Abstract
The properties of a cell are determined both genetically by the DNA sequence of its genes and epigenetically through processes that regulate the pattern, timing and magnitude of expression of its genes. While the genetic basis of disease has been a topic of intense study for decades, recent years have seen a dramatic increase in the understanding of epigenetic regulatory mechanisms and a growing appreciation that epigenetic misregulation makes a significant contribution to human disease. Several large protein families have been identified that act in different ways to control the expression of genes through epigenetic mechanisms. Many of these protein families are finally proving tractable for the development of small molecules that modulate their function and represent new target classes for drug discovery. Here, we provide an overview of some of the key epigenetic regulatory proteins and discuss progress towards the development of pharmacological tools for use in research and therapy.
Links to online information in the IUPHAR/BPS Guide to PHARMACOLOGY
| TARGETS | ||
|---|---|---|
| ASH1L | HDA8 | PRDM2 |
| ATAD2 | HDAC9 | PRMT1 |
| ATAD2B | JMJD1C | PRMT10 |
| BAZ1A | KAT2A | PRMT2 |
| BAZ1B | KAT2B | PRMT3 |
| BAZ2A | KAT5 | PRMT5 |
| BAZ2B | KAT6A | PRMT6 |
| BPTF | KAT6B | PRMT7 |
| BRD1 | KAT7 | PRMT8 |
| BRD2 | KAT8 | SETD1A |
| BRD3 | KDM1A | SETD1B |
| BRD4 | KDM1B | SETD2 |
| BRD7 | KDM2A | SETD7 |
| BRD8 | KDM2B | SETD8 |
| BRD9 | KDM3A | SETDB1 |
| BRDT | KDM3B | SETDB2 |
| BRPF1 | KDM4A | SIRT1 |
| BRPF3 | KDM4B | SIRT2 |
| BRWD1 | KDM4C | SIRT3 |
| BRWD3 | KDM4D | SIRT4 |
| CARM1 | KDM4E | SIRT5 |
| CECR2 | KDM5A | SIRT6 |
| CLOCK | KDM5B | SIRT7 |
| CREBBP | KDM5C | SMARCA2 |
| DOT1L | KDM5D | SMARCA4 |
| EHMT1 | KDM6A | SMYD2 |
| EHMT2 | KDM6B | SP100 |
| EP300 | KDM7A | SP110 |
| EZH2 | KDM8 | SP140 |
| FBXO10 | KMT2A | SP140L |
| FBXO10 | KMT2B | SUV39H1 |
| FBXO11 | KMT2C | SUV39H2 |
| GTF3C4 | KMT2D | SUV420H1 |
| HAT1 | KMT2E | SUV420H2 |
| HDAC1 | NCOA1 | TAF1 |
| HDAC10 | NCOA2 | TAF1L |
| HDAC11 | NCOA3 | TRIM24 |
| HDAC2 | NSD1 | TRIM28 |
| HDAC3 | PBRM1 | TRIM33 |
| HDAC4 | PHF2 | TRIM66 |
| HDAC5 | PHF8 | ZMYND11 |
| HDAC6 | PHIP | ZMYND8 |
| HDAC7 |
| LIGANDS |
|---|
| AMI-1 |
| anacardic acid |
| AZ505 |
| benzo[d]imidazole inhibitors of PRMT4 from BMS |
| BIX-01294 |
| BMS pyrazole inhibitor 7f |
| BRD4770 |
| bromo-deaza-SAH |
| butyric acid |
| C21 |
| C646 |
| Compound 1 (allosteric) |
| curcumin |
| daminozide |
| EI1 |
| entinostat |
| epigallocatechin-3-gallate |
| EPZ-5676 |
| EPZ-6438 |
| garcinol |
| GSK126 |
| GSK-J1 |
| H3-CoA-20 |
| I-BET-762 |
| Lys-CoA |
| mocetinostat |
| nahuoic acid A |
| NCL-1 |
| OG-L002 |
| PBIT |
| plumbagin |
| RM65 |
| rocilinostat |
| romidepsin |
| RVX 208 |
| SGC0946 |
| trichostatin A |
| UNC0638 |
| UNC0642 |
| valproic acid |
| vorinostat |
This table lists protein targets and ligands which are hyperlinked to corresponding entries in http://www.guidetopharmacology.org, the common portal for data from the IUPHAR/BPS Guide to PHARMACOLOGY (Pawson et al., 2014) and the Concise Guide to PHARMACOLOGY 2013/14 (Alexander et al., 2013a, Alexander et al., 2013b).
Introduction
The properties of a cell are determined by its specific genetic material and the pattern in which its genes and, ultimately, proteins are expressed. While the transmissibility of the genome is well recognized, the fact that cellular phenotypes can remain stable through cell division – a dividing T-cell yields two T-cells, a dividing hepatocyte yields two hepatocytes, etc. – indicates that specific gene expression patterns are also heritable in daughter cells. The latter type of inheritance is termed epigenetic (literally, ‘above genetic’) because the generation and maintenance of differentiated cell phenotypes is not due to changes in the nucleotide sequence. While heritable, epigenetic memory is also malleable, in that gene expression patterns can change in response to environmental stimuli. This allows for the development of different cell lineages during processes such as embryogenesis or haematopoiesis, and also for more subtle changes in cell function in response to physiological requirements, or importantly pathological stress that occurs during adaptive immunity.
Epigenetic control of gene expression is linked to the manner in which eukaryotic DNA associates with nuclear proteins, in a structure known as chromatin. The basic unit of chromatin is the nucleosome, which consists of approximately 147 bp of DNA wrapped around an octamer of core histones (which includes two each of histones H3, H4, H2A and H2B) (Luger et al., 1997; Davey et al., 2002). Further higher order structuring of nucleosomes through interactions with additional histone and non-histone proteins allows for tight compaction of the DNA into the limited volume of the nucleus (Talbert and Henikoff, 2010). In addition to permitting efficient DNA packing, chromatin provides an intricate scaffold for interacting with nuclear proteins such as those of the gene transcription machinery. Importantly, chromatin is subject to modifications that generate highly ordered sophisticated heterogeneity in its structure and, as a consequence, in the potential for different gene regions to be expressed. This recognition of and response to specific combinatorial patterns of modifications allows the complex epigenetic code to be translated into selective control of coordinated clusters of genes in transcriptional modules (Taverna et al., 2007; Hardison and Taylor, 2012).
Chromatin can be altered by modifications to both the DNA and the associated histone proteins. At the level of the DNA, the main modification described so far is methylation of cytosine residues, which occurs predominantly in the context of the dinucleotide sequence CpG and is mediated by members of the DNA-methyltransferase family (DNMT1, DNMT3A, DNMT3B) (Okano et al., 1999; Pradhan et al., 1999). DNA methylation leads to suppression of gene transcription through a number of mechanisms, including direct inhibition of transcription factor binding, which is necessary for recruitment of the transcription machinery, and attraction of methyl-CpG-binding domain-containing proteins that associate with transcriptionally repressive protein complexes (Reddington et al., 2013). Methyl marks can be removed from DNA in a passive manner through a failure to remethylate daughter DNA strands during cell division, or in an active process involving ten-eleven translocation (TET1-3) family proteins or DNA glycosylases and repair-mediated excision of modified bases (He et al., 2011b; Ito et al., 2011; Maiti and Drohat, 2011; Spruijt et al., 2013). Notably, TET enzymes generate intermediates in the pathway between 5-methylcytosine and cytosine, including 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxycytosine, which can be detected in cellular chromatin and may serve as epigenetic marks in their own right (Delatte and Fuks, 2013). The therapeutic potential of targeting DNA methylation including the activity of licensed pan-DNMT inhibitors to impact certain cancers has been reviewed recently (Carey et al., 2012), and will not be discussed further here.
Histone modification has been studied most extensively for the core histones of the nucleosome. Many different amino acids in these proteins are subject to post-translational modification, although the majority of these occur in the N-terminal or C-terminal ‘tails’ which extend outside of the main, globular histone domains (Kouzarides, 2007). By contrast to the relatively limited complexity of DNA methylation, histones can be modified in a wide variety of ways; by some accounts up to 60 different chemical modifications of histones have been documented, including acetylation, methylation, phosphorylation, ubiquitination, sumoylation, ADP ribosylation, crotonylation and biotinylation (Stanley et al., 2001; Kouzarides, 2007; Tan et al., 2011; Nikolov and Fischle, 2013). As discussed further below, several families of enzymes responsible for the addition (writers) or removal (erasers) of these modifications have been identified. The multiplicity of modifications and amino acid substrates can be arranged into a very high number of distinct combinations, which has prompted the hypothesis that the different patterns represent a ‘histone code’ that provides specific instructions for a given region of DNA (Strahl and Allis, 2000). Although there is presently little understanding of a detailed code, the functional relevance of histone modification to gene regulation is evident from observed correlations between the presence of certain combinations of marks and gene expression.
Histone modifications are thought to impact gene expression in two broad ways. First, certain modifications such as acetylation alter the net charge of the histone, weakening the DNA–histone interaction and yielding a chromatin structure that is more open and hence accessible to transcription factors and gene expression machinery (Hong et al., 1993). Second, and potentially more importantly, histone modifications serve as recognition marks for proteins termed epigenetic ‘readers’, which can specifically bind to these modified amino acids (Taverna et al., 2007). Thus, while writers and erasers produce the histone code, it is the epigenetic readers that decipher and translate this information (Figure 1). Reader proteins typically possess activities that lead to activation or suppression of gene expression, and/or are able to recruit other proteins that possess such functions. As is the case for the epigenetic writers and erasers, large families of readers able to recognize different modified amino acids have been identified and recently reviewed (Arrowsmith et al., 2012).
Figure 1.
Histone modification in the regulation of chromatin structure. Nucleosomes, which represent the core subunits of chromatin, are subject to numerous modifications that influence chromatin structure and gene expression. Many different amino acids in the core histones can be altered by enzymes termed epigenetic ‘writers’ that generate various post-translational modifications, such as acetylation, methylation and phosporylation. These marks can be removed by ‘erasers’ and are recognised by ‘reader’ proteins which contain domains capable of specific recognition of the modified peptide sequences.
Together, DNA and histone modifications help control the ‘transcribability’ of genes. Thus, linked to the state of the chromatin, a gene or gene cluster may be silenced, constitutively expressed or poised for expression (or suppression) in response to a specific cell signal (Kouzarides, 2007). The dynamic nature of chromatin modifications provides a mechanism for cells to adapt their gene expression pattern in response to environmental cues. This is now well documented for fundamental biological processes such as the differentiation of activated T-cells into effector subsets, where the capacity of the cells to produce different cytokines is controlled by epigenetic modifications in cytokine gene regions that are induced by specific conditions of T-cell activation (Kanno et al., 2012). However, there is also growing evidence that aberrant epigenetic states are associated with a range of pathologies, including inflammatory, neuropsychiatric, cardiovascular, and metabolic diseases and cancer. The identification of the proteins responsible for writing, erasing and reading chromatin modifications has opened up a new area of drug discovery, with the hope of being able to reset abnormal epigenetic landscapes back to normal and thus provide lasting health benefits in these diseases. In this review, we discuss early progress in developing small molecule pharmacological modulators of epigenetic targets, focusing on a subset of histone writers, erasers and readers where understanding of biological relevance and chemical tractability is most advanced.
Lysine acetyltransferases
Multiple lysine residues in each of the core histones are subject to acetylation. Histone acetylation is mediated by a family of enzymes, the lysine acetyltransferases (KATs), which utilize acetyl CoA as a cofactor to catalyse the transfer of an acetyl group to the ε-amino group of lysine side chains (Roth et al., 2001). At least 17 mammalian KATs able to acetylate histones have been identified, although the relatively low sequence homology among protein acetyltransferases suggests that many such enzymes could yet be discovered (Yuan and Marmorstein, 2012). These enzymes have traditionally been grouped into families based on similarity in the sequence of their catalytic domains and biochemical mechanism of acetyl transfer, and are listed utilizing the simplified nomenclature proposed by Allis et al. (Sterner and Berger, 2000; Roth et al., 2001; Allis et al., 2007; Furdas et al., 2012) in Table 1. Different KATs have been shown to preferentially actetylate distinct lysine residues in histones, although considerable overlap appears to exist.
Table 1.
Lysine acetyltransferases
| Family | Proposed symbol* | Synonyms and other symbols | Uni-ProtKB/Swiss-Prot assession number |
|---|---|---|---|
| GNAT | KAT2A | GCN5, GCN5L2, HGCN5, PCAF-b | Q92830 |
| KAT2B | PCAF, P/CAF | Q92831 | |
| KAT9 | ELP3, FLJ10422 | Q9H9T3 | |
| P300/CBP | KAT3A | CBP, CREBBP, RSTS, RTS | Q92793 |
| KAT3B | P300, EP300 | Q09472 | |
| MYST | KAT5 | TIP60, PLIP, HTATIP, cPLA2, HTATIP1, ESA1, ZC2HC5 | Q92993 |
| KAT6A | MOZ, MYST3ZNF220, RUNXBP2, ZC2HC6A | Q92794 | |
| KAT6B | MORF, MYST4, querkopf, qkf, MOZ2, ZC2HC7 | Q8WYB5 | |
| KAT7 | HBO1, MYST2, HBOA, ZC2HC7 | O95251 | |
| KAT8 | hMOF, MYST1, MOF, FLJ14040, ZC2HC8 | Q9H7Z6 | |
| Transcription factor-related | KAT4 | TAF1, TAF2A, BA2R, CCG1, CCGS, DYT3, NSCL2, TAFII250, DYT3/TAF1 | P21675 |
| KAT12 | TFIIIC90, GTF3C4 | Q9UKN8 | |
| NR co-activators | KAT13A | SRC1, NCOA1, F-SRC-1, NCoA-1, RIP160, bHLHe74 | Q15788 |
| KAT13B | AIB1, ACTR, SRC3, NCOA3, RAC3, P/CIP, TRAM-1, cAGH16, TNRC16, bHLHe42, SRC-3 | Q9Y6Q9 | |
| KAT13C | P160, NCOA2, TIF2, GRIP1, NCoA-2, bHLHe75 | Q15596 | |
| KAT13D | CLOCK, KIAA0334 | O15516 | |
| Type B (cytoplasmic) | KAT1 | HAT1/HATB | O14929 |
Proposed symbols are those suggested by Allis et al. (2007). A list of the proposed lysine acetyltransferase names and symbols that have been approved by the HUGO Gene Nomenclature Committee (HGNC) can be found at http://www.genenames.org/genefamilies/kdm-kat-kmt#KAT.
Two things are worth noting with respect to the designation of these enzymes as histone acetyltransferases. First, several of these KATs are known to also acetylate non-histone proteins, which may make an important contribution to their function; this idea is supported by the detection of lysine acetylation in nearly 2000 proteins involved in many key cellular processes (Choudhary et al., 2009). Second, in some cases, enzymes have only been shown directly to acetylate histones in vitro, and their ability to do so in a cellular context remains unknown.
Acetylation of histone tails has long been associated with active gene transcription (Marushige, 1976). This is linked to the ability of acetylation to generate a more open chromatin structure (Hong et al., 1993), and to the recruitment of specific reader proteins able to bind to acetylated histones (see below). Not surprisingly, therefore, many histone acetyltransferases are known to function in transcriptional activation. However, histone acetylation is also known to influence many other processes, including cell cycle progression, chromosome dynamics, DNA recombination, DNA repair and cellular apoptosis, indicating that acetylation plays a central role in regulating chromatin-related functions (Khan and Khan, 2010).
Misregulation of histone acetyltransferase activity has been linked to many different pathogenic states, including multiple cancers, neurodegenerative disorders, plus metabolic, respiratory, inflammatory and cardiovascular diseases; as such, KATs represent attractive targets for drug development (Adcock and Lee, 2006; Avvakumov and Cote, 2007; Grabiec et al., 2008; Ghizzoni et al., 2011; Iyer et al., 2011; Pirooznia and Elefant, 2013). Several different types of KAT inhibitors have been described (Table 2). Peptide-based bisubstrate inhibitors, in which CoA is covalently linked to the ζ nitrogen of the target lysine within histone peptides, act as structural mimics and can show sub-micromolar potency and selectivity between KAT subfamilies (Lau et al., 2000). However, since these inhibitors lack cellular permeability, they have limited use for evaluation of the cellular function of the KATs. Natural products isolated from a number of different plants, as well as their synthetic derivatives, have been shown to possess KAT inhibitory activity (Balasubramanyam et al., 2003; 2004a,b; Choi et al., 2009; Ravindra et al., 2009). In addition, small molecule KAT inhibitors have been identified by high-throughput biochemical and computational (virtual) screens (Gorsuch et al., 2009; Bowers et al., 2010). One compound identified from a virtual screen, C646, was reported to be selective for KAT3A/3B over other KATs and was shown to inhibit the growth of tumour cells in vitro (Bowers et al., 2010).
Table 2.
Examples of KAT inhibitors
| Compound | Structure | Potency (µM) | Known KAT target | Source | Reference |
|---|---|---|---|---|---|
| H3-CoA-20 |  |
0.5 | KAT2B | Peptide-based bisubstrate inhibitors | (Lau et al., 2000) |
| Lys-CoA |  |
0.5 | KAT3B | Peptide-based bisubstrate inhibitors | (Lau et al., 2000) |
| Anacardic acid |  |
5–8.5 | KAT2B, KAT3B | Cashew nut shell | (Balasubramanyam et al., 2003) |
| Curcumin |  |
25 | KAT3A, KAT3B | Turmeric (spice) | (Balasubramanyam et al., 2004b) |
| Garcinol |  |
5–7 | KAT2B, KAT3B | Garcinia indica fruit rind | (Balasubramanyam et al., 2004a) |
| Epigallocatechin-3-gallate (EGCG) |  |
30–50 | Pan-KAT | Green tea | (Choi et al., 2009) |
| Plumbagin (RTK1) |  |
20–50 | KAT3A, KAT3B, KAT2B | Plumbago rosea root | (Ravindra et al., 2009) |
| C646 |  |
5 | KAT3A, KAT3B | Small molecule virtual screen | (Bowers et al., 2010) |
Overall, however, the development of therapeutic KAT inhibitors is at an early stage, and current compounds are suboptimal in a number of ways, because they generally lack potency and selectivity. Nevertheless, one natural product KAT inhibitor, curcumin, has entered into clinical trials for a number of diseases, including Alzheimer's disease, rheumatoid arthritis, cystic fibrosis and psoriasis; there are currently 85 studies at different stages in http://ClincalTrials.gov that list curcumin or related compounds. As this compound is known to affect a number of other epigenetic and non-epigenetic targets, including DNMT I and lysine deacetylases (KDACs), linking potential efficacy with effects on KATs will not be straightforward.
Lysine deacetylases
The reversal of histone acetylation is mediated by members of the KDAC family, which comprises 18 enzymes that can be divided into four classes based on their homology to the yeast orthologues Rpd3, HdaI and Sir2 (Gregoretti et al., 2004) (Table 2013b). The class I, II and IV enzymes are termed histone deacetylases (HDACs), while the class III deacetylases are named sirtuins (SIRTs). The seven sirtuins (SIRT1–7) share a conserved catalytic core domain and use NAD+ as an essential cofactor, while HDACs contain a Zn2+ ion in their active site. Notwithstanding the nomenclature, several sirtuins do function as HDACs, while at least one HDAC, HDAC6, appears to be almost exclusively localized to the cytoplasm and may not deacetylate histones in vivo (Verdel et al., 2000; Zhang et al., 2003; Martinez-Redondo and Vaquero, 2013). In addition to deacetylase activity, some SIRT proteins also possess other enzymatic activities. Thus, while SIRT1–3 and SIRT7 act primarily as KDACs, SIRT4 is an ADP-ribosyltransferase, SIRT5 is a deacetylase, demalonylase, and desuccinylase, and SIRT6 is an ADP-ribosyltransferase and a deacetylase (Roth and Chen, 2013). As for the KATs, KDACs can deacetylate many histone and non-histone proteins.
Table 3.
Lysine deacetylases
| Class | Symbol | Cellular localization | Uni-ProtKB/Swiss-Prot assession number |
|---|---|---|---|
| I (Rpd3) | HDAC1 | Nucleus | Q13547 |
| HDAC2 | Nucleus | Q92769 | |
| HDAC3 | Nucleus | O15379 | |
| HDAC8 | Nucleus/cytoplasm | Q9BY41 | |
| IIa (Hda1) | HDAC4 | Nucleus/cytoplasm | P56524 |
| HDAC5 | Nucleus/cytoplasm | Q9UQL6 | |
| HDAC7 | Nucleus/cytoplasm | Q8WUI4 | |
| HDAC9 | Nucleus/cytoplasm | Q9UKV0 | |
| IIb (Hda1) | HDAC6 | Cytoplasm | Q9UBN7 |
| HDAC10 | Cytoplasm | Q969S8 | |
| III (Sir) | SIRT1 | Nucleus/cytoplasm | Q96EB6 |
| SIRT2 | Nucleus/cytoplasm | Q8IXJ6 | |
| SIRT3 | Mitochondria | Q9NTG7 | |
| SIRT4 | Mitochondria | Q9Y6E7 | |
| SIRT5 | Mitochondria | Q9NXA8 | |
| SIRT6 | Nucleus | Q8N6T7 | |
| SIRT7 | Nucleolus | Q9NRC8 | |
| IV (Rpd3/Hda1) | HDAC11 | Nucleus/cytoplasm | Q96DB2 |
In accordance with the key role that acetylation plays in the regulation of chromatin structure, as well as the expansive function of lysine acetylation in protein networks and cellular signalling pathways (Choudhary et al., 2009), HDACs have been implicated in the regulation of gene expression and in the control of many important cellular processes such as proliferation, DNA repair and apoptosis (Lahue and Frizzell, 2012; Li et al., 2012; Matthews et al., 2012; Yao and Rahman, 2012; Joshi et al., 2013; Ververis et al., 2013). Moreover, dysregulation of HDACs has been proposed to contribute to a variety of diseases including cancer, interstitial fibrosis, autoimmune and inflammatory diseases, and metabolic disorders (Tang et al., 2013a). For this reason, considerable effort has gone into the development of HDAC inhibitors.
Most of the HDAC inhibitors generated to date show activity against multiple family members. Among these, there is a range in the breadth of activity (Table 4) – from those that inhibit essentially all HDACs [e.g. trichostatin A and suberoylanilide hydroxamic acid (SAHA)], to some that are active against class I and IIa HDACs (e.g. butyric acid, valproic acid), to others that appear more selective to class I HDACs (e.g. romidepsin, MS-275) (Khan and La Thangue, 2012) or class IIa HDACs (Lobera et al., 2013). Experiments using such non-selective HDAC compounds have provided much of the evidence that HDAC inhibition could be effective in a range of therapeutic areas (Grabiec et al., 2011; Tang et al., 2013a). More recently, inhibitors with selectivity for HDAC1, HDAC3, HDAC6 and HDAC8 have been described (Hu et al., 2003; Schlimme et al., 2011; Cantley and Haynes, 2013; Jochems et al., 2013). Although there is currently limited understanding of the biological implications of targeting individual family members, HDAC6-selective compounds have been reported to inhibit cancer cell proliferation in vitro and in xenograft models in vivo and to exert antidepressant activity in a mouse model (Schlimme et al., 2011; Santo et al., 2012; Jochems et al., 2013). The latter activity was shown to be associated with increased acetylation of the HDAC6 target α-tubulin rather than histone acetylation (Jochems et al., 2013).
Table 4.
Examples of HDAC inhibitors
| Name | Structure | Potency | HDAC specificity | Clinical trial (cancer) |
|---|---|---|---|---|
| TSA (trichostatin A) |  |
1.8 nM (HDAC5) | Class I, II, IV | – |
| Vorinistat (SAHA, suberoylanilide hydroxamic acid) |  |
10 nM (HDAC1,2,3,8,9) | Class I, II, IV | FDA approved (2006) Phase II, III |
| Romidepsin (FK228) |  |
36–47 nM (HDAC1,2) | Class I | FDA approved (2009) Phase I, II |
| Entinostat (MS-275) |  |
500 nM (HDAC1,2,3,9) | Class I | Phase II |
| Mocetinostat (MGCD0103) |  |
0.15–1.66 µM (HDAC1,2,3) | HDAC1 | Phase I, II |
| Butyric acid |  |
mM | Class I, II | Phase II |
| Valproic acid |  |
0.7–20 mM (HDAC1,2,3) | Class I, II | Phase I, II, III |
| ACY-1215 (rocilinostat) |  |
5 nM | HDAC6 | Phase I/II |
The ability of HDAC inhibitors to induce death, cytostasis or differentiation of tumour cells in preclinical models, combined with evidence of HDAC up-regulation in a variety of cancers, has provided a strong rationale for progressing such compounds into clinical trials for oncology (Giannini et al., 2012). Presently, there are 394 trials that include the term ‘HDAC inhibitor’ recorded in http://ClinicalTrials.gov, with the vast majority of these being in cancer. A large number of trials in multiple solid and haematological tumour types are in progress, with the most promising results obtained so far being observed when HDAC inhibitors were combined with other agents such as proteasome inhibitors (Khan and La Thangue, 2012; Qiu et al., 2013; Richardson et al., 2013; Ververis et al., 2013). Currently, there are two HDAC inhibitors that have received approval from the US FDA for the treatment of cutaneous T-cell lymphoma: vorinostat (SAHA, Zolinza®; Merck & Co., Inc., Whitehouse Station, NJ, USA) and depsipeptide (romidepsin, Istodax, Celgene Corporation, Summit, NJ, USA).
Although broadly active HDAC inhibitors are being tested in the vast majority of trials, one HDAC1-selective inhibitor (MGCD0103) has progressed into clinical trials in haematological tumours, and a HDAC6-selective inhibitor is being evaluated as a monotherapy and also in combination with other treatments in patients with relapsed or relapsed/refractory multiple myeloma (NCT01323751, NCT01583283). By selectively targeting HDAC subfamily members, it is hoped that there will be an opportunity to reduce toxic side effects associated with broadly inhibiting lysine deacetylation and hence for an improved therapeutic treatment window. Another strategy being evaluated in this respect is to design compounds that will preferentially accumulate in specific cell types. This is the basis behind the HDAC inhibitor CHR-2845, a cell-permeant ester that is metabolized to give an active acid which selectively accumulates in monocytes and macrophages. This compound has been evaluated for tolerability in patients with advanced haematological malignancies (NCT00820508), and it is hoped that this approach will be effective in haematological malignancies involving cells of the monocyte lineage.
Reflecting the broad biological effects of HDAC inhibition in preclinical studies, HDAC inhibitors have also entered into trials in other therapeutic areas, including graft versus host disease (NCT01111526), sickle cell disease (NCT01000155), Huntington's disease (NCT00212316), Rubinstein–Taybi syndrome (NCT01619644) and human immunodeficiency virus (HIV; NCT01680094). In the latter study, the aim is to evaluate the ability of the compound to reactivate HIV transcription in latently infected CD4+ T-cells, which would form part of an approach to deplete the latent pool of virus (in combination with anti-retroviral therapy). Evidence that HDAC inhibitors can induce such HIV reactivation has come from studies involving ex vivo compound treatment of cells from HIV-infected individuals, although initial small scale clinical trials have yielded conflicting results concerning the combined effects of HDAC inhibition and anti-retroviral therapy on viral load (Margolis, 2011).
Much of the interest in the SIRT family of KDACs has focused on the function of these enzymes in metabolic, oxidative/genotoxic, and oncogenic stress responses, where their deacetylation of non-histone substrates may play a predominant role. In view of the protective role of SIRTs in these processes, a major therapeutic focus has been on the development of SIRT activators for the treatment of ageing-associated pathologies, including type II diabetes, cardiovascular disease and neurodegeneration (Hall et al., 2013). SIRT1 activation has also been implicated in suppressing the immune response, leading to an interest in developing SIRT activators for treatment of autoimmune and inflammatory diseases (Kong et al., 2013). In cancer, the role of SIRT proteins is complex, with evidence for SIRTs playing roles in both promoting and suppressing tumourigenesis (Roth and Chen, 2013).
Small molecules capable of SIRT1 activation have been identified, including the weakly active polyphenol compound resveratrol, a component of red wine, and a series of compounds structurally unrelated to resveratrol with 1000-fold greater potency against SIRT1 (Dittenhafer-Reed et al., 2011). SIRT1 activators became the subject of controversy when it was shown that these compounds activated enzyme activity towards fluorescently labelled peptide substrates but not their unlabelled counterparts, suggesting a possible assay artefact (Kaeberlein et al., 2005; Pacholec et al., 2010). However, an intriguing explanation for these observations was subsequently provided when it was shown that the bulky hydrophobic fluorophore tag on the assay peptide mimicked hydrophobic amino acids present in a subset of natural SIRT1 protein substrates that are selectively subject to increased deacetylation after SIRT1 activation (Hubbard et al., 2013; Lakshminarasimhan et al., 2013). In addition, a single amino acid substitution outside of the catalytic site in SIRT1 was found to abolish activation of the enzyme as well as the cellular effects mediated by SIRT1 activators, demonstrating that SIRT1 is indeed the target of these compounds.
Trials of resveratrol in obese humans produced mild improvements in a number of different clinical parameters including systolic blood pressure, circulating cytokines, intrahepatic fat content, intramyocellular lipid content, and muscle mitochondrial oxidative phosphorylation capacity (Timmers et al., 2011). However, because resveratrol has known activity against a number of substrates besides SIRT1, including AMP-activated kinase, a fuel-sensing enzyme that is responsive to decreases in cellular energy status, the mechanism by which resveratrol mediates these effects, remains a subject of debate. Early phase clinical trials investigating higher potency SIRT1 activators (SRT2104, SRT2379) in both metabolic diseases and inflammation have been conducted (Libri et al., 2012; Hoffmann et al., 2013). Published results for SRT2104 indicate that this compound appears to be safe and well tolerated and associated with an improved lipid profile (Libri et al., 2012).
Lysine methyltransferases
A large number of enzymes capable of transferring methyl groups to lysine residues have been described. The 24 human lysine methyltransferases (KMTs) categorized by Allis et al. (2007) are listed in Table 5. All KMTs except one [KMT4/Dot1L, a unique KMT, which belongs to the class I methyltransferase family (Min et al., 2003)] contain a catalytic domain of approximately 130 amino acids, referred to as the SET domain; both SET domain-containing enzymes and KMT4 use S-adenosyl methionine (SAM) as the methyl donor. Based on a systematic screen for SET domains in the human genome, 51 putative KMTs have been identified, although the enzymatic activity of many of these is yet to be investigated (Copeland et al., 2009; Richon et al., 2011). KMTs exhibit selectivity for both the lysine residue they can modify and the degree to which that lysine residue is methylated. Thus, while lysine residues can only accept a single acetyl group, lysines can be mono-, di- or trimethylated. The site specificity of lysine methylation is determined by recognition of amino acid residues flanking the target lysine, whereas particular amino acids within the lysine-binding channel of the KMTs play an important role in dictating the methylation multiplicity of the SET domain (Qian and Zhou, 2006).
Table 5.
Lysine methyltransferases
| Proposed symbol* | Synonyms and other symbols | Histone substrate specificity | Uni-ProtKB/Swiss-Prot assession number |
|---|---|---|---|
| KMT1A | SUV39H1, SUV39H | H3K9me2/3 | O43463 |
| KMT1B | SUV39H2, FLJ23414 | H3K9me2/3 | Q9H5I1 |
| KMT1C | G9a, EHMT2, C6orf30, BAT8, Em:AF134726.3, NG36/G9a | H3K9me1/2, H1K26me1/2 | Q96KQ7 |
| KMT1D | GLP, EHMT1, Eu-HMTase1, FLJ12879, KIAA1876, bA188C12.1 | H3K9me1/2 | Q9H9B1 |
| KMT1E | ESET, SETDB1, KG1T, KIAA0067, TDRD21 | H3K9me2/3 | Q15047 |
| KMT1F | SETDB2, CLL8, C13orf4, CLLD8 | H3K9me2/3 | Q96T68 |
| KMT2A | MLL1, TRX1, HRX, ALL-1, HTRX1, CXXC7, MLL1A, MLL | H3K4me1/2/3 | Q03164 |
| KMT2B | MLL2, KIAA0304, TRX2, HRX2, WBP7, MLL1B, MLL4 | H3K4me1/2/3 | Q9UMN6 |
| KMT2C | MLL3, KIAA1506, HALR | H3K4me1/2/3 | Q8NEZ4 |
| KMT2D | MLL4, TNRC21, MLL2, ALR, CAGL114 | H3K4me1/2/3 | O14686 |
| KMT2E | MLL5, HDCMC04P | H3K4me1/2/3 | Q8IZD2 |
| KMT2F | hSET1A, SETD1A, KIAA0339, Set1 | H3K4me1/2/3 | O15047 |
| KMT2G | hSET1B, SETD1B, KIAA1076, Set1B | H3K4me1/2/3 | Q9UPS6 |
| KMT2H | ASH1, ASH1L, huASH1, ASH1L1 | H3K4me1/2/3, H3K9me1/2/3, H4K20me1/2/3 | Q9NR48 |
| KMT3A | SET2, SETD2, HYPB, HIF-1, KIAA1732, FLJ23184 | H3K36me3 | Q9BYW2 |
| KMT3B | NSD1, STO, ARA267, FLJ22263 | H3K36me1/2, H4K20me1/2 | Q96L73 |
| KMT3C | SYMD2, HSKM-B, ZMYND14 | H3K36me1/2 | Q9NRG4 |
| KMT3D | SMYD1, BOP, ZMYND22 | Unknown | Q8NB12 |
| KMT3E | SMYD3, ZNFN3A1, ZMYND1 | H3K4me2/3 | Q9H7B4 |
| KMT4 | DOT1L, KIAA1814, DOT1 | H3K79me1/2/3 | Q8TEK3 |
| KMT5A | Pr-SET7, SETD8, SET07, SET8 | H4K20me1 | Q9NQR1 |
| KMT5B | SUV420H1, CGI-85 | H4K20me2/3 | Q4FZB7 |
| KMT5C | SUV420H2, MGC2705 | H4K20me2/3 | Q86Y97 |
| KMT6A | EZH2, EZH1, ENX-1, KMT6 | H3K27me1/2/3, H1K26me2/3 | Q15910 |
| KMT6B | EZH1, KIAA0388 | H3K27me1/2/3 | Q92800 |
| KMT7 | SET7/9, KIAA1717, SET7, Set9 | H3K4me2 | Q8WTS6 |
| KMT8 | PRDM2, RIZ1, RIZ, RIZ2, MTB-ZF, HUMHOXY1 | H3K9me1/2/3 | Q13029 |
Proposed symbols are those suggested by Allis et al. (2007). A list of the proposed lysine methyltransferase names and symbols that have been approved by the HUGO Gene Nomenclature Committee (HGNC) can be found at http://www.genenames.org/genefamilies/kdm-kat-kmt#KMT.
In contrast to histone acetylation, histone methylation does not alter the charge of the histone tail, but instead influences its basicity and hydrophobicity (Migliori et al., 2010). As for acetylation, methylated lysines also serve as recognition marks for a large family of methyl reader proteins, which show selectivity for both the specific lysine residue modified and the degree of methylation. As a consequence, different types of lysine methylation are associated with divergent functions in the regulation of gene expression. For example, trimethylation of H3K4 (H3K4me3) is commonly found near the transcription start site of genes that are actively expressed or poised for expression, whereas H3K27me3 is a mark that is associated with genes for which expression is suppressed (Kouzarides, 2007). Conversely, the presence of H3K4me1 is tightly correlated with the position of gene enhancers, which are non-coding regions of DNA that promote the expression of genes that are often located a considerable distance away (Heintzman et al., 2009).
In addition to the histone tail, the residues within the core of the nucleosome can also be modified by methylation. For instance, H3K79 is subject to methylation by KMT4, and methylated H3K79 is associated with active gene transcription (Feng et al., 2002; Steger et al., 2008; Kim et al., 2013). Lysine 20 is the only well-characterized methylation site on histone H4, with methylated H4K20 being linked with transcriptional repression and a number of biological processes, including the DNA damage response, mitotic condensation and DNA replication (Jorgensen et al., 2013); the transition from H4K20me1 to me2 and me3 was recently associated with cellular quiescence (Evertts et al., 2013).
Misregulation of KMTs has been linked to a variety of human diseases, and therapeutic interest in the development of KMT inhibitors is particularly strong in cancer, where the pathological involvement of KMT overexpression, mutation and translocation has been shown (Copeland et al., 2009). One interesting example of a potential cancer target is KMT4, which is implicated in leukaemias involving chromosomal translocation of another KMT, KMT2A (MLL1). In such cancers, KMT4 is recruited into the transcriptional complex via MLL-fusion partners, and aberrant methylation of H3K79 is considered to play a causative role in disease (Steger et al., 2008; Bernt et al., 2011). Another target of major interest is KMT6, which is a key mediator of di- and trimethylation of H3K27 and is overexpressed in many types of cancers (Chang and Hung, 2012).
In recent years, small molecule KMT inhibitors have been developed that are directed at either the SAM or the substrate site of the enzymes (Wigle and Copeland, 2013). Inhibitors have been reported for various KMTs, including KMT4, KMT6, KMT1C/D, KMT3C and KMT5A (Table 6). Compounds targeting KMT4, KMT1C/D and KMT6 have shown promising efficacy in preclinical tumour models (Daigle et al., 2011; 2013; Yuan and Marmorstein, 2012; Yuan et al., 2012; Knutson et al., 2013; Liu et al., 2013), strengthening the rationale for targeting these enzymes in cancer. Building on this rationale, the KMT6 inhibitor E7438 is currently being trialled in patients with advanced solid tumours or with B-cell lymphomas (Knutson et al., 2013) (NCT01897571) while the KMT4 inhibitor EPZ-5676 has recently entered phase I studies in patients with advanced haematological malignancies (NCT01684150) (Copeland, 2013; Daigle et al., 2013).
Table 6.
Recent examples of lysine methyltransferase inhibitors
| Name | Structure | Potency | KMT specificity | Reference |
|---|---|---|---|---|
| EPZ-6438 |  |
2.5 nM | MT6 | (Knutson et al., 2013) |
| GSK126 |  |
0.5–3 nM | KMT6 | (McCabe et al., 2012) |
| EI1 |  |
9.4 nM | KMT6 | (Qi et al., 2012) |
| BIX-01294 |  |
2.7 µM | KMT1C/D | (Kubicek et al., 2007; Lu et al., 2013) |
| UNC0638 |  |
<15 nM | KMT1C/D | (Vedadi et al., 2011) |
| BRD4770 |  |
6.3 µM | KMT1C/D | (Yuan and Marmorstein, 2012; Yuan et al., 2012) |
| UNC0642 |  |
<2.5 nM | KMT1C/D | (Liu et al., 2013) |
| Bromo-deaza-SAH |  |
77 nM | KMT4 | (Yu et al., 2013) |
| EPZ-5676 |  |
80 pM | KMT4 | (Daigle et al., 2011) |
| SGC0946 |  |
0.3 nM | KMT4 | (Yu et al., 2012) |
| AZ505 |  |
0.12 µM | KMT3C | (Ferguson et al., 2012) |
| Nahuoic acid |  |
2 µM | KMT5A | (Williams et al., 2013) |
Lysine demethylases
Lysine-specific demethylases (KDMs) capable of removing methyl groups from histones are classified into two families (Table 7). One family is comprised of KDM1A (LSD1) and the closely related KDM1B (LSD2), demethylate lysines, utilizing a flavin adenine dinucleotide (FAD)-dependent oxidation mechanism (Shi et al., 2004; Karytinos et al., 2009). KDM1A and KDM1B are able to demethylate mono- and dimethylated lysines, but cannot remove the methyl group from trimethylated lysine because of the dependence of the demethylation mechanism on a protonated amine (Hou and Yu, 2010). The second much larger family of histone demethylases is formed by the jumonji C-domain (Jmj)-containing enzymes, which catalyse lysine demethylation through a hydroxylation pathway utilizing Fe2+ and α-ketoglutarate (α-KG) as cofactors (Tsukada et al., 2006). Unlike KDM1A and KDM1B, the Jmj family of enzymes does not depend on a protonated amine and therefore can demethylate trimethylated lysines.
Table 7.
Lysine demethylases
| Proposed symbol* | Synonyms and other symbols | Reported histone substrate specificity | Uni-ProtKB/Swiss-Prot assession number |
|---|---|---|---|
| KDM1A | LSD1, AOF2, BHC, KIAA0601, BHC110, | H3K4me1/2, H3K9me1/2 | O60341 |
| KDM1B | LSD2, AOF1, C6orf193, FLJ34109, FLJ33898, dJ298J15.2, bA204B7.3, FLJ43328 | H3K4me1/2 | Q8NB78 |
| KDM2A | JHDM1A, FBXL11, CXXC8, FBL7, KIAA1004, FBL11, LILINA, DKFZP434M1735, FLJ00115 | H3K4me3, H3K36me1/2 | Q9Y2K7 |
| KDM2B | JHDM1B, FBXL10, CXXC2, FBL10, PCCX2 | H3K36me1/2 | Q8NHM5 |
| KDM3A | JMJD1A, JHDM2A, JMJD1, KIAA0742, TSGA | H3K9me1/2 | Q9Y4C1 |
| KDM3B | JMJD1B, JHDM2B, C5orf7, KIAA1082NET22 | H3K9me1/2 | Q7LBC6 |
| KDM3C | JMJD1C, JHDM2C | H3K9me1/2 | Q15652 |
| KDM4A | JMJD2A, JHDM3A, JMJD2, KIAA0677, TDRD14A | H3K9me2/3, H3K36me2/3, H1K26me3 | O75164 |
| KDM4B | JHDM3B, JMJD2B, KIAA0876, TDRD14B | H3K9me2/3, H3K36me2/3, H1K26me3 | O94953 |
| KDM4C | JMJD2C, GASC1, JHDM3C, KIAA0780, TDRD14C | H3K9me2/3, H3K36me2/3, H1K26me3 | Q9H3R0 |
| KDM4D | JMJD2D, JHDM3D, FLJ10251 | H3K9me2/3, H1K26me2/3 | Q6B0I6 |
| KDM4E | JMJD2E, KDM4DL | H3K9me2/3 | B2RXH2 |
| KDM5A | JARID1A, RBBP2, RBP2 | H3K4me1/2/3 | P29375 |
| KDM5B | JARID1B, PLU-1, RBBP2H1, RBBP2H1A, CT31 | H3K4me1/2/3 | Q9UGL1 |
| KDM5C | JARID1C, SMCX, DXS1272E, XE169, MRX13 | H3K4me1/2/3 | P41229 |
| KDM5D | JARID1D, SMCY, HY, HYA, KIAA0234 | H3K4me2/3 | Q9BY66 |
| KDM6A | UTX | H3K27me2/3 | O15550 |
| KDM6B | JMJD3, KIAA0346 | H3K27me2/3 | O15054 |
| KDM7A | JHDM1D, KIAA1718 | H3K9me1/me2, H3K27me1/me2 | Q6ZMT4 |
| KDM7B | PHF8, JHDM1F, KIAA1111, ZNF422, DKFZp686E0868 | H3K9me2/me1, H3K27me2, H3K36me2 | Q9UPP1 |
| KDM7C | PHF2, JHDM1E, GRC5, KIAA0662, MGC176680, CENP-35 | H3K9me2 | O75151 |
| KDM8 | JMJD5, FLJ13798 | H3K36me2 | Q8N371 |
Proposed symbols are those suggested by Allis et al. (2007). A list of the proposed lysine demethylase names and symbols that have been approved by the HUGO Gene Nomenclature Committee (HGNC) can be found at http://www.genenames.org/genefamilies/kdm-kat-kmt#KDM.
As a group, the KDMs have been reported to erase a range of methyl marks on histones (Table 7). Enzymes show preferences for both the degree of lysine methylation and the histone sequence, although promiscuity with respect to the latter is exhibited by some KDMs. This promiscuity can be attributed to the presence of similar amino acids flanking the methylated lysine in distinct peptides or to a dominant role of the peptide backbone, rather than the side chains, in recognition by the enzyme (Hou and Yu, 2010). Importantly, while substrate specificity is often defined in vitro using isolated catalytic domains, the actual lysine residues targeted in vivo may be confined by other mechanisms. For example, although KDM7B can demethylate H3K9me2/me1, H3K27me2 and H3K36me2 in vitro, the intact protein contains a plant homeo domain finger that binds to H3K4me3, directing the catalytic domain towards H3K9me2 (Horton et al., 2009). In addition to regulation by other domains within the same protein, KDMs are typically found within multi-protein complexes that will greatly influence their targeting to chromatin. As for other histone-modifying enzymes, the KDMs can also act on non-histone substrates, which may play a key role in their function. For example, KDM1A has been shown to demethylate key cellular targets such as p53, DNMT 1, STAT3, E2F1 and MYPT1 (Huang et al., 2007a; Wang et al., 2009a; Kontaki and Talianidis, 2010; Yang et al., 2010; Cho et al., 2011).
Given the correlation between particular methyl marks and the transcriptional state of genes, it is expected that the activity of specific KDMs will be linked to gene activation or repression, depending on the KDM substrate. Notably, however, some KDMs such as KDM1A possess the capacity to erase marks associated with both active (H3K4me2) and silent (H3K9me2) genes. In addition, there is considerable apparent redundancy in substrate specificity, with multiple KDMs able to erase the same marks (Table 7). Thus, the functions of KDMs within cells are likely to be determined by multiple factors such as KDM expression level, enzymatic activity, and targeting to specific sites within the genome in the context of particular cells and specific environmental signals. The development of potent and selective inhibitors against members of the family combined with sophisticated epigenetic mapping of functional outcomes (mark and gene transcription level) will be essential to define these in a cellular context.
A major focus of therapeutic interest in KDMs is in oncology, as mutations and aberrant expression of KDMs have been linked to various cancers (Hojfeldt et al., 2013). For example, KDM1A is reported to be overexpressed in a number of different cancers, including neuroblastoma, breast cancer, lung cancer, prostate cancer and bladder cancer (Schulte et al., 2009; Chi et al., 2010; Lim et al., 2010; Hayami et al., 2011). The other FAD-dependent KDM, KDM2B, has also been linked to cancer, with amplification and high expression observed in urothelial carcinoma (Heidenblad et al., 2008). Likewise, Jmj KDMs including KDM2B, KDM4A, KDM4B, KDM4C, KDM5B and KDM7C have been shown to be overexpressed in breast, colorectal, lung, prostate, bladder and other tumours; the functional significance of KDM4C overexpression is further suggested by the presence of the KDM4C gene within an amplified region of a chromosome in multiple cancers (Xiang et al., 2007; Couvelard et al., 2008; Roesch et al., 2010; He et al., 2011a; Berry and Janknecht, 2013; Kogure et al., 2013; Tzatsos et al., 2013). Notably, both increased and decreased expressions of KDMs may be associated with cancer, suggesting a key role for precise control of lysine methylation in maintaining cellular homeostasis. For example, while overexpression of KDM6A is associated with breast cancer and renal cell carcinoma, inactivating mutations in KDM6A are also found in multiple cancer types (van Haaften et al., 2009; Dalgliesh et al., 2010; Gui et al., 2011; Shen et al., 2012; Paolicchi et al., 2013). Inactivating mutations in other KDMs such as KDM5A have also been linked to cancer, supporting the notion that these proteins can have a tumour suppressor function (Dalgliesh et al., 2010).
Although presently there is much less information linking KDMs to other therapeutic areas, there is suggestive genetic evidence that altered KDM activity may be relevant to a number of diseases. For instance, single nucleotide polymorphisms (SNPs) in KDM5A and KDM1A have been linked to the autoimmune diseases ankylosing spondylitis and Grave's disease respectively (Newby et al., 2010; Pointon et al., 2011). KDM6B has also been implicated in an autoimmune disease based on its overexpression in antineutrophil cytoplasmic autoantibody-associated vasculitis (Ciavatta et al., 2010). In addition, SNPs in KDM4C have been linked with autism, and SNPs in KDM3C have been linked with a number of metabolic and haematological parameters, while mutations in KDM5C cause a form of X-linked mental retardation (Jensen et al., 2005; Yuan et al., 2008; Chasman et al., 2009; Soranzo et al., 2009; Johnson et al., 2010; Kantojarvi et al., 2010). Finally, possible therapeutic applications in virus infections are suggested by the demonstrated role for KDM1A in alpha herpes virus reactivation from latency (Liang et al., 2009).
A number of small molecules have been described that inhibit the demethylase activity of KDM1A, the first histone KDM identified. Early KDM inhibitors were generated based on the homology of KDM1A/B with MAOs, which also use FAD as a cofactor. Many of these inhibitors, such as trans-2-phenylcyclopropylamine (PCPA) and paraglyne, are non-specific and broadly inhibit MAOs (Metzger et al., 2005; Lee et al., 2006; Culhane et al., 2010). Derivatives of these molecules that possess some selectivity for KDM1A over MAOs have been produced, such as OG-L002 (>30-fold selective for KDM1A) (Liang et al., 2013) (Table 8). Peptide-based inhibitors (N-propargyl lysine-containing H3 peptides) with greater potency and selectivity than the MAO inhibitors have also been developed, but these possess poor cell permeability and hence are of limited use to investigate cellular activity (Szewczuk et al., 2007; Yang et al., 2007; Culhane et al., 2010; Dancy et al., 2012). Conversely, hybrid molecules between PCPA and lysine produced cell active inhibitors with significant selectivity for KDM1A over MAOs (Ueda et al., 2009; Ogasawara et al., 2011) (Table 8). Selective KDM1 inhibitors have also been developed based on the homology of this enzyme to polyamine oxidases and on the basis of structural features of the KDM1 active site (Huang et al., 2007b; 2009b; Wang et al., 2011).
Table 8.
Examples of KDM inhibitors
In recent years, considerable progress has also been made in the development of inhibitors targeting the more recently discovered Jmj KDMs. Based on the requirement of these enzymes for α-KG as a cofactor, α-KG analogues such as N-oxalylglycine (NOG) and α-hydroxyglutarate and their derivatives have been investigated and shown to act as low potency non-selective inhibitors of this target class (Cloos et al., 2006; Rose et al., 2008; 2010; Hamada et al., 2010; Chowdhury et al., 2011). More potent compounds that function through α-KG competition have also been identified based on small molecule screens (Rose et al., 2008; King et al., 2010; Chang et al., 2011). In addition, compounds showing selectivity for Jmj KDMs over NOG have been identified (Hamada et al., 2010).
While most of these ligand-based inhibitors are promiscuous KDM inhibitors, some compounds with more selective activities have been reported. For example, the plant growth regulator daminozide was shown to be an α-KG-competitive inhibitor that is much more potent against KDM2 and KDM7 family enzymes than other KDMs (Rose et al., 2012); other compounds with a biased activity against KDM2 and KDM7 family enzymes have been developed based on the crystal structure of KDM7B (Suzuki et al., 2013). High-throughput screening has been used to identify inhibitors of KDM4C and KDM5B (Hutchinson et al., 2012; Sayegh et al., 2013). In addition, inhibitors showing selectivity for KDM4 subfamily enzymes have been developed using a peptide-based approach, in which an α-KG analogue was linked to a small histone peptide bearing the target of these enzymes, H3(7–14)K9me3 (Woon et al., 2012). Finally, structural knowledge of mode of binding of the H3K27me3 peptide to KDM6B was used to drive the development of the compound GSK-J1, which has selectivity for KDM6A/B over other tested KDMs (Kruidenier et al., 2012) (Table 8).
Given that many of the KDM inhibitors developed so far, while improving are relatively non-selective, the therapeutic utility of targeting specific KDMs remains to be determined. However, inhibitors with some level of selectivity have shown potentially promising effects in early preclinical models. For example, certain KDM1A inhibitors have been shown to inhibit proliferation of cancer cells in vitro and to block herpes simplex virus lytic replication and reactivation from latency (Liang et al., 2009; Wang et al., 2011; Willmann et al., 2012). In addition, a cell-penetrant prodrug version of GSK-J1 (GSK-J4) was recently shown to inhibit the production of pro-inflammatory cytokines by human macrophages, supporting the notion of targeting KDM6A/B for inflammatory diseases (Kruidenier et al., 2012) consistent with initial evidence in mouse macrophages (De Santa et al., 2007; 2009).
Arginine methyltransferases
In addition to lysine residues, histone arginines are also subject to methylation (Di Lorenzo and Bedford, 2011). Such methylation is favoured by the presence of glycine-arginine rich sequences (GAR motifs), although these are neither necessary nor sufficient. Methylated guanidine nitrogen atoms on peptidyl-arginine residue confer differential packaging, structural changes and altered protein interactions. Additional levels of intricacy result from differential dimeric processing of mono-methylated arginine (MMA) into either an asymmetrical- dimethylarginine (ADMA) or symmetrical-dimethylarginine (SDMA) residue.
To date, there are 11 proteins generally accepted as being members of the family of protein arginine methyltransferases (PRMTs), identified either on the basis of demonstrable methyltransferase activity, typically using SAM as the methyl donor, or homology to other family members (Table 2004a) (Wolf, 2009). However, a systematic survey of the human genome identified 44 putative PRMTs based on sequence homology at the active site, suggesting that this number could be much higher (Richon et al., 2011). The 11 commonly accepted PRMTs have been classified into subgroups with different profiles (Yang and Bedford, 2013) (Table 2004a). All PRMTs can generate MMA, while type I PRMTs (PRMT1–4, 6 and 8) generate ADMA and type II PRMTs (PRMT5, 9) produce SDMA. PRMT7 appears to generate only MMA and has been termed as type III PRMT, although its capacity to produce SDMA remains a subject of debate (Zurita-Lopez et al., 2012). The most recent family members (PRMT10-11) await definitive characterization. PRMT1 has been proposed to be the dominant cellular PRMT enzyme on account of its driving 85% of arginine methylation in diverse cells (Tang et al., 2000).
Table 9.
Arginine methyltransferases
| Symbol | Family | Synonyms and other symbols | Reported histone substrate | Uni-ProtKB/Swiss-Prot assession number |
|---|---|---|---|---|
| PRMT1 | Type I | ANM1, HCP1, IR1B4, HRMT1L2 | H4R3 H4R3 | Q99873 |
| PRMT2 | Type I | MGC11137, HRMT1L1 | H4 | P55345 |
| PRMT3 | Type I | HRMT1L3 | O60678 | |
| PRMT4 | Type I | CARM1 | H3R17, H3R26 | Q86X55 |
| PRMT5 | Type II | JBP1, SKB1, IBP72, SKB1hs, HRMT1L5 | H3R8, H4R3 | O14744 |
| PRMT6 | Type I | FLJ10559, HRMT1L6 | H3R2, H2AR29, H4R3, H2AR3 | Q96LA8 |
| PRMT7 | Type II, III | FLJ10640, KIAA1933, [Myelin basic protein]-arginine N-methyltransferase | H4R3, H2AR3, H3R2 | Q9NVM4 |
| PRMT8 | Type I | HRMT1L4 | Unknown | Q9NR22 |
| PRMT9 | Type II | FBOX11, VIT1, UBR6, FLJ12673, MGC44383 | Unknown | Q86XK2 |
| PRMT10 | Not classified | LOC90826, FLJ46629 | Unknown | Q6P2P2 |
| PRMT11 | Not classified | FBX10, FBXO10, FLJ41992, MGC149840 | Unknown | Q9UK96 |
Most PRMTs are ubiquitously expressed, although PRMT8 is reported to be selectively expressed in the CNS (Lee et al., 2005; Kousaka et al., 2009). Lethal mouse phenotypes have been observed after knockout of at least two family members (PRMT1 and PRMT4), suggesting that these proteins have non-redundant functions (Pawlak et al., 2000; Yadav et al., 2003).
The functional consequences of protein arginine methylation are ranging wide across most physiological processes, including growing evidence for a role in epigenetic regulation. In accordance with such a function, nuclear shuttling or localization has been demonstrated for some PRMTs [e.g. for PRMT1 and PRMT6 (Frankel et al., 2002; Herrmann and Fackelmayer, 2009)]. Conversely, PRMT3 appears to be predominantly cytosolic and hence may not have a physiological role in histone methylation (Frankel and Clarke, 2000). Although understanding of histone arginine methylation has historically trailed that of lysine methylation, PRMTs have been identified as members of transcriptional complexes and can be recruited onto promoters by the action of transcription factors such as NF-κB and p53 (An et al., 2004; Covic et al., 2005). A growing number of PRMTs (including PRMT1, PRMT2, PRMT4, PRMT5, PRMT6 and PRMT7) are known to methylate different combinations of arginine residues on histones H2A, H3 and H4 (Table 2004a) with effects on chromatin accessibility.
Arginine methylation (and ADMA vs. SDMA methylation) may be stimulatory or inhibitory to transcription, depending on the histone context, the modifying enzyme and the degree of dimethylation. Co-integration with other histone code modifications has been reported. For example, PRMT1-mediated methylation of H4R3 facilitates subsequent acetylation (Wang et al., 2001) while PRMT6-mediated methylation of H3R2 prevents H3K4 methylation by the MLL complex, effectively repressing transcriptional elongation (Hyllus et al., 2007). Conversely, histone H3K18 acetylation primes the histone tail for asymmetric dimethylation at arginine 17 (H3R17me2a) by PRMT4 (Daujat et al., 2002; An et al., 2004), while H3K9ac blocks H3R8 symmetric dimethylation (H3R8me2s) by PRMT5 (Pal et al., 2004).
These subtleties further emphasize the combinatorial complexity and likely exquisite selectivity of such epigenetic changes. However, histone methylation represents only part of the regulatory transcriptional potential of PRMTs, which also includes methylation and modulation of transcription factors such as CBP (Chevillard-Briet et al., 2002) and Tat (Boulanger et al., 2005), effects on RNA stability and splicing, and genomic reorganization via methylation of AT hooks of nuclear scaffold proteins such as HMGA proteins (Sgarra et al., 2003; Edberg et al., 2004). In keeping with their broad effects, PRMT1 and PRMT4 are considered to function as general transcription factors. Although understanding of how methylarginine marks are subsequently ‘read’ to activate transcription is currently limited, a recent study reported that PRMT4-mediated asymmetric dimethylation of H3R17 (a stimulatory modification) facilitates transcription elongation through recruitment of the PAF1 complex to activate oestrogen-receptor-dependent gene transcription, suggesting a possible model that other PRMTs may also use (Wu and Xu, 2012).
Abnormal PRMT expression or activity is increasingly being associated with a growing list of diseases. At present, the major link is between PRMTs and cancer. In particular, PRMT1 is considered key for transformation by the MLL complex (Cheung et al., 2007). However, studies also support a potential role for therapeutic intervention in pulmonary and viral disorders (Boulanger et al., 2005; Sun et al., 2012; Zakrzewicz et al., 2012) as well as spinal muscular atrophy (Brahms et al., 2001).
Aided by increased understanding of catalytic mechanisms and knowledge of a number of PRMT crystal structures, several interesting tool molecules have been identified (Wigle and Copeland, 2013) (see Table 2004b for examples). Since the discovery of the first PRMT family inhibitor truly selective for methyltransferase activity [AMI-1 (Cheng et al., 2004)], screens have been run successfully and novel chemical equity has been disclosed, including the cellular inhibitor RM65 (Spannhoff et al., 2007). In a flurry of recent published activity, for example (Bissinger et al., 2011; Hart et al., 2011), the rational design of C21, a chloroacetamidine-bearing histone H4 tail analogue that acts as an irreversible PRMT1 inhibitor (Obianyo et al., 2011), has been included. Progress towards selectivity within the PRMT family, originally thought challenging due to the high sequence conservation, is also encouraging (Dillon et al., 2012; Dowden et al., 2012), because such selectivity may prove necessary to maximize therapeutic index. Additional exemplars include potent PRMT4 inhibitors from BMS (Huynh et al., 2009 and Wan et al., 2009) and a PRMT3-selective inhibitor that is also reported to be the first allosteric inhibitor of PRMTs or indeed of any reader, writer, eraser of methyl marks (Siarheyeva et al., 2012). These promising early probes raise the hope that, with appropriate lead optimization, molecules with suitable pharmacokinetic and development properties for in vivo and clinical testing may be identified.
Table 10.
Examples of PRMT inhibitors
| Inhibitor | Structure | Potency | Reported target | Reference |
|---|---|---|---|---|
| AMI-1 |  |
8.8 µM (PRMT1) | Pan-PRMT | (Cheng et al., 2004) |
| RM65 |  |
55 µM | PRMT1 (not tested vs. other PRMTs) | (Spannhoff et al., 2007) |
| BMS pyrazole inhibitor 7f |  |
40 nM | PRMT4 | (Huynh et al., 2009) |
| Benzo[d]imidazole inhibitors of PRMT4 from BMS |  |
70 nM (best exemplar) | PRMT4 | (Wan et al., 2009) |
| C21 |  |
1.8 µM | PRMT1 (PRMT6) | (Obianyo et al., 2011) |
| Compound 1 (allosteric) |  |
2.5 µM | PRMT3 | (Jones et al., 2012; Siarheyeva et al., 2012) (Siarheyeva et al., 2012) |
Arginine deiminases
Unlike the removal of lysine methyl marks, there is a scarcity of candidate enzymes with convincing demethylase activity against methylated arginines identified to date, with the exception of JmjD6 (Chang et al., 2007). Consequently, it had been suggested that enzymes of the peptidyl-arginine deiminase (PAD) family, which are able to catalyse the deimination (or citrullination) of arginine side chains into citrulline moieties, could similarly act on methylated arginines, and reverse methylation in the process (Wang et al., 2004). However, such catalysis is now thought to be unlikely under cellular conditions (reviewed by Thompson and Fast, 2006). Wider confirmation of the role of JmjD6 and the identification of additional demethylase enzymes therefore await further research.
Nevertheless, the PAD family remains a subject of interest as potential epigenetic regulators. The PADs include five members (PADs 1–4 and PAD6) with noted differences in function and substrate specificity (reviewed by Jones et al., 2009). PAD4 has been the primary focus with regard to an epigenetic function, because it is the only family member with a clear nuclear localization sequence and it has been reported to citrullinate accessible arginine residues on the tails of various histones (most notably R2, R8, R17 and R26 on H3, and R3 on H4). However, in light of recent data suggesting that PAD2 can also be found in the nucleus (Jang et al., 2011) and can effectively citrullinate histones (Zhang et al., 2012), additional PADs may cause epigenetic modulation. PAD2 represents a potential target for multiple sclerosis based on its CNS expression and ability to citrullinate, and thereby destabilize, myelin basic protein (Oguz et al., 2009). PADs 1 and 3 have roles in skin and hair follicle physiology, respectively, while PAD6 expression is limited to gametes and has not been shown to citrullinate any substrate to date.
Limited evidence for PAD4-mediated citrullination affecting transcription has come from a small number of reports, including effects on ER-responsive genes (Cuthbert et al., 2004; Wang et al., 2004; Zhang et al., 2012) and p53-regulated promoters (Li et al., 2008; 2010b). Interestingly, a reciprocal relationship between histone arginine methylation and citrullination has been demonstrated in a number of these studies [e.g. on p53 target promoters after UV treatment (Li et al., 2008)], suggesting that citrullination may indeed be an indirect barrier to methylation via depletion of naive arginine residues, and that inhibitors of histone citrullination may have widespread transcriptional effects.
Citrullinated histones are also associated with the formation of neutrophil extracellular traps (NETs). These elusive structures (Brinkmann et al., 2004; Yipp et al., 2012) offer innate immunity functions through the trapping and killing of pathogens by extruded filaments containing DNA, histones and potent granule proteins. The initial discovery of citrullinated H3 and H4 epitopes (Neeli et al., 2009; Wang et al., 2009b) followed by the reported lack of NETosis and selective interference with host defence in PAD4-deficient mice (Li et al., 2010a) emphasizes that citrullination by this enzyme is a key feature in NETosis. There is increasing evidence supportive of the rationale that a selective PAD4 inhibitor may be effective in a wide range of diseases characterized by an excessive burden of NETs. These range from thrombosis (Martinod et al., 2012) to systemic lupus erythematosus (Villanueva et al., 2011), ulcerative colitis (Savchenko et al., 2011), small-vessel vasculitis (Kessenbrock et al., 2009) and sepsis (Clark et al., 2007). NETs have also recently been linked to the pathogenesis of rheumatoid arthritis (Khandpur et al., 2012), supporting historical non-epigenetic evidence for PAD4 being important in loss of tolerance to synovial proteins in this disease.
The first notable PAD inhibitors published were peptidomimetics, rationally designed to irreversibly modify a key active site cysteine residue via covalent attachment to a haloacetaminidine moiety (Luo et al., 2006). The best studied exemplar, Cl-amidine, has subsequently been used widely as an in vitro tool. It has also demonstrated impressive efficacy in animal models of arthritis (Willis et al., 2011), colitis (Chumanevich et al., 2011) and lupus (Knight et al., 2013), despite poor pharmacokinetics in vivo and an uncertain PK–PD relationship. Cl-amidine is also a non-selective inhibitor of all PAD enzymes and subsequent efforts have focussed on the development of second-generation inhibitors with increased potency and selectivity for individual PAD enzymes (e.g. see Table 11). Molecules such as o-F-amidine and Thr-Asp-F-amidine (Causey et al., 2011; Jones et al., 2012) demonstrate signs of increased selectivity for PAD4, while PAD3-selective probes have also been described (Knuckley et al., 2010a). Encouraging signs of wider activity include the development of additional screens for PAD inhibitors and the identification of diverging and additional chemotypes (Wang et al., 2012; Bozdag et al., 2013). Ultimately, exploiting the binding determinants between the different PAD enzymes in order to identify and develop truly selective inhibitors for individual enzymes should allow definitive mechanistic understanding and guide optimal therapeutic positioning across a wider range of diseases.
Table 11.
Examples of PAD inhibitors
Bromodomains
Acetylated lysines on histone proteins can be recognized by bromodomains (BRDs), which are small protein interaction modules of approximately 110 amino acids (Tamkun et al., 1992). There are 61 human BRDs found within 42 different proteins (Table 12), with individual proteins containing between one and six BRDs (Figure 2). The three-dimensional structure of more than half of the family of BRD containing proteins (BCPs) has been experimentally determined (Figure 2), demonstrating a conserved hydrophobic pocket that accommodates acetyl-lysine side chains (Jacobson et al., 2000; Nakamura et al., 2007; Filippakopoulos and Knapp, 2012; Filippakopoulos et al., 2012). BRDs are present in diverse nuclear proteins that possess intrinsic chromatin-modifying activity, including KATs (KAT2A, KAT2B, KAT4), KMTs (KMT2A, KMT2H), ATP-dependent chromatin-remodelling proteins (BAZ1B), helicases (SMARCA) and nuclear-scaffolding proteins (PB1) (Muller et al., 2011). In addition, BCPs are often found as components of large protein complexes controlling chromatin architecture and recruit other proteins such as epigenetic writers and readers as well as transcriptional regulatory proteins to chromatin (Dawson et al., 2011). Although the ability of BRDs to bind to acetylated lysine residues within histone proteins is linked to their gene regulatory activity, these domains have also been implicated in binding to non-histone acetylated proteins such as HIV Tat, RelA and p53 (Barlev et al., 2001; Dorr et al., 2002; Huang et al., 2009a).
Table 12.
Bromodomain-containing proteins
| Symbol | Synonyms and other symbols | Uni-ProtKB/Swiss-Prot assession number |
|---|---|---|
| ASH1L | ASH1, ASH1L1, huASH1, KMT2H, KIAA1420 | Q9NR48 |
| ATAD2 | ANCCA, CT137, DKFZp667N1320, MGC29843, MGC5254, PRO2000 | Q6PL18 |
| ATAD2B | KIAA1240 | Q9ULI0 |
| BAZ1A | ACF1, hACF1, WALp1, WCRF180 | Q9NRL2 |
| BAZ1B | WSTF, WBSCR10, WBSCR9 | Q9UIG0 |
| BAZ2A | KIAA0314, TIP5, WALp3 | Q9UIF9 |
| BAZ2B | WALp4, KIAA1476 | Q9UIF8 |
| BPTF | FALZ, FAC1, NURF301 | Q12830 |
| BRD1 | BRPF2, BRL | O95696 |
| BRD2 | KIAA9001, RING3, D6S113E, FSRG1, NAT | P25440 |
| BRD3 | KIAA0043, RING3L, ORFX | Q15059 |
| BRD4 | HUNK1, HUNKI, MCAP, CAP | O60885 |
| BRD7 | BP75, CELTIX1 | Q9NPI1 |
| BRD8 | p120, SMAP, SMAP2 | Q9H0E9 |
| BRD9 | FLJ13441 | Q9H8M2 |
| BRDT | BRD6, CT9 | Q58F21 |
| BRPF1 | BR140, PEREGRIN | P55201 |
| BRPF3 | KIAA1286 | Q9ULD4 |
| BRWD1 | C21orf107, WDR9 | Q9NSI6 |
| BRWD3 | FLJ38568, MRX93 | Q6RI45 |
| CECR2 | KIAA1740 | Q9BXF3 |
| CREBBP | CBP, KAT3A, RTS, RSTS | Q92793 |
| EP300 | KAT3B, p300 | Q09472 |
| KAT2A | GCN5, GCN5L2, HGCN5, PCAF-b | Q92830 |
| KAT2B | PCAF, GCN5, GCN5L, P/CAF | Q92831 |
| PBRM1 | BAF180, PB1 | Q86U86 |
| PHIP | WDR11, BRWD2, DCAF14, FLJ20705, ndrp | Q8WWQ0 |
| SMARCA2 | BAF190B, BRM, hBRM, hSNF2a, SNF2, SNF2LA, Sth1p, SWI2, SNF2L2 | P51531 |
| SMARCA4 | BAF190A, BRG1, FLJ39786, hSNF2b, SNF2B, SNF2L4 | P51532 |
| SP100 | – | P23497 |
| SP110 | IFI41, IFI75 | Q9HB58 |
| SP140 | LYSP100 | Q13342 |
| SP140L | – | Q9H930 |
| TAF1 | DYT3/TAF1, KAT4, NSCL2, TAFII250, BA2R, CCG1, CCGS, TAF2A | P21675 |
| TAF1L | TAFII210 | Q8IZX4 |
| TRIM24 | hTIF1, RNF82, Tif1a, TIF1A, TIF1, RNF82 | O15164 |
| TRIM28 | KAP1, RNF96, TF1B, TIF1B | Q13263 |
| TRIM33 | FLJ11429, KIAA1113, PTC7, RFG7, TF1G, TIF1G, TIF1GAMMA, TIFGAMMA, KIAA1113 | Q9UPN9 |
| TRIM66 | C11orf29, KIAA0298, TIF1D | O15016 |
| ZMYND8 | PRKCBP1, KIAA1125, RACK7 | Q9ULU4 |
| ZMYND11 | BS69 | Q15326 |
Figure 2.
Phylogenetic tree of the human bromodomain family of proteins. The targets for which small molecule inhibitors have been identified are highlighted with asterisks. Yellow hexagons indicate X-ray structures in the public domain.
Recent studies have implicated BCPs in a wide range of human diseases, including cancer, inflammatory diseases, obesity, diabetes, infectious diseases, neurological disorders, and metabolic and cardiovascular indications (Taverna et al., 2007; Prinjha et al., 2012). Evidence for the role of BCPs includes altered expression in disease tissue, chromosomal translocations, amplifications and deletions involving BCP gene loci, genome-wide or focused gene sequence analyses linking SNPs to disease incidence, as well as phenotypes identified using knock-down or knockout studies. As an example, among the multiple BCPs reported to be overexpressed in tumours, which include ASH1L, BPTF, EP300, MLL, SMARCA2, SMARCA4, TRIM24 and TRIM28, ATAD2 has been shown to be up-regulated in various cancer types and to be significantly associated with prostate and endometrial cancer progression (Zou et al., 2009; Raeder et al., 2013), poor prognosis in breast and lung cancer (Caron et al., 2010), and occurrence of metastasis and overall survival in breast cancer (Boussouar et al., 2013). Furthermore, the identification of three sites of polymorphism in BRD2 associated with rheumatoid arthritis and the observation that Brd2-hypomorphic mice are severely obese and have reduced inflammation in fat tissue are examples of links of BCPs to inflammation (Muller et al., 2011).
An understanding of the therapeutic relevance of the regulatory function of the BRD of BCPs is beginning to emerge with the recent development of small molecule BRD inhibitors (Table 13) (Chung, 2012; Hewings et al., 2012). In some cases, these have been used to explore the interactions between BCPs and non-histone proteins. For example, compounds that bind to the BRD of PCAF with selectivity over the structurally related BRDs of CREBBP and TIF1β were identified by NMR-based small molecule screening and shown to disrupt the association of PCAF with HIV Tat-AcK50 in vitro (Zeng et al., 2005). Likewise, ischaemin (Table 13), a selective modulator of the transcriptional co-activator CREBBP, is able to block the interaction of acetylated p53 (p53K382ac) with CREBBP, leading to regulation of tumour suppressor p53-induced transcriptional activity in cells and preventing apoptosis in ischaemic cardiomyocytes (Borah et al., 2011).
Table 13.
Examples of bromodomain inhibitors
| Inhibitor | Structure | Potency | Reported target | Reference |
|---|---|---|---|---|
| Compound 2 |  |
1.6 µM | KAT2B | (Zeng et al., 2005) |
| Ischaemin (MS120) |  |
19 µM | CREBBP | (Borah et al., 2011) |
| I-BET-762 (GSK525762A) |  |
50–60 nM | BRD2, BRD3, BRD4, BRDT | (Nicodeme et al., 2010) |
| I-BET-151 (GSK1210151A) |  |
250–800 nM | BRD2, BRD3, BRD4, BRDT | (Seal et al., 2012) |
| JQ1 |  |
50–90 nM | BRD2, BRD3, BRD4, BRDT | (Filippakopoulos et al., 2010) |
| RVX-208 |  |
40 nM – 3 µM | BRD2, BRD3, BRD4, BRDT | (Khmelnitsky et al., 2013) |
The most advanced targets with respect to the development of BRD inhibitors are the members of the bromodomain and extraterminal (BET) subfamily of BCPs, which include BRD2, BRD3, BRD4 and BRDT (Table 13). Recently, a small number of potent, highly cell-permeable inhibitors with low nanomolar affinity for BET BRDs have been identified; these inhibitors appear highly selective for BET BRDs, but are active against the eight BRDs found in these four proteins due to their high degree of homology (Mirguet et al., 2013). Among the diverse chemotypes reported to date are the first inhibitors disclosed, I-BET762 (GSK525762) and JQ1, both of which originated from chemical starting points found by phenotypic screening assays aimed to identify up-regulators of apolipoprotein A1 (Apo-A1), and I-BET151 and RVX-208 (Table 13).
BET inhibitors have shown promising effects in a variety of preclinical cancer studies. One cancer of particular interest is nuclear protein in testis (NUT) midline carcinoma (NMC), a rare, aggressively lethal tumour type in which chromosomal translocations between BRD4 (and sometimes BRD3) and the NUT protein play a causative role. JQ1 has been found to induce squamous differentiation and growth arrest in patient-derived BRD4-NUT-positive NMC cell lines and to decrease tumour size and improve survival in mouse xenograft models (Filippakopoulos et al., 2010). In addition, BET inhibitors including I-BET762, I-BET151 and JQ1 have been shown to be active against myeloma (Delmore et al., 2011), lymphoma (Emadali et al., 2013), acute lymphoblastic leukaemia (Da Costa et al., 2013), prostatic cancer (Gao et al., 2013), neuroblastoma (Puissant et al., 2013; Wyce et al., 2013) and glioblastoma (Cheng et al., 2013), in vitro and in vivo, while I-BET151 has been shown to have considerable preclinical activity against acute leukaemias, including MLL-fusion protein-driven leukaemia (Dawson et al., 2011), and also against JAK2-driven myeloproliferative neoplasms (Wyspianska et al., 2013). Similarly, I-BET726 was shown to induce cytotoxicity in mouse xenograft models of human neuroblastoma (Wyce et al., 2013), and inhibition of BET has been shown to impair melanoma cell proliferation in vitro and tumour growth and metastatic behaviour in vivo (Segura et al., 2013).
Based on these promising preclinical results, BET inhibitors are now entering clinical trials (Table 14). I-BET762 (Nicodeme et al., 2010; Mirguet et al., 2013), a benzodiazepine derivative developed by GlaxoSmithKline (GSK), was recently progressed into a phase I clinical trial for treatment of NMC, as well as other cancers (Mirguet et al., 2013). In addition, CPI-0610 (Constellation Pharmaceuticals) and OTX-015 (OncoEthix) are also examples of BET inhibitors currently in phase I clinical trials for the treatment of various cancer types.
Table 14.
Clinical studies of bromodomain inhibitors
| Primary drugs | Sponsor | Trial phase | Disease type(s) | Trial ID |
|---|---|---|---|---|
| I-BET-762 | GSK | I | NMC Leukaemias, lymphomas Multiple myeloma Myeloproliferative neoplasms | NCT01587703 NCT01943851 |
| RVX-208 | Resverlogix | I/II | Dyslipidemia Atherosclerosis Acute coronary syndrome Cardiovascular disease | NCT00768274 NCT01067820 NCT01058018 NCT01423188 NCT01863225 |
| II | Type 2 diabetes | NCT01728467 | ||
| II | Alzheimer's disease | (Study planned) http://www.resverlogix.com/programs/epigenetics/neurodegenerative-diseases | ||
| CPI-0610 | Constellation Pharmaceuticals | I | Lymphomas | NCT01949883 |
| I | Leukaemias Multiple myeloma Myelodysplastic syndrome | (Study planned) http://www.constellationpharma.com/2012/09/constellation-pharmaceuticals-and-the-leukemia-lymphoma-society-partner-to-develop-novel-bet-inhibitor-for-the-treatment-of-hematologic-malignancies/ | ||
| OTX-015 | OncoEthix/ Mitsubishi Tanabe Pharma | I | Leukaemias, lymphomas Multiple myeloma Unspecified haematological cancer | NCT01713582 |
There is also great interest in the potential application of BET inhibitors in other therapeutic areas. In particular, there is considerable evidence that BET inhibitors may have utility in the treatment of autoimmune/inflammatory disease. In this regard, I-BET762 was shown to inhibit the expression of inflammatory cytokines and chemokines in activated mouse macrophages and to confer protection against LPS-induced endotoxic shock and bacteria-induced sepsis in mice (Nicodeme et al., 2010). These anti-inflammatory effects were replicated by I-BET151, which reduced pro-inflammatory cytokine production by activated human peripheral blood mononuclear cells, and was effective at suppressing LPS-induced inflammation and sepsis in mice (Seal et al., 2012), and also recently by JQ1 (Belkina et al., 2013). Moreover, I-BET762 inhibited the ability of antigen-specific T-cells, differentiated under Th1 conditions in vitro, to induce pathogenesis in an adoptive transfer model of experimental autoimmune encephalomyelitis (EAE; Bandukwala et al., 2012), and JQ1 was recently shown to suppress Th17 differentiation in vivo and to be protective in mouse models of autoimmunity (collagen-induced arthritis and EAE) (Mele et al., 2013).
One of the most clinically advanced but significantly less potent BET BRD inhibitors is RVX-208 (RVX-000222) (Picaud et al., 2013), which is currently being developed by Resverlogix Corp for the treatment of atherosclerosis and coronary artery disease based on its capacity to increase the levels of Apo-A1 and hence increase high-density lipoprotein cholesterol (McNeill, 2010) (Table 14). Toxicity and tolerability studies in animals and phase I/II clinical trials have indicated that RVX-208 is safe and well tolerated in multiple dosing regimens. It will be of great interest to see whether more potent BET inhibitors are similarly well tolerated in phase I trials mentioned above to gain an understanding of the therapeutic index of these inhibitors. RVX-208 is currently in phase 2 clinical trials for the treatment of atherosclerosis (Nicholls et al., 2011). In addition, a phase I trial indicated that RVX-208 may have potential for the removal of β-amyloid plaques in Alzheimer's disease and this will be further assessed in an ongoing phase I/II clinical trial.
Like HDAC inhibitors, BET inhibitors have been shown to reactivate HIV from latency in cell lines and primary T-cell models, indicating their possible use in clearance and cure of the latent viral pool, as described above (Zhu et al., 2012; Boehm et al., 2013a,b; Li et al., 2013). Their potential utility as therapeutics for heart failure has also been suggested recently based on the ability of JQ1 to block cardiomyocyte hypertrophy in vitro, and to prevent left ventricular hypertrophy and improve cardiac function in adult mice subjected to transverse aortic constriction (Spiltoir et al., 2013). Finally, the efficacy of BET inhibitors in blocking the pro-fibrotic responses of idiopathic pulmonary fibrosis (IPF) lung fibroblasts and attenuating bleomycin-induced lung fibrosis in mice provides a rationale to target the BET proteins for the treatment of IPF (Tang et al., 2013b).
Concluding remarks
Although the basic scientific understanding of epigenetic regulatory mechanisms is at an early stage, great progress has already been made in taking drugs targeting these pathways into the clinic. The rapid pace of these developments has been driven by the recognition that dysregulation of epigenetic processes is apparent in diverse disease states, combined with the finding that many of the proteins that generate, remove and recognize histone modifications are tractable to small molecule drug development. In turn, the tractability of epigenetic targets has led to the generation of chemical probes that are being used to accelerate investigation into the biological function of these proteins.
As work in this young field continues, it will be of great interest to understand the full potential of this target class for the treatment of human disease. There will be many important questions relating to drug development for epigenetic pathways. For example, how many proteins within the multiple target classes of writers, erasers and readers will prove tractable to the generation of potent and selective small molecule modulators? Is there redundancy among these targets, and what role will polypharmacology play? What approaches can be taken to modulate epigenetic states in disease tissue while minimizing effects on normal cellular homeostasis? As well as acutely modifying gene expression, will it be possible to reset aberrant epigenetic states to normal, allowing for short-term treatments to induce remission or even ‘cure’ disease? Answering these questions will be aided by the continuing development of pharmacological tools together with increasingly sophisticated molecular approaches for elucidating the mechanisms that regulate chromatin structure and gene expression.
Author contributions
All authors contributed to writing of sections of the manuscript.
Conflict of interest
All authors are employees and shareholders of GlaxoSmithKline, which is researching and developing epigenetic inhibitors.
Glossary
- α-KG
α-ketoglutarate
- ADMA
asymmetrical- dimethylarginine
- Apo-A1
apolipoprotein A1
- BCP
bromodomain-containing protein
- BET
bromodomain and extraterminal
- BRD
bromodomain
- DNMT
DNA-methyltransferase
- EAE
experimental autoimmune encephalomyelitis
- FAD
flavin adenine dinucleotide
- HDAC
histone deacetylase
- IPF
idiopathic pulmonary fibrosis
- Jmj
jumonji C-domain
- KAT
lysine acetyltransferase
- KDAC
lysine deacetylase
- KDM
lysine-specific demethylase
- KMT
lysine methyltransferase
- MMA
mono-methylated arginine
- NET
neutrophil extracellular trap
- NMC
NUT midline carcinoma
- NOG
N-oxalylglycine
- NUT
nuclear protein in testis
- PAD
peptidyl-arginine deiminase
- PCPA
trans-2-phenylcyclopropylamine
- PRMT
arginine methyltransferase
- SAHA
suberoylanilide hydroxamic acid
- SAM
S-adenosyl methionine
- SDMA
disymmetrical-dimethylarginine
- SIRT
sirtuin
- SNP
single nucleotide polymorphism
- TET
ten-eleven translocation
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