Identification of Novel Disruptor of Telomeric Silencing 1-like (DOT1L

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Identification of Novel Disruptor of Telomeric Silencing 1-Like (DOT1L) Inhibitors through Structure-Based Virtual Screening and Biological Assays Shijie Chen, Linjuan Li, Yantao Chen, Junchi Hu, Jingqiu Liu, Yu-Chih Liu, Rongfeng Liu, yuanyuan Zhang, Fanwang Meng, Kongkai Zhu, Junyan Lu, Mingyue Zheng, Kaixian Chen, Jin Zhang, Hualiang Jiang, Zhiyi Yao, and Cheng Luo J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.5b00738 • Publication Date (Web): 25 Feb 2016 Downloaded from http://pubs.acs.org on February 29, 2016

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Journal of Chemical Information and Modeling

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Identification of Novel Disruptor of Telomeric Silencing 1-Like (DOT1L) Inhibitors through Structure-Based Virtual Screening and Biological Assays Shijie Chen§, #, ¶, Linjuan Li§, #, ¶, Yantao Chen#, ¶, Junchi Hu#, Jingqiu Liu#, Yu-Chih Liu, Rongfeng Liu,Yuanyuan Zhang#, Fanwang Meng#, Kongkai Zhu#, Junyan Lu#, Mingyue Zheng#, Kaixian Chen#, §, Jin Zhang±, Hualiang Jiang#, §*, Zhiyi Yao^* and Cheng Luo#,*

§

School of Life Science and Technology, Shanghai Tech University, Shanghai 200031,

China #

Drug Discovery and Design Center, State Key Laboratory of Drug Research,

Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zu Chongzhi Road, Shanghai 201203, China 

In Vitro Biology, Shanghai ChemPartner LifeScience Co., Ltd., #5 Building,998

Halei Road, Shanghai 201203, China ±

Department of Urology, Renji Hospital , School of Medicine ，Shanghai Jiao Tong

University, Shanghai, 200127, China ^

College of Chemical and Environmental Engineering, Shanghai Institute of

Technology, Shanghai, 210032, China

¶

These authors contributed equally to this work.

*Correspondence:

Hualiang

Jiang

([email protected]),

([email protected]) and Cheng Luo ([email protected])

ACS Paragon Plus Environment

Zhiyi

Yao

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Abstract Histone methyltransferases are involved in many important biological processes, and abnormalities in these enzymes are associated with tumorigenesis and progression. Disruptor of telomeric silencing 1-like (DOT1L), a key hub in histone lysine methyltransferases, has been reported to play an important role in the processes of mixed lineage leukemia (MLL)-rearranged leukemias and validated to be a potential therapeutic target. In this study, we identified a novel DOT1L inhibitor, DC_L115 (CAS NO. 1163729-79-0), by combining structure-based virtual screening with biochemical analyses. This potent inhibitor DC_L115 show high inhibitory activity towards DOT1L (IC50=1.5 µM ). Through a process of surface plasmon resonance (SPR)-based binding assays, DC_L115 was founded to bond to DOT1L with binding affinities of 0.6 µM in vitro. Moreover, this compound selectively inhibited MLL-rearranged cell proliferation with an IC50 value of 37.1 µM. We further predicted the binding modes of DC_L115 through molecular docking analysis and found that the inhibitor competitively occupied the binding site of SAM (S-adenosylmethionine). Overall, this study demonstrated the development of potent DOT1L inhibitors with novel scaffolds.



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Introduction Post-transcriptional modifications of histone including methylation, acetylation, ubiquitination, phosphorylation, ribosylation,1 and SUMOylation2 are important parts of epigenetic regulation. Among them, histone methylation is a dynamic and invertible modification3, 4 that plays crucial roles in numerous biological processes which include the transcription and translation of genetic information, cell proliferation, cell differentiation, signal transduction, and embryonic development.5 Histone methylation occurs in the nitrogen atom of the amino or guanidino of lysine or arginine mainly in the tails of histone H3 and histone H45, 6 respectively. Among them, histone lysine methyltransferases (HKMTs) mainly target lysine for mono-, di-, or tri-methylation7, 8 and can be categorized into two subclasses based on whether a SET domain is contained in the catalytic domain. To date, disruptor of telomeric silencing 1-like (DOT1L) is the only HKMT that has been confirmed not to contain an SET domain,9 which catalyzes the methylation of nucleosome histone H3 lysine 79 (H3K79).10-12 Additionally, aberrant activities of DOT1L are proven to be closely associated with many diseases, such as mixed lineage leukemia (MLL)-rearranged leukemia,13,

14

which is an aggressive disease with undesirable clinical outcomes

partially because of the lack of efficiency of current accessible therapies.15 MLL accounts for >70% of infant leukemias,16 for approximately 5% of acute lymphoblastic leukemias, and for approximately 5%–10% of acute myeloid leukemias.17 MLL rearrangements result in oncogenic fusion proteins formed by AF9, AF10, ENL, and DOT1L18-21 and then result in hypermethylation at H3K79, leading


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to the aberrant expression of a characteristic set of genes, including HOXA9,22 followed by leukemogenesis.23 DOT1L plays an important role in the occurrence and maintenance processes of MLL-rearranged leukemias; thus, DOT1L inhibitors are promising therapeutic tools to treat MLL-rearranged leukemias.21 The first selective inhibitor (EPZ004777) of DOT1L was discovered by Epizyme International Company.24 Shortly thereafter, three research teams including the Epizyme International Company, the Song Laboratory, and the Structural Genomics Consortium have published several dozens of compounds with activity against DOT1L.25-30 Moreover, the inhibitor EPZ-5676 has already entered clinical investigation.31 According to the structure of compounds, these inhibitors can be divided into four categories: (i). SAH(S-adenosylhomocysteine)-like DOT1L inhibitors,

(ii).

benzimidazole/urea-containing

DOT1L

inhibitors,

(iii).

carbamate-containing DOT1L inhibitors, and (iv). mechanism-based DOT1L inhibitors.25 Two representative inhibitors for each of the category are shown in the Supporting Information Figure S1. These compounds have remarkable activities against the enzyme, but they all have scaffolds similar to SAM/SAH containing an adenosine or a deazaadenosine.25 The ribose fragment can be rapidly degraded by relative enzymes when entering organisms, which leads to poor pharmacokinetics properties, low oral bioavailability, hindered oral administration.32, 33 In addition, no compound has already passed clinical development and entered the market up to now.33 Therefore, novel selective DOT1L inhibitors with new scaffolds different from SAM/SAH still need to be developed.



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Virtual screening is becoming increasingly popular and has been successfully used in several lead-compound-discovery projects.34-38 Thus, considering the low cost and convenience of the approach; we detected DOT1L inhibitors by virtual screening in the

present

work.

An

integrated

structure-based

method

incorporating

pharmacophore-based with docking-based virtual screening was utilized to identify novel DOT1L inhibitors from the SPECS database39 (http://www.specs.net). After performing cluster analysis on highly ranked candidates derived from the virtual-screening results, 117 compounds (Supporting Information Table S1) were selected and purchased to test their bioactivity against DOT1L. Finally, DC_L115 (IC50 = 1.5 µM) was identified as a potent DOT1L inhibitor with higher inhibitory activity than any other DOT1L inhibitor possessing new scaffolds different from SAMs based on the outcomes of credible biochemical experiments. Further experimental studies demonstrated that the compound bound to DOT1L, with binding affinities of 0.6 µM in vitro, and selectively inhibited MLL-rearranged cell proliferation. All these results suggested that DC_L115 may further be developed as a lead compound and participate in exploring the diversiforms and intricate the biological functions of DOT1L as a chemical probe.

Methods Virtual-Screening Protocol. Ligand Preparation. The ligand database, a multiconformer 3D database derived


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from 182014 distinct molecules, was obtained from the Specs database39 (http://www.specs.net) with approximately 200000 molecules treated by the same methods as those of Meng, F. et al..34 Apart from the ligand database, two test-set databases and a training set used for virtual screening were also established. The first test-set database comprised 67 DOT1L inhibitors published by researchers and decoys containing 3600 molecules built by DUD•E40, 41 referring to the structures of these inhibitors. The structures and activities of the used 67 DOT1L inhibitors are shown in the Supporting Information Table S2. LigPrep42 was then used to generate diverse conformational isomers, tautomers, and protonated states at pH 7.0 ± 2.0 with Epik43 of these molecules. The training-set database comprised 14 inhibitors extracted from the 67 with relatively better bioactivities25-30 (Supporting Information Figure S2). The second test-set database containing the 14 selected DOT1L inhibitors and corresponding decoys was built in the same way as the first one by applying LigPrep42 and DUD•E.40, 41

Protein Preparation.

Taking the integrality and resolution of the structure into

consideration, the crystal structure of DOT1L with SAM obtained from the Protein Data Bank (PDB ID 3QOW) was selected for subsequent virtual screening. The solvent molecules were initially removed, and then the Protein Preparation Wizard Workflow provided in the Maestro44 graphical user interface was used to prepare the remaining complex structure. The pH was set to 7.0 ± 2.0, the same pH at which the ligand was prepared, and exhaustive sampling was performed during hydrogen-bond assignment. For the other involved parameters, the default value was assigned.



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Pharmacophore

Generation

and

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Pharmacophore-Based

Screening.

Receptor-ligand-based and ligand-based-pharmacophore models were generated and evaluated using Accelrys Discovery Studio 3.0.45 For the former, the structure of DOT1L in complex with SAM (PDB ID 3QOW) and that of the protein in complex with EPZ-5676 (PDB ID 4HRA) were separately used to gain 10 different models. Default values were assigned to all parameters, except for the number of pharmacophore features contained within a model, which was set as between 4 to 10. The accuracy of these pharmacophore models were evaluated by screening the first test-set database prepared before, and the enrichment factor (EF)46 was calculated according to the screening results (Supporting Information Table S3). For the latter, the training-set database was utilized to generate the ligand-based pharmacophore model, and the second test-set database was screened using 10 models obtained to gain their EF46 and thus validate their accuracy (Supporting Information Table S3). During

the

process,

features

including

HB_DONOR,

HB_ACCEPTOR,

HYDROPHOBIC, POS_IONIZABLE, NEG_IONIZABLE, and RING_AROMATIC were selected when performing Feature Mapping in Accelrys Discovery Studio 3.0,45 and the default values were assigned to the remaining parameters. Four rational pharmacophore models were selected one by one to screen the ligand database prepared at the beginning using Search 3D Database within Accelrys Discovery Studio 3.045 (the Limit Hits was set at All; others were set at default values). Afterwards, the Lipinski’s rule of five47 and pan assay interference compounds48, 49 were checked again with Pipeline Pilot.50 Then, the remaining molecules were


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prepared by LigPrep42 for docking-based virtual screening, with the limit that at most three stereoisomers were generated for each ligand. Docking-Based Screening and Cluster Analysis. Glide 5.551 was used to perform the screening. The applicability of this docking software for the virtual screening of DOT1L inhibitors was first validated by evaluating its EF46 (top 20%) with values of 3.288258 (Glide SP mode52) and 3.057535 (Glide XP mode53), both >2.5 (half of the maximum value of 5). Then, the endogenous ligand was redocked into the complex structure (PDB ID 3QOW) with an RMSD value of 0.2451 (Glide SP mode52) and 0.4705 (Glide XP mode53), respectively, suggesting that this docking program was able to reproduce the ligand’s active conformation (Supporting Information Figure S3). A receptor grid box was defined as a space region of 20 Å × 20 Å × 20 Å centered at the endogenous ligand SAM. In addition, two hydrogen bond constraints were introduced into Asp222 and Thr139 during grid-box generation and docking-based virtual screening because of their contribution to the selectivity between DOT1L and SAM.54 The compounds obtained by pharmacophore-based virtual screening was first docked into the SAM binding site in Glide SP mode.52 The origin input poses were not that abundant, and the poses were all redocked into the pocket in Glide XP mode,53 except those with Glide scores greater than zero. The top-ranked 943 compounds were subjected to cluster analysis by Pipeline Pilot50 with the number of clusters defined. The number of clusters was initially set to 110. Because some categories of the clustering results included dozens of compounds with similar structures, we decided to select a little more compounds from these clusters



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considering a possibly larger probability for discovering hit compounds. For ensuring the diversity of scaffolds, a second round cluster analysis was performed to these categories with the cluster number defined according to the amount of compounds included, respectively. After checking these compounds one by one, 117 molecules were selected based on the following principles derived from the interactions between DOT1L and SAM: (i). the more hydrogen bonds the compound can form with DOT1L, especially with Asp222 and Thr139 (which may contribute to its selectivity), the better the activity of the molecule; (ii). compounds that can form π-π stacking interactions with Phe223 may be good candidates with high potency; (iii). molecules should occupy SAM binding site rationally; (iv). compounds with low molecular weight are preferred; and (v). among a cluster of similar compounds, at least one should be selected to ensure the diversity of candidates’ structure. The putative binding mode of DC_L115 was obtained with Glide 5.551 in XP mode.53

Binding Energy Calculation In order to generate more conformations for ligands used for binding energy calculation, Glide 5.551 was used to perform the docking process (Glide SP mode52). The docking results are following to be the input files of Prime MM-GBSA (molecular mechanics/Poisson–Boltzman surface area methods) ,55 the procedure used to calculate the binding energy of ligands with the macromolecule. In the calculation, the protein flexibility was set to 12 Å.

Protein Expression and Purification.


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Human DOT1L sequence (residues 1–416) covering the catalytic domain was cloned into a modified pET28a vector, which encoded a SUMO tag after the N-terminal His6 tag. DOT1L protein was overexpressed in E. coli BL21 (DE3) cells at 16 °C. The protein was first purified by nickel affinity chromatography (HisTrap FF, GE Healthcare), and then the His6-SUMO tag was removed by ULP1 at 4 °C overnight. Afterwards, DOT1L protein was further purified through cation exchange (HiTrap SP, GE Healthcare), followed by gel-filtration chromatography on a Superdex 75 10/300 column (GE Healthcare). The purified DOT1L protein was concentrated in a buffer containing 20 mM Tris-HCl (pH 8.0), 200 mM NaCl, 1 mM DTT, and 5% glycerol.

DOT1L Inhibition Assays. AphaLISA DOT1L Histone H3 Lysine-N-methyltransferase Assay. All 117 compounds were first screened using an AphaLISA DOT1L Histone H3 Lysine-N-methyltransferase Assay (PerkinElmer). About 80 nM purified DOT1L was incubated with 50 µM of the different compounds for 10 min at room temperature (RT) in the assay buffer (50 mM Tris-HCl pH 8.0, 150 mM NaCl, 3 mM MgCl2, and 0.1% BSA). Then, 1 µM S-adenosylmethionine (AdoMet) and 0.25 ng oligonucleosomes were added to the assay plate (White opaque OptiPlate™-384, PerkinElmer), which was incubated at RT for 1 h. Next, high-salt buffer (50 mM Tris-HCl pH 7.4, 1 M NaCl, 0.1% Tween-20, and 0.3% poly-L-lysine) was added, and the mixture was incubated for 15 min at RT to stop DOT1L enzymatic reaction. Anti-Histone H3 acceptor beads/biotinylated anti-H3K79me2 antibody mixture was added to the



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reaction systems, which were incubated for 60 min at RT. Finally, streptavidin donor beads were added, and the mixture was incubated in subdued light for 30 min at RT. EPZ00477724 was used as a positive control. The signal was read in Alpha mode using EnVision Readers (PerkinElmer). Radioactive Methylation Assay. DOT1L radioactive methylation inhibition assays were performed in 25 µL reactions containing adenosyl-L-methionine S-[methyl-3H] (3H-SAM, PerkinElmer), oligonucleosome (Active Motif), and DOT1L in modified Tris buffer. The proteins were preincubated with compounds for 15 min at RT, and then the substrate and [3H]-SAM were added to the assay plate to start reaction. After 120 min of incubating at RT, the reaction systems were stopped by adding cold SAM and were transferred to a MultiScreen HTS Filter Plate (Millipore). After washing three times with ddH2O in a vacuum, radioactivity was determined by liquid scintillation counting (MicroBeta, PerkinElmer). IC50 values were derived by fitting the data for the inhibition percentage to a dose-response curve by nonlinear regression in GraphPad Prism 5.0.

Surface Plasmon Resonance (SPR)-Based Binding Assays. SPR binding assays were performed on a Biacore T200 instrument (GE Healthcare) at 25 °C as previously described.38 By conducting a standard amine-coupling procedure, DOT1L protein was covalently immobilized onto a CM5 chip in 10 mM sodium acetate (pH 5.0). The compound was serially diluted with HBS buffer (10 mM HEPES (pH 7.4), 150 mM NaCl, 3 mM EDTA, and 0.1% (v/v) DMSO) and injected


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at a flow rate of 30 µL/min for 150 s to contact DOT1L protein immobilized on the chip, followed by dissociation from the chip for 500 s. The equilibrium dissociation constant (KD) values of the tested compound were determined with Biacore T200 evaluation software (GE Healthcare).

Cell-Viability Analysis. All cell lines were obtained from the American Type Culture Collection. Human leukemia cell line MV4-11 and human pancreatic adenocarcinoma cell line AsPC-1 were cultured in RPMI 1640 medium (Life Technologies) supplemented with 10% fetal bovine serum and 1× Pen/Strep (Life Technologies), whereas the other five cell lines were cultured in DMEM medium (Life Technologies) supplemented with 10% fetal bovine serum and 1× Pen/Strep (Life Technologies). The cells were cultured in a humidified incubator set to 37 °C and 5% CO2. For cell-proliferation assay, cells were treated with compounds of different concentrations. Cell viabilities were measured by the Alamar Blue assay,56 and fluorescence was measured at an excitation wavelength of 544 nm and wavelength of 590 nm. Percentage proliferation was calculated by normalizing the fluorescence to that of the control cells.

Results and Discussion Structure-Based Virtual Screening. In this study, structure-based virtual screening methods combining pharmacophore- and docking-based virtual screening processes were used to identify novel DOT1L inhibitors with scaffold distinct from its cofactor SAM, and the flow chart is shown in Figure 1A. The compound library obtained from



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the SPECS database (http://www.specs.net) containing more than 200 000 molecules was handled with the same strategy used by Meng, F. et al34 to yield the multiconformer 3D database with 182 014 compounds. First, a pharmacophore-based in silico screening process was performed. Four different pharmacophore models (pharmacophore model 01-04; Supporting Information Figure S4) were constructed using Accelrys Discovery Studio 3.045 from the structure of DOT1L in complex with its endogenous molecule SAM (pharmacophore model 01), the structure of DOT1L in complex with EPZ-567631 (pharmacophore model 02 and pharmacophore model 03; the most effective inhibitor reported up to now), and the mutual features of 14 available DOT1L inhibitors with different bioactivities25-30 (pharmacophore model 04). After screening, 15, 1347, 810, and 4348 molecules were obtained from the four models. After filtering out the duplicated ones, as well as those that did not match the Lipinski’s rule of five47 and pan assay interference compounds48, 49 by using Pipeline Pilot,50 the remaining 4150 molecules were subsequently docked into the SAM binding site with Glide 5.5.51 According to the docking scores, the top-ranked 943 compounds were clustered by Pipeline Pilot.50

Finally, 117 compounds carrying

diverse scaffolds were selected and purchased from SPECS Corp. (The Netherlands) for further biochemical validation. DOT1L Enzymatic Assays. All of the selected 117 candidate molecules were tested for DOT1L inhibition to determine their biochemical activities. First, we used AlphaLISA DOT1L histone H3 lysine-N-methyltransferase assay to determine the inhibition activities of the compounds at 50 µM. Among them, we chose 10


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compounds for their ability to inhibit DOT1L activity by >50% (Figure 1B). To further validate the 10 compounds’ activities, we measured the methyltransferase activity of DOT1L at 100 µM in these compounds using H-3-labeled radioactive methylation assay. As shown in Figure 2A, SAH was used as a positive control in the assay, and then three of the candidate compounds were selected for their ability to inhibit DOT1L activity by >50%. Among these three compounds, DC_L115 (IC50 = 1.5 µM) showed the highest inhibitory activity in the radioactive methylation assay (Figure 2D). As shown in Figures 2B and 2C, the other two compounds DC_L94 (IC50 > 200 µM) and DC_L107 (IC50 = 29.7 µM) displayed much lower activity than DC_L115 against DOT1L. Given the low water solubility of DC_L94, we did not obtain an accurate inhibition ratio of this compound, especially at higher concentrations (Figure 2B). All these results suggested that DC_L115 could be characterized as a structurally novel DOT1L inhibitor with remarkable potency against DOT1L. SPR-Based Binding Assay. To more precisely validate the identity of DC_L115, we used SPR-based binding assay to determine the direct interactions between DOT1L and DC_L115. As shown in Figure 3A, the interactions were strong and dose dependent, suggesting that DC_L115 can bind to DOT1L and then inhibit DOT1L activity in vitro. KD between DC_L115 and DOT1L was 0.60 µM, which was approximate with the DOT1L-inhibition potency level. Binding-Mode Analysis. We further calculated the binding energy of three



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compounds with over 50% of inhibitory activity derived from radioactive methylation assay using Prime MM-GBSA55 (Supporting Information Table S4). DC_L115 bond to the SAM binding pocket of DOT1L with the lowest binding energy (-10.747 kcal/mol)，which had the best inhibitory activity against DOT1L, while DC_L107 (-16.972 kcal/mol) with a higher value and DC_L94 (-35.172kcal/mol) with the highest binding energy. The ranking trend of calculated binding energy is in accordance with that of activity, which reasoned our experimental data. To probe the molecular basis of the inhibitory activity and selectivity of DC_L115 toward DOT1L, a putative binding mode was generated by molecular docking with Glide51 in XP mode.53 The predicted binding pose of DC_L115 in the SAM binding site of DOT1L (PDB ID 3QOW) is shown in Figure 3B. In this model, the pyrimidine ring moiety of DC_L115 forms π-π stacking interactions with residue Phe223, similar to that of SAM (Supporting Information Figure S5). Some polar interactions also occurred between DC_L115 and DOT1L, though less than that between SAM and DOT1L (Supporting Information Figure S5). Among these contacts, two hydrogen bonds that provided selectivity to DOT1L25,

54

was formed by the NH2 and NH groups of

DC_L115 with the carbonyl oxygen of residue Asp222. A polar interaction also occurred between the nitrogen in the pyrimidine ring moiety and the NH group of residue Phe223. Another hydrogen bond further formed between the NH2 group of the quinoline amine moiety and the carbonyl oxygen of Asn241 (Figure 3B). The hydrogen bond lengths of Asp222, Phe223, and Asn241 were 1.8, 2.2, 2.3, and 2.7 Å, respectively, suggesting that these polar interactions substantially contributed to


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DC_L115 activity. However, we found no polar interaction between the DC_L115 and residue Thr139, which was involved in the selectivity of SAM to DOT1L.54 In addition to π-π stacking interactions and hydrogen bonds, there are also some hydrophobic interactions between DOT1L and DC_L115 and SAM. Although the number of non-ligand residues involved is similar, some differences exist between residues involved for DC_L115 and those involved for SAM (Supporting Information Figure S5). For instance, DC_L115 established hydrophobic interactions with Val185, Glu134, Leu224, Val249 and Gly163 which not been formed between SAM and DOT1L. Especially, SAM established a hydrogen bond with Gly163 which formed hydrophobic interaction with DC_L115. Considering all the given information and our experimental data, we deduced that DC_L115 could efficiently bind the SAM binding site of DOT1L and supersede the cofactor SAM with moderate selectivity. The pose shown in Figure 3C suggested that DC_L115 well fitted the SAM binding site of DOT1L. Cell Activity. Based on the above results, DC_L115 showed potential DOT1L inhibitory activity in vitro, so we subsequently determined whether this compound can affect cancer-cell proliferation. We tested DC_L115 in human leukemia cells (MV4-11),

human

normal-embryonic-lung

normal-lung fibroblast

fibroblast cells

cells (MRC-5),

(IMR-90), and

human human

pancreatic-adenocarcinoma cells (Capan-1, AsPC-1, and Panc-1). We used Alamar Blue assays to determine the compound’s effects on cell viability. Treatment of MLL-AF4 expressing acute leukemia cell lines MV4-11 with DC_L115 led to a



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dose-dependent reduction in viable cells, with an IC50 value of 37.1 µM (Figure 4A). DC_L115 also showed approximately no inhibitory activities against normal cells (Figures 4B and 4C) and solid tumor cells (Figure S6), which demonstrated that DC_L115 could selectively inhibit the proliferation of MV4-11 cells.

Conclusion The aberrant methylation of H3K79 by DOT1L is an important step in the development and maintenance of MLL-rearranged leukaemia. EPZ004777 and EPZ-5676 are reportedly the potent and selective inhibitors of DOT1L. However, these inhibitors have poor pharmacokinetics properties and low oral bioavailability. In this study, by combining structure-based virtual screening and biochemical assays, we have identified DC_107 and DC_L115 as novel inhibitors of DOT1L, with IC50 values of 29.7 and 1.5 µM, respectively. Their relative strength of inhibitory activity are consistent with that of binding energy of them (DC_L115, DC_L107 and DC_L94). A SPR-based binding assay precisely validated the most potent compound DC_L115 by determining its interaction with DOT1L. KD between DC_L115 and DOT1L was 0.60 µM, which verified the inhibitory activity of DC_L115 against DOT1L in vitro. The predicted binding-mode prediction also revealed that DC_L115 could efficiently bind in the SAM binding site of DOT1L, though there are some differences between the interactions involved in DC_L115 with DOT1L and that involved in SAM with DOT1L which mentioned before. Furthermore, DC_L115 could selectively block the proliferation of MV4-11 cells with an IC50 value of 37.1


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µM. This study demonstrated an efficient integrated structure-based method incorporating a pharmacophore-based with a docking-based virtual-screening procedure that can be used to identify novel DOT1L inhibitors. The results may provide meaningful clues for the further development of DOT1L inhibitors with novel scaffolds to treat MLL-rearranged leukemia.

ASSOCIATED CONTENT Supporting Information The Supporting Information section contains the following: The 2D structures of all the 117 compounds submitted to biological testing; the structures and activities of the 67 DOT1L inhibitors used to build the first test-set database; the structures and activities of representative DOT1L inhibitors. 14 published DOT1L inhibitors that yielded the ligand-based pharmacophore model; the redocking validation results of SAM; pharmacophore models utilized in the pharmacophore-based virtual screening; enrichment factors of the evaluation of pharmacophore applicability; binding energy for compound DC_L94, DC_L107 and DC_L115; key interactions between DOT1L and DC_L115 or SAM at the SAM binding pocket; and effects of DC_L115 on the proliferation of solid tumor cells. This material is available free of charge via the Internet at http://pubs.acs.org. ⊥Author Contributions



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Shijie Chen, Linjuan Li, Yantao Chen contributed equally to this work. The authors declare no competing financial interests. Acknowledgment This work was supported by the National Basic Research Program (2015CB910304), Hi-Tech Research and Development Program of China (2014AA01A302), the National Natural Science Foundation of China (21210003, 81230076，81430084, 81202398 and 91229204) and the National Science and Technology Major Project “Key New Drug Creation and Manufacturing Program” (2013ZX09507-004, 2013ZX09507001 and 2014ZX09507002-005-012).

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Figure legends Figure 1. Virtual-screening procedures and DOT1L-activity assays in vitro. (A) Flow chart of the integrated virtual screening for DOT1L inhibitors. A structure-based strategy combining docking- and pharmacophore-based virtual screening. (B) Inhibitory activities of the 117 compounds at 50 µM. EPZ004777 was used as a positive control (red column); among them, 10 compounds (blue columns) inhibited DOT1L activity by >50% in the AlphaLISA assay. Figure 2. Radioactive methylation assays for DOT1L. (A) Ten compounds (blue columns in Figure 1B) were retested at 100 µM using a radioactive methylation assay; the red column denotes the reference compound SAH; 3 of the 10 compounds showed >50% inhibition of DOT1L activity (blue columns). (B) Structure and inhibitory activity of DC_L94 against DOT1L. (C) Structure and inhibitory activity of DC_L107 against DOT1L. (D) Structure and inhibitory activity of DC_L115 against DOT1L. Figure 3. Binding assays between DOT1L and DC_L115. (A) SPR assay of the binding between DOT1L and DC_L115; the concentrations of DC_L115 injected over the CM5 chip are indicated; SPR curves for DC_L115 binding with DOT1L are shown; KD was 0.60 µM for DC_L115 binding with DOT1L. (B, C) Putative binding mode of DC_L115 in the DOT1L structure (PDB ID: 3QOW). (B) A close-up view of the key interactions involved in stabilizing DC_L115 at the SAM binding pocket; DC_L115 is shown as cyan sticks, and surrounding key residues are shown as yellow



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sticks and labeled; the DOT1L structure is depicted as wheat cartoons; hydrogen bonds are depicted as dotted red lines, and Phe223 involved in the π-π stacking interactions formed between DC_L115 and DOT1L is also labeled out. (C) The SAM binding site of DOT1L occupied by DC_L115 aligned with SAM; DC_L115 is depicted as cyan sticks while SAM is depicted as hotpink sticks and the DOT1L structure is shown in vacuum electrostatics; all binding-mode figures were generated using PyMOL, version 1.3r1.57 Figure 4. Cellular activity of compound DC_L115. (A) Human leukemia cell lines were treated with 1.875, 3.75, 7.5, 15, 30, 60, 120, and 240 µM DC_L115 for 72 h. (B, C) Human normal-lung fibroblast cell lines were treated with 1.875, 3.75, 7.5, 15, 30, 60, 120, and 240 µM DC_L115 for 72 h.


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Table of Contents graphic



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Figure 1. Virtual-screening procedures and DOT1L-activity assays in vitro. (A) Flow chart of the integrated virtual screening for DOT1L inhibitors. A structure-based strategy combining docking- and pharmacophorebased virtual screening. (B) Inhibitory activities of the 117 compounds at 50 µM. EPZ004777 was used as a positive control (red column); among them, 10 compounds (blue columns) inhibited DOT1L activity by >50% in the AlphaLISA assay. 109x44mm (300 x 300 DPI)


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Figure 2. Radioactive methylation assays for DOT1L. (A) Ten compounds (blue columns in Figure 1B) were retested at 100 µM using a radioactive methylation assay; the red column denotes the reference compound SAH; 3 of the 10 compounds showed >50% inhibition of DOT1L activity (blue columns). (B) Structure and inhibitory activity of DC_L94 against DOT1L. (C) Structure and inhibitory activity of DC_L107 against DOT1L. (D) Structure and inhibitory activity of DC_L115 against DOT1L. 177x165mm (300 x 300 DPI)



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Figure 3. Binding assays between DOT1L and DC_L115. (A) SPR assay of the binding between DOT1L and DC_L115; the concentrations of DC_L115 injected over the CM5 chip are indicated; SPR curves for DC_L115 binding with DOT1L are shown; KD was 0.60 µM for DC_L115 binding with DOT1L. (B, C) Putative binding mode of DC_L115 in the DOT1L structure (PDB ID: 3QOW). (B) A close-up view of the key interactions involved in stabilizing DC_L115 at the SAM binding pocket; DC_L115 is shown as cyan sticks, and surrounding key residues are shown as yellow sticks and labeled; the DOT1L structure is depicted as wheat cartoons; hydrogen bonds are depicted as dotted red lines, and Phe223 involved in the π-π stacking interactions formed between DC_L115 and DOT1L is also labeled out. (C) The SAM binding site of DOT1L occupied by DC_L115 aligned with SAM; DC_L115 is depicted as cyan sticks while SAM is depicted as hotpink sticks and the DOT1L structure is shown in vacuum electrostatics; all binding-mode figures were generated using PyMOL, version 1.3r1. 85x39mm (300 x 300 DPI)


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Figure 4. Cellular activity of compound DC_L115. (A) Human leukemia cell lines were treated with 1.875, 3.75, 7.5, 15, 30, 60, 120, and 240 µM DC_L115 for 72 h. (B, C) Human normal-lung fibroblast cell lines were treated with 1.875, 3.75, 7.5, 15, 30, 60, 120, and 240 µM DC_L115 for 72 h. 574x150mm (300 x 300 DPI)


Identification of Novel Disruptor of Telomeric Silencing 1-like (DOT1L

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