 and EGFR potency.90 Computational structure-based approaches can also be used in extensive medicinal chemistry projects to guide the rational modification of known dual inhibitors in which the putative binding modes inside kinase and BRD targets have been 9314
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characterized using crystallography. As described by Schönbrunn et al., the three different binding types identified in AcK of BRD4 (BD1) may guide the identification of new more potent BET inhibitors or dual kinase/BET inhibitors.78 Fletcher et al. reported new dual inhibitors obtained through structural modifications of compound 13.89 Moreover, selective and more potent BET inhibitors can also be obtained starting from the kinase inhibitor space. For instance, slight modifications of compounds classified as type PZA/ZA can decrease the kinase inhibitory activity. Fletcher et al. described distinct modifications of 13 that enhanced selectivity and BRD4 inhibitory activity.89 Remarkably, because type I binders do not bind the AcK pocket with the kinase hinge binding group, compounds of this class may be easily converted into selective BET inhibitors. Finally, type N binders are intrinsically dual inhibitors because they bind both targets with the hingebinding group.78 Moreover, structure-based tools supported by experimental approaches may also be used to identify new protein−ligand interactions inside BRDs. It has been reported that residues located on the surface of the epigenetic targets and in close proximity to the AcK pocket are important for substrate specificity of different BRDs and may be exploited as new anchoring points.47 These additional structural features were recently exploited by Wohlwend et al., who designed structural modifications of a reference ligand based on a 4-acylpyrrole scaffold that provided new derivatives with micromolar activity on the epigenetic target.106 Moreover, Hoelder et al. performed a structure-based virtual screen on BRD4 followed by rational modification of the discovered hits, resulting in the identification of compounds with significantly improved activity on BET proteins.107 Finally, Wang et al. recently identified new selective nanomolar BET inhibitors after an analysis of the cocrystallized structures of BRD4 followed by structural modification of the reference ligands.108 In general, identification of new dual kinases BRD inhibitors through computational based approaches should comprise diverse strategies because ligands can bind the AcK pocket with a chemical group that differs from that of the hinge binding motif, which is mandatory for the binding to protein kinases. As described above, the acetyl-lysine mimetic binding group present in the dual inhibitors classified as type I binders can be solvent exposed in kinases. For this reason, any computational workflow aimed at the identification of new dual inhibitors should take into account the three different binding types shown inside BET-BRDs (i.e., N, PZA/ZA, I). For instance, the identification of dual kinase/BRD inhibitors belonging to type N or type PZA/ZA could be achieved by pharmacophore screenings conducted in parallel on kinases and BRDs (type N and/or PZA/ZA queries, Figure 4A and Figure 4B), followed by postprocessing with structure-based methods (e.g., docking) to refine the selection of the final hit compounds. On the other hand, computational workflows to identify type I dual ligands would require a definition of the starting chemical space. If the kinase inhibitor chemical space is used, pharmacophore screenings made with the type I pharmacophore query described above (Figure 4C) followed by docking would be appropriate. If wider chemical spaces are used, computational approaches should be conducted in series on the targeted kinase and BRD (or vice versa). For type I ligands, this would allow the presence of a hinge binding group and an AcK mimetic group in the same molecule.
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FINAL REMARKS AND PERSPECTIVES
The identification of small molecules targeting protein kinases has become one of the milestones in the development of anticancer drugs. Over the years, these inhibitors have shown therapeutic limitations mainly resulting from drug resistance, poor selectivity, and off-target effects. In addition, most tumors can elude the effects of inhibiting a single kinase by activating alternative pathways and escape mechanisms.19−22 For these reasons, in recent years, multitarget inhibition of cancerassociated kinases (intrafamily polypharmacology) as well as multitarget inhibition of kinases and targets belonging to different families (interfamily polypharmacology) gained a foothold in drug discovery. BRDs play a key role in the epigenome and have very recently been discovered as druggable targets. Since then, dual kinase/BRD inhibitors targeting key drivers in a number of cancers have been reported and demonstrate significant potential for the achievement of higher efficacy and more durable response. The first compound (10) showing dual kinase/BET inhibitory activity was identified by Schönbrunn et al. in 2013.76 In 2014, the Schönbrunn and Knapp groups identified several compounds with dual kinases/BETs inhibitory activity.78,85 Among them, four compounds (11, 12, 13, and 17) were reported by both groups. The most active compound, 13, is a known inhibitor of the PLK1 kinase, which inhibited BRD4 in the nanomolar range, i.e., with an activity comparable to that of 7, the first selective BETs inhibitor. Moreover, from the analysis of the available crystal structures, the dual inhibitors identified so far have been classified into three groups depending on the binding mode of their kinase hinge binding region adopted in BRD4. Although the three different binding types provide a solid foundation for structurebased design of future compounds with putative dual inhibitory activity, the identification of dual kinase/BRD inhibitors is still in the earliest stages. Evidence of this is given by the results of the cocrystallization screening campaign conducted by Schönbrunn et al., according to which even weak inhibitors cocrystallized with BRD4 could represent an excellent starting point for the rational design of high-potency BET inhibitors.78 The results obtained so far indicate that there is ample room for discovering new classes of compounds with dual activity in the near future. Moreover, the virtual screening investigations conducted by Schürer et al. demonstrated that wider chemical spaces, i.e., not necessarily those of kinase and BRD inhibitors, can be used to identify new dual kinase/BRD inhibitors.90 Additionally, already optimized druglike kinase inhibitors with nanomolar inhibitory activity on BETs, such as 13, still show considerable margins for improvement of activity toward BRDs.85 Furthermore, all compounds with dual kinases/ BRDs inhibitory activity reported so far belong to kinase type I inhibitors. It is conceivable that progress in the discovery of kinase allosteric inhibitors (types III, IV) will provide additional chemical space that once combined with the chemical space accessible to BRD proteins, may lead to dual ligands less prone to drug resistance and with reduced off-target effects. Finally, the presence of seven additional BRD subfamilies in nature, besides the BET-BRDs discussed in this review, will certainly open the way to new interesting target combinations to be exploited for future drug design and discovery investigations. Overall, co-targeting kinases and BRD epigenetic reader proteins is rapidly emerging as a promising approach in cancer drug development. The identification of dual inhibitors is at the 9315
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early stages but is definitely a promising opportunity to fight cancer in the polypharmacology era. Knapp et al. observed that the rational design of dual kinase/BRD inhibitors is probably more accessible than the design of ligands with dual activity for two rationally chosen kinases (owing to kinase similarities).85 For example, the structural optimization of 11 and 12 (Table 1), showing dual FLT3/BETs and JAK/BETs inhibitory activity, respectively, may represent a future strategy against hematological cancers. The fact that dual ligands could be obtained despite that kinases and BRDs have different structures and binding site architectures provides additional confidence that polypharmacological drugs can also be rationally designed for targets that do not share significant structural homology.98 More generally, compounds with a desired polypharmacology profile represent a promising strategy against cancer, mainly due to the capacity to counteract compensatory mechanisms activated by tumor cells leading to drug resistance. Moreover, drugs able to hit specific target combinations represent useful tools to investigate the biochemical pathways involved in cancer and to analyze the effects of altering specific drug nodes. Remarkably, polypharmacological drugs can have several advantages with respect to single target or combination therapies. In addition to a generally higher efficacy and safety, some of these advantages can be summarized as follows: (i) a multitarget drug may show a more predictable pharmacokinetic profile compared to a combination therapy; (ii) acute and delayed toxicities may be reduced by administering a multitarget drug in place of a combination therapy; (iii) drug−drug interactions are avoided; (iv) combination therapies might also lead to negative synergistic effects; (v) a multitarget approach guarantees the simultaneous presence of the molecule in the tissues where the active principle exert its function; and (vi) regulatory agencies usually require the demonstration of the safety of each individual drug before their combination can be tested in humans, thus delaying the assessment of novel combinations.27−29 Finally, computational methods are useful in predicting the binding mode of known ligands and in identifying new ligands with dual activity using either ligand-based or structure-based methods or a combination of both methods. The recent successes in predicting polypharmacology and the raising numbers of computational approaches available for this purpose will certainly boost the identification and optimization of nextgeneration compounds with dual kinase/BRD inhibitory activity.
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using computational techniques, of novel inhibitors of epigenetic targets. In 2015 he moved to the University of Modena and Reggio Emilia, Italy, where he earned a postdoctoral position in the group of Prof. Giulio Rastelli. Currently he is working on the identification of anticancer drugs based on kinase inhibitors with innovative mechanisms of action. Giulio Rastelli is Professor in Medicinal Chemistry and Head of the Molecular Modeling and Drug Design laboratory (www.mmddlab. unimore.it) of the University of Modena and Reggio Emilia. He received his Ph.D. in Medicinal Chemistry at the University of Modena and Reggio Emilia and has been Research Fellow at the University of California, San Francisco under the supervision of Prof. Daniel Santi and Peter Kollman. His research interests focus on the development and application of computational drug design methodologies to address problems that lie at the interface between chemistry, biology, and medicine. His lab recently developed BEAR, an innovative tool for virtual screening. He collaborates with academic and private institutions for the discovery and development of smallmolecule inhibitors of relevant drug targets, with a special focus on cancer.
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ACKNOWLEDGMENTS
This work was supported by a grant from the Associazione Italiana per la Ricerca sul Cancro (Grant AIRC IG 15993).
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ABBREVIATIONS USED DFG, Asp-Phe-Gly; ATP, adenosine 5′-triphosphate; BRD, bromodomain; TNBC, triple-negative breast cancer; PCR2, polycomb repressive complex 2; CML, chronic myelogenous leukemia; GIST, gastrointestinal stromal tumor; PDGFR, platelet-derived growth factor receptor; EGFR, epidermal growth factor receptor; VEGFR-2, vascular endothelial growth factor receptor 2; PI3K, phosphoinositide 3-kinase; mTOR, mammalian target of rapamycin; HAT, histone acetyltransferase; HMT, histone methyltransferase; HDAC, histone deacetylase; PHD, plant homeodomain; PDB, Protein Data Bank; NUT, nuclear protein in testis; NMC, nuclear protein in testis midline carcinoma; BET, bromodomain and extraterminal domain; BL, Burkitt Lymphoma; AML, acute myeloid leukemia; JAK, Janus kinase; FLT3, fms-related tyrosine kinase 3; BPC, blast progenitor cell; BTK, bruton tyrosine kinase; MCL, mantle cell lymphoma; CDK, cyclin-dependent kinase; OS, osteosarcoma; WPF, Trp-Pro-Phe; AcK, acetylated lysine; DSF, differential scanning fluorimetry; PLK1, polo-like kinase 1; RSK, ribosomal s6 kinase
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AUTHOR INFORMATION
Corresponding Author
*Phone: +39 059 2058564. E-mail:
[email protected].
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Author Contributions
The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes
The authors declare no competing financial interest. Biographies Luca Carlino obtained his Master’s degree in Chemistry and Pharmaceutical Technologies at the University of Parma, Italy, in 2009. He received his Doctoral degree in Medicinal Chemistry in 2014 under the supervision of Prof. Wolfgang Sippl at the University of Halle/Saale, Germany. His studies were focused on the discovery, 9316
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