G9a through virtual screening

Journal Pre-proof Identification of novel quinoline inhibitor for EHMT2/G9a through virtual screening M.Ramya Chandar Charles, Arun Mahesh, Shu-Yu Lin, Hsing-Pang Hsieh, Arunkumar Dhayalan, Mohane Selvaraj Coumar PII:

S0300-9084(19)30329-3

DOI:

https://doi.org/10.1016/j.biochi.2019.11.006

Reference:

BIOCHI 5789

To appear in:

Biochimie

Received Date: 11 June 2019 Accepted Date: 14 November 2019

Please cite this article as: M.R. Chandar Charles, A. Mahesh, S.-Y. Lin, H.-P. Hsieh, A. Dhayalan, M.S. Coumar, Identification of novel quinoline inhibitor for EHMT2/G9a through virtual screening, Biochimie, https://doi.org/10.1016/j.biochi.2019.11.006. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

Identification of novel quinoline inhibitor for EHMT2/G9a through virtual screening Abstract G9a (also known as EHMT2 - Euchromatin histone methyltransferase 2) is a protein lysine methyltransferase which introduces methylation modification in variety of proteins including histones. G9a catalyzes the dimethylation of lysine 9 on histone 3 (H3K9me2) which is a repressive epigenetic modification. H3K9me2 is associated with the silencing of several genes including tumor suppressor genes in many cancers and hence G9a is a well characterized drug target for cancer therapy. Here, we report the discovery of CSV0C018875 as a novel quinoline based G9a inhibitor through virtual screening strategy from a HTS database. Sub-structure querying based on the known G9a inhibitors, followed by docking based virtual screening, led to the identification of CSV0C018875 as G9a inhibitor. We found that CSV0C018875 inhibits the activity of G9a in both enzyme and cell based assays. Importantly, the toxicity of CSV0C018875 is much lesser than that of the well-studied G9a inhibitor, BIX-01294. Molecular dynamics simulations shows that CSV0C018875 binds deeper inside the active site cavity of G9a, which facilitates the tight binding and also increases the compounds residence time, which in turn reflects better G9a inhibition. The novel quinoline CSV0C018875 could be further optimized to improve the ADME as well pharmacodynamic property.

Identification of novel quinoline inhibitor for EHMT2/G9a through virtual screening M Ramya Chandar Charles,a,# Arun Mahesh,b,# Shu-Yu Lin,c Hsing-Pang Hsieh,c Arunkumar Dhayalan,b,* Mohane Selvaraj Coumara,*

a

Centre for Bioinformatics, Pondicherry University, Kalapet, Puducherry 605014, India.

b

Department of Biotechnology, Pondicherry University, Kalapet, Puducherry - 605 014, India.

c

Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes,

35 Keyan Road, Zhunan, Miaoli County 350, Taiwan, ROC.

#

Equaly contributed to this work

*Correspondence: [email protected]; [email protected]

Abstract G9a (also known as EHMT2 - Euchromatin histone methyltransferase 2) is a protein lysine methyltransferase which introduces methylation modification in variety of proteins including histones. G9a catalyzes the dimethylation of lysine 9 on histone 3 (H3K9me2) which is a repressive epigenetic modification. H3K9me2 is associated with the silencing of several genes including tumor suppressor genes in many cancers and hence G9a is a well characterized drug target for cancer therapy. Here, we report the discovery of CSV0C018875 as a novel quinoline based G9a inhibitor through virtual screening strategy from a HTS database. Sub-structure querying based on the known G9a inhibitors, followed by docking based virtual screening, led to the identification of CSV0C018875 as G9a inhibitor. We found that CSV0C018875 inhibits the activity of G9a in both enzyme and cell based assays. Importantly, the toxicity of CSV0C018875 is much lesser than that of the well-studied G9a inhibitor, BIX-01294. Molecular dynamics simulations shows that CSV0C018875 binds deeper inside the active site cavity of G9a, which facilitates the tight binding and also increases the compounds residence time, which in turn reflects better G9a inhibition. The novel quinoline CSV0C018875 could be further optimized to improve the ADME as well pharmacodynamic property. Keywords: Small molecule inhibitors, histone lysine methyltransferase, G9a enzyme, molecular dynamics and virtual screening.

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1. Introduction Protein lysine methyltransferases (PKMTs) belong to the class of epigenetic “writer” enzymes that introduces methylation modifications on lysine residues of histones and other proteins by using S-adenosyl methionine (SAM) as a methyl group donor. Methylation on histones may either results in the activation or suppression of gene transcription depending upon the position of the lysine which is methylated. Mounting evidences suggest that alterations in PKMTs activity plays a major role in various disease conditions [1]. Hence, selective inhibition of PKMTs will be a useful in those disease conditions. G9a (EHMT2) was identified as SET domain containing methyltransferase primarily responsible for mono- and di-methylation on ε-amino group of H3K9, which suppresses the gene expression. In addition, G9a methylate several non-histone proteins including p53, a tumor suppressor protein, which is inactivated by G9a mediated methylation [2,3]. The functions of G9a are implicated in the serine metabolism [4], Prader–Willi syndrome [5], maintenance of HIV-1 latency [6], colitis [7], intellectual disabilities and cognitive disturbances (mental retardation, memory formation, age-related cognitive decline, cocaine addiction) [8], embryonic development [9], and cellular reprogramming to produce inducible pluripotent stem cells (iPSCs) [10]. Up-regulation of G9a was reported in various cancers which are associated with metastasis and poor prognosis [11–13]. Knockdown of G9a inhibits the growth of prostate, leukemia and lung cancer cells [14–16]. Recent evidences show that pharmacological inhibition of G9a prolonged the life of hematological cancer xenogeneic mouse models [17]. All these reports establish that G9a is a potential therapeutic target for cancer therapy.

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Table 1. Reported G9a inhibitors. Inhibitor

Core

X

L

H

S

BIX-01294

Core 1

N

CH3

H1

S1

UNC0224

Core 1

N

L1

H1

S2

UNC0321

Core 1

N

L2

H1

S2

UNC0638

Core 1

N

L3

H2

S3

UNC0642

Core 1

N

L3

H3

S3

A-366

Core 2

-

L3

-

-

CM-272

Core 1

C

L3

H4

S3

BIX-01294 is the first selective inhibitor of G9a discovered through high throughput chemical library screening [18]. Exploiting the quinazoline core structure of BIX-01294, several analogs, including UNC0224, UNC0321, UNC0642 and UNC0638 were reported with improved G9a inhibitory activity and cellular potency (Table 1) [19]. Alternative to the quinazoline core inhibitors of G9a, indole core containing A-366 [20] and quinoline core containing CM-272 [17], a dual inhibitor of G9a and DNMT1 with in vivo activity in AML mouse models are reported [21]. The co-crystal structures of G9a-UNC0224 and G9a-UNC0638 shows that, both the inhibitors bind in the substrate binding site of G9a and the lysine mimic (L1 group of UNC0224 and L3 group of UNC0638) side chain occupy the lysine binding tunnel of G9a catalytic site [22–24]. A detailed analysis of the SAR and co-crystal structure of G9a-inhibitor complex, suggest that the presence of lysine mimic side chain is an essential feature in the design of potent G9a inhibitors with cellular activity [25].

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Here, we report the discovery of CSV0C018875, a novel quinoline core based G9a inhibitor without a lysine mimic side chain from HTS library of 1,50,000 compounds through virtual screening (Fig. 1). CSV0C018875 inhibits the enzymatic activity of G9a in vitro, and in cell based in vivo assay. Importantly, CSV0C018875 shows lesser cytotoxicity than that of wellstudied G9a inhibitor, BIX-01294 in HEK293 and HeLa cells. Docking studies and molecular dynamics investigations suggest that CSV0C018875 binds to the active site of G9a much deeper than that of BIX-01294 and UNC0638, resulting in G9a inhibition, even though it lacks the classical lysine mimic side chain bearing an amino group (such as L1, L2 and L3 groups, Table 1). CSV0C018875 could constitute a novel tool compound both to explore the functions of G9a as well as act as a starting point for SAR exploration to identify novel inhibitors of G9a.

Figure 1. Virtual screening workflow that was used in the identification G9a inhibitors from in-house HTS library. A total of 1,50,000 compounds were screened in a hierarchical manner to select and test six compounds for G9a inhibition. 5

2. Experimental section 2.1. Computational methods 2.1.1. Sub-structure screening of database Sub-structure queries 1-4 (Fig. 2) were designed based on the core ring scaffolds of the previously reported G9a inhibitors. The sub-structure queries include quinoline 4-amine, 2methylquinazolin-4-amine, 2-methyl-5H,6H,7H-cyclopenta[d]pyrimidin-4-amine and 6-methyl7H-pyrrolo[2,3- ]pyrimidine. They were used to query the in-house HTS database as described before [26]. 331 compounds were retrieved from the database and further used for docking.

Figure 2. Sub-structure queries used to retrieve compounds from in-house HTS database. The sub-structure queries were designed based on the core structure of known G9a inhibitors. 2.1.2. Docking based virtual screening Docking based virtual screening (DBVS) was performed using extra precision mode of Glide module in Schrodinger maestro [26]. For this, 3D coordinates of two G9a-inhbitor complexes (PDB ID: 3K5K and 3RJW) were retrieved from PDB and were used. The protein structures 6

were pre-processed using protein preparation wizard of maestro. All hydrogens were added and a simple restrained minimization was performed to remove the steric clashes in the protein structure. Active site grid was set around 10 Å of the crystalized ligands in all three dimensions. Ligands (331) retrieved from HTS database through sub-structure query were prepared using Ligprep module of Schrodinger. Possible isomeric and tautomeric states were predicted using Hammett and Taft methodology associated with energy based penalties at pH 7.0 ± 0.2 for the compounds with epic tool incorporated in Ligprep module. For assessing the validity of docking procedure, co-crystalized G9a inhibitors were also prepared and used as internal standard along with HTS compounds. During docking run, default parameters were used. 2.1.3. Molecular dynamics simulations and binding free energy calculation Simulations were carried with Amber16 package [27]. Ligand and co-factor parameters were generated using antechamber program using AM1-BCC basis parameter set and treated with general AMBER force field [28]. Protein was prepared using ff99SB force filed with default protonation state and zinc atoms of G9a were treated using cationic dummy approach [29]. All protein-ligand-cofactor complexes were placed in a cubic box with the margin of 10 Å from the edges of the box in each dimension. Neutrality of the system was achieved by adding counter ions. TIP3P water model [30] were used for solvating the complexes by means of LEaP program [27]. Particle Mesh Ewald (PME) method [31] was used to treat the long-range electrostatic interactions and Coulomb and van der Waals potentials were calculated using a cutoff radius of 10 Å. SHAKE algorithm was used to constraint all bond lengths and the time integration step of 2 fs was used for all simulations. The system was minimized using steepest descent method then gradually heated up to 300 K by applying harmonic restrains with a force constant of 2.0 kcal/mol.Å2. Then the pressurization phase was carried out for 500 ps at 1 atm pressure 7

maintained using Langevin piston barostat. Production run was carried out for 100 ns time period under NPT conditions without any restraints. Trajectory was processed using cpptraj module of Amber tools [32]. 2000 frames, taken at equal intervals over the 100 ns of the production run were used to calculate the MMPBSA binding free energy. Calculation was performed using MMPBSA.py [33] program in the AMBER16 package. For this calculation inp=1 was used for non-polar solvation model [34] radiopt=0 was used for atomic radii and ionic strength was set to 0.100 mM. Other parameters were kept at default values of AMBER16 [27]. 2.1.4. Steered molecular dynamics In steered molecular dynamics (SMD), external force is applied on the ligand bound to a protein, to facilitate the ligand unbinding process. During the unbinding process, external force applied on the system can be calculated. Depending on the amount of force exerted on the system we can define the strength of the ligand bound with the protein. From the Amber trajectory 100, 90 and 80th ns frames were extracted and used for SMD. All SMD simulations were performed in NAMD v2.12 [35]. A predefined pathway is required for SMD to calculate the ligand release. For this, the direction vector defined by the center of mass of the protein and the center of mass of the ligand was set as the ligand dissociation path and each SMD experiment was repeated three times [36]. To avoid severe distortions in the protein conformations during the SMD, few residues which are not part of the active site were kept as stationary atoms. Pulling parameters, in particular the spring constant was set to 5 kcal/mol.Å2 and the velocity of pulling was set to 0.005 Å/ps. The ligands were pulled to a distance of 25 Å in which the protein and the ligand interaction will be completely lost. Native contact analysis was performed between the ligand and the protein with a distance cutoff of 7 Å. The time ligand completely lost contacts with

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protein was considered as ligand residence time. Trajectory frames were recorded for every picosecond. 2.2. Synthesis of hit 4-Chloroaniline, ethyl acetoacetate, indium (III) chloride, and phenyl ether were purchased from Acros and 4-ethoxyaniline from Tokyo Chemical Industry. All other reagents were of synthesis grade. For detailed general synthetic methods, refer to our previous publication [37]. 2.2.1. Ethyl (E)-3-((4-chlorophenyl)amino)but-2-enoate (3). To a mixture of 4-chloroaniline (1, 1.91 g, 15.0 mmol) and ethyl acetoacetate (2, 1.91 mL, 15.0 mmol), added indium (III) chloride (15.0 mg, 67.8 µmol) at room temperature. The mixture was stirred at 100 °C for 4.0 h, cooled to room temperature, diluted with methanol (15 mL), filtered through a pad of celite and concentrated under reduced pressure to give a residue. The residue was purified by flash column chromatography (10% hexanes in ethyl acetate) to give 3 (1.75 g, 49%) as a solid product. 1HNMR (400 MHz, DMSO-d6) δ 10.32 (br s, 1H), 7.38 (d, J = 8.8 Hz, 2H), 7.21 (d, J = 8.8 Hz, 2H), 4.72 (s, 1H), 4.05 (q, J = 7.2 Hz, 2H), 2.00 (s, 3H), 1.19 (t, J = 7.2 Hz, 3H); LC-MS (ESI) m/z: 240.1 [M + H]+. 2.2.2. 6-Chloro-2-methylquinolin-4(1H)-one (4). A solution of compound 3 (1.00 g, 4.18 mmol) in phenyl ether (9.0 mL) was heated to 200 °C for 3.5 h, then cooled to room temperature, and dissolved in ethyl acetate. The solution was poured into hexanes to give a precipitate; the solid was collected by filtration to give the desired product 4 (536 mg, 66%). 1H-NMR (300 MHz, DMSO-d6) δ 11.76 (br s, 1H), 7.95 (d, J = 2.4 Hz, 1H), 7.64 (dd, J = 8.8, 2.4 Hz, 1H), 7.53 (d, J = 8.8 Hz, 1H), 5.95 (s, 1H), 2.34 (s, 3H), 1.19 (t, J = 7.2 Hz, 3H); LC-MS (ESI) m/z: 194.1 [M + H]+.

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2.2.3. 4,6-Dichloro-2-methylquinoline (5). To a solution of compound 4 (800 mg, 4.13 mmol) in toluene (8.0 mL), added phosphoryl chloride (1.93 mL, 20.7 mmol) and stirred for 15 min. Then N,N-diisopropylethylamine (DIPEA, 3.60 mL, 20.7 mmol) was added slowly to the solution; the resulting solution was stirred at 100 °C for 3.0 h and then poured into ice-water. The solution was diluted with water and dichloromethane and basified by Na2CO3(aq). The mixture was extracted twice with dichloromethane, dried over MgSO4(s), filtered, and concentrated to give a residue. The residue was purified by flash column chromatography (dichloromethane) to give 5 (480 mg, 55%) as a solid product. 1H-NMR (400 MHz, DMSO-d6) δ 8.13 (d, J = 2.4 Hz, 1H), 8.02 (d, J = 8.8 Hz, 1H), 7.85 (dd, J = 8.8, 2.4 Hz, 1H), 7.77 (s, 1H), 2.66 (s, 3H); LC-MS (ESI) m/z: 212.0 [M + H]+. 2.2.4. 6-Chloro-N-(4-ethoxyphenyl)-2-methylquinolin-4-amine (6). A solution of compound 5 (164 mg, 0.773 mmol) and 4-ethoxyaniline (0.120 mL, 0.928 mmol) in acetic acid (2.0 mL) was heated to 120 °C for overnight in a sealed tube. The reaction was quenched by the addition of water and neutralized with 6N NaOH(aq) solution. The mixture was extracted with dichloromethane, dried over MgSO4(s), filtered, and concentrated to give a residue. The residue was purified by flash column chromatography (12.5–50% ethyl acetate in dichloromethane) to give 6 (63 mg, 26%) as a solid product. 1H-NMR (400 MHz, DMSO-d6) δ 8.77 (s, 1H), 8.44 (d, J = 2.4 Hz, 1H), 7.75 (d, J = 8.8 Hz, 1H), 7.63 (dd, J = 8.8, 2.4 Hz, 1H), 7.25 (d, J = 8.8 Hz, 2H), 7.00 (d, J = 8.8 Hz, 2H), 6.55 (s, 1H), 4.05 (q, J = 6.8 Hz, 2H), 2.39 (s, 3H), 1.35 (t, J = 6.8 Hz, 3H); LC-MS (ESI) m/z: 313.1 [M + H]+.

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2.3. Biological methods 2.3.1. Cloning, expression and purification of recombinant G9a enzyme: The sequence encoding human G9a C-terminal region (280 amino acids) was PCR amplified from the cDNA prepared from the HEK293 cells using Advantage HD polymerase (Clontech) and cloned in to pET28a bacterial expression vector. The protein expression and purification was performed as described previously [38]. The purified proteins were loaded in 12% SDS PAGE to analyze the quantity and quality of the recombinant protein (Fig. S1, supporting information).

2.3.2. In vitro ELISA based assay of G9a enzyme activity To screen the effective inhibitors for G9a, we developed in vitro ELISA based assay similar to the avidin coated 96 well plate method described previously [39] with the following modifications. 1 µg of neutravidin prepared in 100 mM NaHCO3 (pH 9.6) buffer was added to each well of 96 well microtitre high binding plate (Corning: 3590) and incubated at 4 ºC for overnight. The wells were washed with TTBS (50mM Tris-Cl (pH 7.5), 150mM NaCl and 0.1% Tween 20) for five times to remove the unbound neutravidin. Then the wells were blocked with 5% BSA prepared in TTBS buffer for 1 h in room temperature with shaking and the plates were kept at 4 ºC. The in vitro methylation assay was carried out in methylation buffer (50 mM Tris, (pH 7.4), 4 mM DTT, 5 mM MgCl2) by incubating 100 nM of biotinylated H3 histone peptide (Anaspec: 61702) as a substrate with 200 nM of G9a and 100 µM S-adenosyl- L-methionine (SAM). The reaction mixtures were supplemented with or without the G9a inhibitors and incubated for 3 h at room temperature. After the incubation, the reaction mixtures were transferred to the neutravidin coated 96 well plate and incubated for 30 min at room temperature with continuous shaking. Unbound enzyme, SAM and inhibitors were removed by washing the plate with 200 µl of TTBS for five times. Biotinylated peptide coupled plate was then incubated with anti-H3K9me2 antibody (Abcam: ab1220) for 1 h at room temperature. After the incubation, plate was washed three times with TTBS and then incubated with HRP conjugated anti-mouse 11

(secondary antibody GE healthcare: NA931V) for 1 h at room temperature, then the plate was washed with TTBS and the ELISA signals were generated and measured using TMB substrate kit (Thermo scientific: 34021) according to the manufacturer’s instructions. The colorimetric reading was recorded on Dynex triad multimode reader at 450 nm.

2.3.3. Cell based assay of G9a enzyme activity To measure the activity of G9a inhibitors, HEK293 cells were treated with 2.5 µM of BIX-01294 or 2.5 µM or 10 µM or 20 µM of CSV0C018875 compound for 48 hours. After 48 hours of treatment, cells were collected and native histone was isolated using standard acid extraction method as described previously [40]. The isolated histones were resolved in 15% SDS PAGE and transfer to the PVDF membrane by semidry transfer method. The membrane was blocked with 5% blocking agent (GE healthcare: RPN2125) and probed with anti-H3K9me2 (Abcam: ab1220) antibody or anti-histone 3 antibody (Abcam: ab1791) antibody to measure the levels of H3K9me2 modifications. The anti-histone 3 antibody is used for normalizing loading amount.

2.3.4. MTT assay The cytotoxicity effects of the BIX-01294 and the CSV0C018875 compound were analyzed in HEK293 cells and HeLa cells by MTT assay. For MTT assay, HEK293 cells and the HeLa cells were seeded in 96 well plate and the cells were treated with compound CVS0108875 or BIX-01294 at different concentrations (2.5 µM, 5 µM, 10 µM and 20 µM) for 48 hours. The proteasomal inhibitor and apoptosis inducer drug MG-132 (Sigma; M7449) was used as a positive control for MTT assay. Cells treated with the vehicle (DMSO) served as a negative control. After 48 h of incubation cells were washed with DMEM (Dulbecco’s Modified Eagle’s medium) and MTT assay was performed as described previously [41].

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3. Results & discussion 3.1. Sub-structure query design and database screening Compounds for virtual screening were retrieved from the in-house HTS database of 1,50,000 compounds using sub-structure queries. Sub-structure queries were used to filter the database compounds, so that the number of compounds subjected to docking-based virtual screening will be much lower and manageable. Sub-structure querying is a relatively easy method and at the same time very powerful way of identifying new ligands. We have previously used sub-structure based screening of our in-house HTS database for the successful identification of several kinase inhibitors [26,42], which lead to the development of several class of drug-like molecules [43–45]. The sub-structure queries for the current study were designed from prominent scaffolds of already known inhibitors of G9a. We have recently analyzed the literature reported G9a inhibitors and found that majority of G9a inhibitors bear the quinazoline ring (present in BIX01294, UNC0224 and UNC0638). Also pyrrolopyrimidine and quinoline rungs are present in well-known G9a inhibitors A-366 and CM-272, respectively. Based on this, four substructure queries (Fig. 2) were designed and used to screen the in-house database, which retrieved a total of 331 compounds from the database. 3.2. Docking based virtual screening (DBVS) of selected database compounds Next, the 331 compounds retrieved from the in-house database were subjected to docking based virtual screening (DBVS) in two crystal structures (PDB ID: 3K5K and 3RJW). For the DBVS, three G9a co-crystal structure inhibitors UNC0224 (from PDB ID: 3K5K), UNC0638 (from PDB ID: 3RJW) and A-366 (from PDB ID: 4NVQ), along with BIX-01294 were used as reference standard. These inhibitors would serve as quality check for the DBVS protocol and 13

also would help to define the cutoff docking score to select the compounds for biological testing. The three co-crystal structures inhibitors were bound in the substrate peptide binding site of G9a. PMTs such as G9a has a substrate peptide binding site and a co-factor binding site; the cofactor S-adenosyl methionine (SAM; methyl donor) binding site is quite similar within the sub-family of methyltransferase and the substrate peptide binding site is distinct for each methyltransferases. Selective inhibition of a PMTs is achieved by targeting the substrate peptide binding site instead of the cofactor binding site [1]. Hence, for the DBVS, we used the substrate peptide binding site where the inhibitors UNC0224, UNC0638 and A-366 were bound. Using the Glide XP program, 335 (331 compounds from database + 4 known inhibitors) compounds were docked in the substrate binding site of G9a, scored and ranked. A total of 518 docked poses were generated for the 335 compounds. Out of 518 poses, 157 and 104 poses docked in the active site of 3RJW and 3K5K structures, respectively. This showed that only 130 and 93 compounds docked into the 3RJW and 3K5K structures, respectively. Next, the docked poses were analyzed individually and selected with the criteria that the compounds should have a docking score greater than the co-crystal inhibitors and also should make essential interactions within the G9a active site. Our previous analysis of the G9a-susbtrate peptide and G9a-inhibitor complexes, as well as structure - activity relationship (SAR) of G9a inhibitors has provided detailed insights about the preferred site and residues for inhibitor binding within the protein and the crucial ligand binding groups for G9a inhibitors [46]. The key findings from the analysis are, (i) compounds with a lysine mimic group that occupy the lysine tunnel in the substrate binding site are potent and selective to G9a target and (ii) it is crucial for the G9a inhibitors to interact with one or more

14

of the residues – Asp1074, Asp1083, Leu1086, Asp1088, Tyr1154, and Phe1158, for potent G9a inhibition [25,46].

Figure 3: Binding mode of compounds identified from docking based virtual screening in PDB ID: 3RJW. (A) Crystal structure conformation of reported G9a inhibitor UNC0638 (PDB ID: 3RJW). (B) Docking pose of 150 compounds in PDB ID: 3RJW. (C) Docking pose of 19 compounds selected based on interaction within the G9a crucial region surrounded by the six key residues (Asp1074, Asp1083, Leu1086, Asp1088, Tyr1154, and Phe1158). Protein shown in yellow surface view and ligands in cyan sticks. Key G9a residues are colored red and labeled. Red circle highlights the compounds bound in the G9a crucial region and black circle highlights the compounds bound in other regions of G9a. Based on these insights from previous investigations, the docked compounds in both the G9a structures were analyzed, to pick only those compounds that are bound within the active site lined by the six key residues (Asp1074, Asp1083, Leu1086, Asp1088, Tyr1154, and Phe1158) and also interact inside the catalytic lysine binding tunnel (Fig. 3). Based on these criteria a total of 19 compounds were retrieved from docking in 3RJW and 15 from docking in 3K5K crystal structures (Tables S1 and S2, supporting information). In both the docking, three co-crystal ligands UNC0224, UNC0638 and A-366 were also retrieved, suggesting that the docking

15

protocol would be reliable to pick active G9a inhibitors. Among them, four compounds (CSV0A016876, CSV0A016969, CSV0D043260 and CSV0D043256) were present in both the list and were selected for biological testing for G9a inhibition. Moreover, two compounds (CSV0C018875 and CSV0C011685) with a Glide XP docking score better than the co-crystal ligand A-366 were also selected for biological testing (Table 2). Of the six compounds, 3 had a quinazoline and the remaining 3 had a quinoline core [43–45]. Table 2. G9a inhibitory activity of the compounds selected from docking based virtual screening.

Structure

Code CSV0A016876 CSV0A016969 CSV0C018875 CSV0C011685 CSV0D043260 CSV0D043256 A-366 UNC0638 BIX-01294 a

X C N C C N N

R1 S1 S1 S2 S3 S4 S5

R2 CH3 CH3 CH3 CH3 S6 S6

R3 OCH3 H Cl Cl H H

Docking score R4 H Cl H H H H

3RJW -10.84 -9.69 -9.59 -9.48 -8.53 -9.25 -8.70 -

3K5K -8.90 -7.68 -7.74 -6.92 -7.66 -6.83 -6.84 -

% Inhibition of G9a at 100 µM concentration 19.7 7.2 44.6 (72)a 7.1 4.9 4.9 91

Resynthesized compound showed 72% inhibition

3.3. Identification of CSV0C018875 as a novel G9a inhibitor The six compounds that were selected using docking based virtual screening (DBVS) were tested for their efficiency to inhibit the enzymatic activity of G9a at a concentration of 100 µM using in vitro ELISA based assay. BIX-01294, the standard inhibitor of G9a was also 16

included in the assay as a positive control (Table 2). Among the tested compounds, CSV0C018875 shows a maximum of 44.6% of inhibition of G9a enzyme at 100 µM concentration. CSV0C018875 was identified only in 3K5K docking, but not in 3RJW screening. Another compound CSV0A016876, a quinazoline identified in both screening, inhibited the activity of G9a by 20%. The remaining four compounds inhibited the G9a by less than 10%. The positive control, BIX-01294 exhibited 92% of inhibition of G9a activity at 100 µM concentration. Based on these results, the quinoline ring containing CSV0C018875 compound was selected for further investigation. Further, the selected compound CSV0C018875 was structurally dissimilar from the previously reported G9a inhibitors. The calculated 2D tanimoto similarities with the known G9a inhibitors were < 0.34 (Table S3, supporting information). Since the in-house HTS compounds were procured long time back, we synthesized the CSV0C018875 compound to confirm the structural identity as well as biological activity. The synthesized CSV0C018875 compound with a purity of 98% inhibited the enzymatic activity of G9a in a dose-dependent manner. The synthesized CSV0C018875 compound and BIX-01294 inhibited the G9a activity by 72% and 91% respectively at 100 µM concentration (Fig. 4A). Moreover, the IC50 values were calculated and found to be 3.83 ± 0.12 µM for BIX-01294 and 67.02 ± 0.64 µM for CSV0C018875. We have also noticed that the solubility of the synthesized compound in DMSO is not very good and hence repeated freeze and thaw of compound affects its performance. We then investigated the inhibitory potential of CSV0C018875 on G9a enzymatic activity by using cell based assay. For this, we incubated the HEK293 cells with BIX-01294 or CSV0C018875 at different concentrations for 48 hours and quantified the global H3K9me2 17

modification levels in these cells by immunoblotting using a modification specific antibody. The levels of H3K9me2 reflects the activity of G9s in the cells. We found that the CSV0C018875 compound inhibited the enzymatic activity of G9a in a dose-dependent manner in HEK293 cells (Fig. 4B). Strikingly, the inhibition of G9a activity is higher than that of BIX-01294 suggesting that cell permeability of CSV0C018875 is better than BIX-01294 (Fig. 4B). We investigated the cytotoxicity of CSV0C018875 and BIX-01294 in HEK293 cells and HeLa cells by MTT assay. We included the proteasomal inhibitor drug, MG-132 as a positive control for MTT assay, which is known to induce apoptosis [47,48]. We observed that BIX-01294 exhibited a stronger cytotoxicity as reported previously [49]. Strikingly the toxicity of CSV0C018875 is much lesser than that of BIX-01294 in both HEK293 and HeLa cells (Fig. 4C). While the BIX-01294 reduced the cell viability by 63% in HEK293 cells at 2.5 µM concentration, the compound CSV0C018875 reduced the cell viability only by 8% in HEK293 cells at the same concentration (Fig. 4C). All these data establish that CSV0C018875 inhibits the enzymatic activity of G9a both in vitro enzyme and cell based assays and the cytotoxicity of CSV0C018875 is low.

18

Figure 4. CSV0C018875 inhibits the enzymatic activity of G9a. (A) CSV0C018875 and BIX01294 inhibits the enzymatic activity of G9a in the ELISA based in vitro assay in a dose dependent manner. Data are presented as mean of three independent experiments, with error bars representing standard deviations. (B) HEK293 cells were treated with indicated concentrations of CSV0C018875 and BIX-01294 for 48 hours and the histones were isolated from these cells. The levels of H3K9me2 modifications in the histones were quantified by immunoblotting using antiH3K9me2 antibody. H3 antibody is used as a loading control. The experiments were repeated three times and the H3K9me2 signals in the immunoblots were quantified and normalized to the H3 signal and are presented relative to the control sample (Bar graph on the bottom). Data are 19

represented as mean of three experiments, with error bars representing standard deviations. (C) HEK293 and HeLa cells were treated with indicated concentrations of CSV0C018875 and BIX01294 for 48 hours and their toxicity were assessed by MTT assay. Data are represented as mean of three independent experiments, with error bars representing standard deviations. 3.4. Computational investigation of CSV0C018875 binding to G9a In order to understand the mode of interaction of CSV0C018875 with G9a, as well pave a way for the structural exploitation to design better analogs, detailed computational studies were carried out. CSV0C018875 makes a pi-pi interaction with Tyr1154 and hydrophobic contacts with residues Tyr1067, Phe1087, Tyr1154 and Phe1158. However, it does not make H-bonds with the G9a residues. Unlike in BIX-01294, where the lysine tunnel is unoccupied, the 4ethoxy-anilino substituent on the quinoline ring of CSV0C018875 binds deeper inside the lysine tunnel (Fig. 5). It was found that the presence of the 4-ethoxy-anilino substituent is essential for activity, as the closely related analog CSV0C011685 with 2-ethoxy-anilino substituent was found to be inactive. Hence, it will be pertinent to investigate if the 4-ethoxy-anilino substituent on the quinoline ring of CSV0C018875 can interact in the lysine tunnel of G9a in a stable manner. Moreover, unlike the UNC0638 and other potent G9a inhibitors with a terminal amino group in the lysine mimic side chain, CSV0C018875 does not have amino group at the lysine mimic side chain. This feature could be exploited for improving the activity of CSV0C018875, by introducing an amino group in the aniline ring.

20

Figure 5. Binding mode of (A) BIX-01294, (B) UNC0638 and (C) CSV0C018875 in G9a. Lysine tunnel of G9a is occupied by UNC0638, whereas BIX-01294 lacks the lysine mimic side chain, hence the tunnel is left unoccupied. The 4-ethoxy-anilino substituent of CSV0C018875 binds deeper inside the lysine tunnel of G9a and mimics the lysine binding. Protein surface shown in yellow and ligands in cyan sticks. Key G9a residues involved in interaction with inhibitors are colored red and labeled. To check the stability of the G9a-CSV0C018875 complex, it was subjected to 100 ns molecular dynamics simulation. Conformational stability of the complex was analyzed with root mean square deviation (RMSD) and root mean square fluctuation (RMSF) plots from the simulation trajectories (Fig. 6). RMSD plot shows G9a exhibits more flexibility when it is bound with BIX-01294 than with UNC0638 and CSV0C018875. The conformational divergence of G9a-BIX-01294 complex is due to the increased fluctuations (RMSF) of active site and the lysine binding tunnel residues. Reduced flexibility was observed for the lysine tunnel residues in the presence of UNC0638 and CSV0C018875, as the lysine binding tunnel was occupied and the residues interacted with the inhibitors; whereas, in the case of BIX-01294 the tunnel was unoccupied by the inhibitor (Fig. 5). Comparatively, UNC0638 is a larger molecule and binds to larger area of the G9a active site than BIX-01294 and CSV0C018875. This results in a stable complex of G9a-UNC0638 with lower RMSF of the residues. The deeper binding of 21

CSV0C018875 inside the lysine binding tunnel using the 4-ethyoxy-anilino group forms a tight complex with the lysine tunnel residues, resulting in lower RMSF; however, residues are still flexible at the mouth of the binding pocket.

Figure 6. Molecular dynamics simulation trajectories of G9a-inhibitor (BIX-01294, UNC0638 and CSV0C018875) complexes for 100 ns. (A) Plots of root mean square deviation (RMSD) of backbone atoms and (B) root mean square fluctuations (RMSF) of residues. Next, the H-bond formation between the protein and ligand was investigated. For this, the life time of the H-bonds was calculated and those that are present continuously for at least one nano second were taken into account. BIX01294 formed a total of four H-bonds, one each with Asp1083 (1.06 ns) and Arg1157 (1.36 ns), and two with side chain terminal oxygen atoms of Asp1078 (1.92 ns and 1.28 ns). UNC0638 makes two H-bonds with residues Asp1083 (1.56 ns) and Leu1086, in which contact with Leu1086 was continuously observed for 7.56 ns. CSV0C018875 maintained contact with only Leu1086 for 1.19 ns. Other than these continuous H-bonds interactions, H-bond with Leu1086 was observed in more number of frames in the trajectory with UNC0638 (7654 frames) and CSV0C018875 (3427 frames) among the 10,000

22

written frames. Leu1086 residue is located inside the lysine tunnel, hence cannot be accessed by BIX-01294. Other than Leu1086, CSV0C018875 also forms H-bonds with Tyr1067 (1481 frames). On the other hand, BIX-01294 forms H-bond with Arg1157 (2460 frames), Asp1078 (2425 and 1407 frames) and Asp1074 (1248 frames) (Table S4, supporting information). This indicates that Leu1086 H-bond interaction is dominant but discontinuous in CSV0C018875. Next, the binding of the inhibitors to G9a was quantitatively assessed by using MMPBSA free energy binding calculation. UNC0638 (-40.43 kcal/mol) shows higher binding energy followed by BIX-01294 (-34.54 kcal/mol) and then CSV0C018875 (-24.12 kcal/mol). The lower ∆G for CSV0C018875 than that of BIX-01294 as well as UNC0638, could be due to the fact that

CSV0C018875 is much smaller in size and binds to smaller region of the G9a active site. However, CSV0C018875 had a ligand efficiency (LE) of -1.10, which is similar to UNC0638 (1.09) and higher than BIX-01294 (-0.96). Ligand efficiency (LE = ∆G/number of heavy atoms) is used to determine the binding energy of the non-hydrogen atoms of a ligand. LE parameter is used during virtual screening or high throughput screening to identify suitable hit/leads for lead optimization. Also LE is used in fragment-based drug design. Ligands with higher LE are more suitable for lead optimization, as the atom in the ligands bind stronger to the target. Moreover, ligands with better LE have more room for chemical modification [50,51]. Based on the LE criteria, CSV0C01887 is a better starting point for lead optimization program. Further, we also used steered molecular dynamics (SMD) simulations to investigate the G9ainhibitor interaction. SMD is used to understand the ligand egress pathways from the protein as well as to calculate the force required to pull the ligand from the protein [52,53]. SMD was performed using the G9a-inhibitor complex extracted from 80, 90 and 100th ns frame from the MD trajectories. While pulling the ligand, the native contacts between the ligand and the protein 23

was calculated and the time required for the ligand to lose all contacts with the protein was considered as the dissociation time. The average force required to pull the ligand out of G9a is maximum for CSV0C018875 (913.03 pN), followed by UNC0638 (902.66 pN) and then BIX01294 (755.85 pN) (Fig. 7 and Table S5, supporting information). BIX-01294 is pulled out of the active site with lower force as it binds in the mouth of the binding pocket. While, both CSV0C018875 and UNO0638 needs greater force for pulling, as they are bound deeper inside the active site and interacted with the target more strongly. This is also reflected in the longer time required for the dissociation of CSV0C018875 (361.11 ps) and UNO0638 (345.11 ps) from G9a, as compared to BIX-01294 (285.44 ps). To investigate the interactions during the dissociation phase, three representative complex structures were extracted from 0, 100 and 300th ps of the SMD simulations trajectory and noncovalent contacts between G9a and the inhibitors were analyzed (Figure S2, supporting information). Due to the location of binding, CSV0C018875 and UNC0638 have more hydrophobic contacts than BIX-01294. At the initial frame of SMD, CSV0C018875 shows unique contacts with residues Arg1109, Ile1099, Ile1111 and Ser1108, which are not observed with UNC0638 and BIX-01294. At 100 ps of dissociation, Arg1109, Tyr1067, Ile1111 and Gly1155 were found to be unique contact in CSV0C018875-G9a complex structure. Moreover, interaction with residues (Arg1157, Asp1088, Phe1158 and Ile1161) found at 300 ps dissociation frame of CSV0C018875 were observed at the starting frame and 100 ps frame of UNC0638/BIX-01294 and lost early during their dissociation from G9a. It should be noted that Asp1088 and Phe1158 are key residues important for the substrate peptide/inhibitor binding to G9a and CSV0C018875 maintains interaction with these residues for longer period of time during SMD dissociation phase. 24

Figure 7. Steered molecular dynamics (SMD) simulation to determine the force required to pull the inhibitors from G9a-inhibitor complexes. Pulling force plots for G9a-BIX-01294 (A, B & C), G9a-UNC0638 (D, E & F) and G9a-CSV0C018875 (G, H & I) complexes from 100th, 90th and 80th ns of MD simulation trajectories. Each SMD simulation was repeated thrice (black, red and green color) and the average puling force and dissociation mentioned. Further, the H-bond contacts maintained during the ligand unbinding process were analyzed and listed (complete list of H-bonds observed are listed in Table S6, supporting information and H-bonds observed for a minimum of 50 frames during the SMD simulation are shown in Fig. 8). During MD simulation, all the three G9a inhibitors did not form more than three H-bonds at any given time; this was also observed in SMD simulation. Only Leu1086 formed H-bonds in multiple runs of SMD of UNC0638 and CSV0C018875. This H-bond appeared in maximum number of frames in the dissociation trajectory of these compounds, but was not present in the case of BIX-01294. The result from SMD suggest that CSV0C018875 25

binds and interact with G9a quite similar to that of UNC0638, particularly it is able to make stable H-bond interaction with Leu1086 in the lysine binding tunnel.

Figure 8. H-Bonds formed and their lifetime (1frame/1ps) during SMD simulation. Pattern of H-bond contacts during ligand dissociation is similar for UNC0638 and CSV0C018875. Leu1086 maintains longer contact time with UNC0638 and CSV0C018875. 3.5. Synthesis of CSV0C018875 compound For the synthesis of the hit compound, Combes quinoline synthesis methodology was utilized (Scheme 1) [54]. The key intermediate 4-quinolinone (4) was constructed from 4-chloro-aniline by condensation with ethyl acetoacetate in two steps. Chlorination using POCl3 afforded the 4-

26

chloro quinoline (5). Nucleophilic attack by 4-ethoxy-aniline afforded the final product 6 in 4.6% yield over four steps. The products were characterized using 1H NMR and mass spectral data (Fig. S3-S5, supporting information). NH 2 O

O

+

OEt

Cl

OEt

b

Cl

O

Cl

2

O

H N

a

N H

3 4

1 O Cl c

Cl

HN

d Cl N 5

N 6

Scheme 1. Reagents and conditions: (a) InCl3, neat, 100ºC, 49%; (b) phenyl ether, 200ºC, 66%; (c) POCl3, DIPEA, toluene, 100ºC, 55%; (d) acetic acid, reflux, 26%. 4. Conclusion Histone methylation is one of the crucial epigenetic mark that regulates the gene expression and early cell differentiation. G9a represses the expression of several genes including tumor suppressor genes by generating H3K9me2 modifications. G9a is elevated in diverse cancer types and inhibition or depletion of G9a reduces the growth of cancer cells. Hence, selective inhibition of G9a serves as an emerging therapeutic target for cancer treatment. In this study, we report the identification and characterization of CSV0C018875, a novel quinoline based G9a inhibitor discovered through virtual screening. CSV0C018875 is a cell active G9a inhibitor, which exhibits lesser cytotoxicity than the previously reported quinazoline derivative BIX-01294. Further, computational investigations showed that CSV0C018875 binds deeper in the lysine binding tunnel of G9a efficiently as compared to BIX-01294. In this context, it’s noteworthy that CSV0C018875 is a useful lead G9a inhibitor for further optimization. 27

Conflicts of interest The authors declare no conflict of interest. Author contributions MRCC performed computational experiments and wrote the paper. AM performed biological experiments. SYL synthesized the compound under the guidance of HPH. HPH acquired the library compound collection. AD designed, analyzed and wrote the biology section. SMC oversaw the computational investigation, overall development of the project and corrected the paper. All authors read and approved the final article. Acknowledgements We acknowledge University Grants Commission, Government of India (Junior and Senior Research Fellowships to AM) and Department of Biotechnology, Government of India (for DBTʼs Twining program for North East-BT/246/NE/TBP/2011/77 to SMC). We acknowledge DST-FIST and UGC-Special Assistant Programme (SAP) - funded instrumentation facilities of Department of Biotechnology, Pondicherry University. Also we acknowledge the financial support by the Center of Applied Nanomedicine, National Cheng Kung University from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE), Taiwan. S.Y.L. is supported by a postdoctoral fellowship from Ministry of Science and Technology, Taiwan. References [1]

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Identification of novel quinoline inhibitor for EHMT2/G9a through virtual screening Highlights •

G9a, a lysine methyltransferase is a well-studied drug target for cancer therapy

•

CSV0C018875, quinoline based G9a inhibitor was identified through in silico studies

•

CSV0C018875 inhibits G9a in vitro and cell based assays with low toxicity

•

SMD simulation revealed the stronger binding of CSV0C018875 with G9a

Supporting information Identification of novel quinoline inhibitors for EHMT2/G9a through virtual screening M Ramya Chandar Charles,a,# Arun Mahesh,b,# Shu-yu Lin,c Hsing-Pang Hsieh,c Arunkumar Dhayalan,b,* and Mohane Selvaraj Coumara,* a

Centre for Bioinformatics, Pondicherry University, Kalapet, Puducherry 605014, India.

b

Department of Biotechnology, Pondicherry University, Kalapet, Puducherry - 605 014, India.

c

Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes,

35 Keyan Road, Zhunan, Miaoli County 350, Taiwan, ROC. #

Equaly contributed to this work

*Correspondence: [email protected]; [email protected]

Table S1. List of compounds making similar orientation as crystal structure inhibitors in docking with 3RJW crystals structure. S. No

Title

1.

CSV0A016876

glide energy -50.157

docking score -10.836

2.

CSV0A016969

-39.149

-9.691

3.

CSV0C011685

-39.522

-9.599

4.

CSV0D043260

-51.759

-9.479

5. 6.

A-366 (4NVQ-ligand) CSV0D043266

-46.452 -53.702

-9.245 -8.738

7.

UNC0638 (3RJW-ligand)

-66.886

-8.698

8.

CSV0D043256

-45.681

-8.532

9.

CSV0C011682

-41.346

-8.309

10.

CSV0D002483

-46.788

-8.148

11.

UNC0224 (3K5K-ligand)

-68.380

-7.546

12.

CSV0B020597

-37.133

-7.468

13.

CSV0D024743

-49.839

-6.987

14.

CSV0C013887

-50.717

-6.763

15.

CSV0D043262

-66.212

-6.744

16.

CSV0C019218

-37.301

-6.717

17.

CSV0D000458

-39.072

-6.712

18.

BPR0M000021

-49.797

-6.618

19.

CSV1C000771

-26.563

-6.579

Common compounds


Selected for testing




Cutoff




Cutoff - Compounds with better docking score than the cutoff value selected for G9a testing.

S2

Table S2. List of compounds making similar orientation as crystal structure inhibitors in docking with 3K5K crystal structures. S. No

Title

glide energy

docking Common score compounds -8.901


Selected for testing

1.

CSV0A016876

-79.539

2.

CSV0C018875

-50.796

-7.745

3.

CSV0A016969

-66.559

-7.678




4.

CSV0D043256

-72.950

-7.664




5.

CSV0D000552

-65.828

-7.059

NT

6.

CSV0C013887

-48.838

-6.995

NT

7.

CSV0D043260

-79.016

-6.921

8.

UNC0638 (3RJW-ligand)

-98.312

-6.843

9.

A-366 (4NVQ-ligand)

-47.395

-6.825

10.

CSV0C011691

-64.673

-6.444

11.

CSV1C000771

-43.772

-6.070

12.

CSV0D002484

-49.911

-6.060

13.

CSV0C011729

-45.826

-6.052

14.

CSV0C006903

-52.392

-5.997

15.

UNC0224 (3K5K-ligand)

-106.810

-5.978





Cutoff

Cutoff - Compounds with better docking score than the cutoff value selected for G9a testing; NT– not tested

S3

Table S3. 2D Tanimoto similarity* values of CSV0C018875 with reported G9a inhibitors. Compound

CSV0C018875

CSV0C018875 BIX-01294 UNC0224 UNC0321 UNC0638 UNC0642 A-366 CM-272

1.0 0.2525 0.2640 0.2671 0.2867 0.2794 0.1815 0.3324

BIX01294 0.2525 1.0 0.8258 0.8074 0.5486 0.5352 0.2318 0.3766

UNC0224

UNC0321

UNC0638

UNC0642

A-366

0.2640 0.8258 1.0 0.8571 0.6611 0.6440 0.2720 0.4308

0.2671 0.8074 0.8571 1.0 0.5813 0.5671 0.2278 0.3926

0.2867 0.5486 0.6611 0.5813 1.0 0.9697 0.2838 0.4883

0.2794 0.5352 0.6440 0.5671 0.9697 1.0 0.2777 0.4897

0.1815 0.2318 0.2720 0.2278 0.2838 0.2777 1.0 0.2968

CM272 0.3324 0.3766 0.4308 0.3926 0.4883 0.4897 0.2968 1.0

*Tanimoto similarity calculated using CDK library [1]. Tanimoto similarity value of 1.0 refers to highly similar compound and a value of 0 for highly dissimilar compounds.

S4

Table S4. H-bonds formed between G9a-inhibitor complexes during MD simulation. Top panel shows the running average plot of H-bonds between G9a and ligand during MD simulation. Bottom panel shows the number of frames the H-bonds appeared in the MD trajectory with specific residues of G9a.

Residues TYR_1067@OH ASP_1074@O ASP_1074@OD1 ASP_1074@OD2 ALA_1077@O ASP_1078@O ASP_1078@OD1 ASP_1078@OD2 ARG_1080@O GLU_1081@O ASP_1083@OD1 ASP_1083@OD2 LEU_1086@O ASP_1088@N TYR_1154@O ARG_1157@O ARG_1157@NH1 ARG_1157@NH2 ARG_1157@NE

BIX-01294 N1

N2

N3

N4

N5

UNC0683 N6

O1

O2

N1

N2

N3

N4

N5

CSV0C018875 O1

O2

N1

N2

O1 1481

7 845 1248 67 6 12

2125 1407

84 50

18 2 238 424

157 138

79 371 7654 2

11

13 2521

1

17

1 1 1

27 2

57 2 5

3427 39 16

2 3

S5

3

Table S5. Results of steered molecular dynamics of pulling ligands from G9a active site. Maximum force and complete dissociation time of the ligands are provided for three runs. Force values were mentioned in piconewton (pN) and time in nanoseconds (ns). BIX-01294 MD frame 100th ns

Average 90th ns

Average 80th ns

UNC0638

CSV0C018875

Run

Max. Force

Dissociation time

Max. Force

Dissociation time

Max. Force

Dissociation time

1 2 3

883.5 848 777.9 836.47±53.7 679.2 745.9 739.5 721.53±36.8 752.85 648.6 727.17 709.54±54.3 755.85

241 289 298 276±30.6 310 373 278 320.33±48.3 275 246 259 260±14.5 285.33

865.6 832.75 917.5 871.95±42.7 806.7 926.05 860.65 864.47±59.7 908.25 1031 975.41 971.55±61.4 902.66

317 342 403 354±44.2 318 302 323 314.33±10.9 352 328 421 367±48.2 345.11

933 952.05 932.82 939.29±11.0 921.5 867.2 982.4 923.7±57.6 832.55 856.9 938.7 876.05±55.6 913.03

361 365 332 352.67±18.0 387 372 436 398.33±33.4 311 350 336 332.33±19.7 361.11

1 2 3 1 2 3

Average Total average

S6

Table S6. Number of frames the H-bonds appeared during SMD of G9a-inhibitor complexes.

MD frame

100th ns

R u n

Acceptor

1

ASP_1083@OD2

2

3

BIX-01294 Donor

UNC0638 Donor

No. of Frames

No. of Frames

Acceptor

BIX-01294@N2

77

LEU_1086@O

UNC0638@N5

119

LEU_1086@O

CSV@N2

144

ASP_1074@OD2

BIX-01294@N6

13

ASP_1083@OD1

UNC0638@N5

100

CSV@N1

ARG_1157@NE

24

ASP_1083@OD1

BIX-01294@N2

4

UNC0638@O1

ARG_1157@NH1

11

CSV@N1

ARG_1157@NH2

11

ASP_1078@OD2

BIX-01294@N2

1

ASP_1083@O

UNC0638@N5

10

UNC0638@O1

ARG_1157@NH2

3

UNC0638@O2

ARG_1157@NH1

2

LEU_1086@O

UNC0638@N5

120

LEU_1086@O

CSV@N2

119

ASP_1083@OD1

CSV@N2

23

CSV@o1

LYS_1162@NZ

4

CSV@O1

LYS_1162@NZ

1

CSV@N1

ARG_1157@NH2

1

ASP_1083@OD2

CSV@N2

1

CSV@N1

ARG_1157@NE

1

ASP_1083@OD2

BIX-01294@N2

42

ARG_1080@O

BIX-01294@N4

3

No. of Frames

CSV0C018875 Acceptor Donor

ASP_1083@OD2

BIX-01294@N2

77

LEU_1086@O

UNC0638@N5

115

LEU_1086@O

CSV@N2

119

ASP_1078@OD1

BIX-01294@N2

16

ASP_1083@OD1

UNC0638@N5

94

CSV@O1

ARG_1157@NH1

1

ARG_1080@O

BIX-01294@N4

1

ASP_1078@OD2

UNC0638@N5

55

th

90 ns

1

2

3

80th ns

1

2

3

ASP_1078@OD1

UNC0638@N5

37

ASP_1074@OD1

BIX-01294@N6

96

LEU_1086@O

UNC0638@N5

129

LEU_1086@O

CSV@N2

117

ASP_1083@OD1

BIX-01294@N2

43

GLU_1081@OE1

UNC0638@N5

14

TYR_1165@OH

CSV@N2

23

BIX-01294@O1

LYS_1162@NZ

8

CSV@O1

LYS_1162@NZ

9

BIX-01294@O2

LYS_1162@NZ

3

CSV@O1

ASP_1088@N

1

ASP_1074@OD2

BIX-01294@N6

2

ASP_1074@OD1

BIX-01294@N6

123

LEU_1086@O

CSV@N2

88

ASP_1083@OD1

BIX-01294@N2

84

CSV@N2

ASP_1088@N

2

ASP_1074@OD2

BIX-01294@N6

32

SER_1084@O

CSV@N2

1

ASP_1074@OD1

BIX-01294@N6

126

LEU_1086@O

CSV@N2

73

ASP_1083@OD1

BIX-01294@N2

27

CSV@N2

ASP_1088@N

4

BIX-01294@O1

LYS_1162@NZ

4

SER_1084@O

CSV@N2

1

BIX-01294@O1

LYS_1162@NZ

4

CSV@O1

LYS_1162@NZ

1

BIX-01294@O1

LYS_1162@NZ

1

ASP_1074@OD2

BIX-01294@N6

1

LEU_1086@O

LEU_1086@O

UNC0638@N5

UNC0638@N5

105

138

LEU_1086@O

UNC0638@N5

117

TYR_1165@OH

CSV@N2

42

GLU_1081@OE2

UNC0638@N4

38

CSV@O1

LYS_1162@NZ

1

LEU_1086@O

UNC0638@N5

127

ASP_1083@OD1

UNC0638@N5

19

ASP_1083@OD2

UNC0638@N5

4

GLU_1081@O

UNC0638@N5

2

LEU_1086@O

UNC0638@N5

122

CSV@O1

LYS_1162@NZ

2

CSV@O1

LYS_1162@NZ

1

CSV@N2

TYR_1165@OH

1

S8

Figure S1. SDS PAGE run of G9a protein

Figure S2. Detailed interactions of inhibitors with G9a at different periods of SMD simulations. Interactions were calculate from the structures extracted at staring (0th ps), 100th ps and 300th ps S10

for BIX-01294 (A, B, C) UNC0638 (D, E, F) and CSV0C018875 (G, H, I) SMD simulations, respectively. At starting SMD, inhibitors makes interactions with the G9a, later while pulling out of the active site gradually loses interactions. BIX-01294 loses contacts with G9a very quickly in shorter time, whereas UNC0638 and CSV0C018875 maintains more hydrophobic interactions than BIX-01294 during the dissociation phase. Interactions with the underlined residues are found only with CSV0C018875 at the specific time period.

Figure S3. 1H-NMR of CSV0C018875

S11

Figure S4. LCMS of CSV0C018875

S12

Figure S5. LC-Purity of CSV0C018875 S13

Reference: [1]

C. Steinbeck, Y. Han, S. Kuhn, O. Horlacher, E. Luttmann, E. Willighagen, The Chemistry Development Kit (CDK): An open-source Java library for chemo- and bioinformatics, in: J. Chem. Inf. Comput. Sci., 2003: pp. 493–500. doi:10.1021/ci025584y.

S14

Identification of novel quinoline inhibitor for EHMT2/G9a through virtual screening Graphical abstract

Identification of novel quinoline inhibitor for EHMT2/G9a through virtual screening M Ramya Chandar Charles,a,# Arun Mahesh,b,# Shu-Yu Lin,c Hsing-Pang Hsieh,c Arunkumar Dhayalan,b,* Mohane Selvaraj Coumara,*

Declaration of interests  The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Corresponding Author: Mohane