Discovery of Selective Inhibitors Against EBNA1 via High
Throughput In Silico Virtual Screening
Ning Li1., Scott Thompson2., David C. Schultz2, Weiliang Zhu1, Hualiang Jiang1, Cheng Luo1*, Paul M.
1Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China, 2The
Wistar Institute, Philadelphia, Pennsylvania, United States of America
Background: Epstein-Barr Virus (EBV) latent infection is associated with several human malignancies and is a causal agent of
lymphoproliferative diseases during immunosuppression. While inhibitors of herpesvirus DNA polymerases, like gancyclovir,
reduce EBV lytic cycle infection, these treatments have limited efficacy for treating latent infection. EBNA1 is an EBV-
encoded DNA-binding protein required for viral genome maintenance during latent infection.
Methodology: Here, we report the identification of a new class of small molecules that inhibit EBNA1 DNA binding activity.
These compounds were identified by virtual screening of 90,000 low molecular mass compounds using computational
docking programs with the solved crystal structure of EBNA1. Four structurally related compounds were found to inhibit
EBNA1-DNA binding in biochemical assays with purified EBNA1 protein. Compounds had a range of 20–100 mM inhibition of
EBNA1 in fluorescence polarization assays and were further validated for inhibition using electrophoresis mobility shift
assays. These compounds exhibited no significant inhibition of an unrelated DNA binding protein. Three of these
compounds inhibited EBNA1 transcription activation function in cell-based assays and reduced EBV genome copy number
when incubated with a Burkitt lymphoma cell line.
Conclusions: These experiments provide a proof-of-principle that virtual screening can be used to identify specific inhibitors
of EBNA1 that may have potential for treatment of EBV latent infection.
Citation: Li N, Thompson S, Schultz DC, Zhu W, Jiang H, et al. (2010) Discovery of Selective Inhibitors Against EBNA1 via High Throughput In Silico Virtual
Screening. PLoS ONE 5(4): e10126. doi:10.1371/journal.pone.0010126
Editor: Thomas F. Schulz, Hannover Medical School, Germany
Received December 31, 2009; Accepted March 7, 2010; Published April 12, 2010
Copyright: ? 2010 Li et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was funded in part by grants from NIH (R01CA093606 and R21NS063906) to PML and the National Natural Science Foundation of China
(20972174), Shanghai Committee of Science and Technologyy grant (10410703900 and 08431900800) and the State Key Program of Basic Research of China grant
(2009CB918502) to CL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: Paul Lieberman has a competing interest as an officer (Founder/Owner and President) in a small biotechnology company called Vironika.
A provisional patent has been submitted based on this work. No funding from Vironika was used for this study. The authors confirm that this does not alter their
adherence to all the PLoS ONE policies on sharing data and materials.
* E-mail: firstname.lastname@example.org (PML); email@example.com (CL)
. These authors contributed equally to this work.
Epstein-Barr virus (EBV) is a carcinogenic cofactor for several
lymphoid and epithelial cell malignancies (reviewed in [1,2,3]).
EBV is associated with the majority of endemic forms of Burkitt’s
lymphoma and nasopharyngeal carcinomas (NPC). EBV is also
found in ,40% of all Hodgkin’s disease tumor biopsies, some
forms of gastric carcinoma, thyroid tumors, NK/T cell lymphoma,
and the majority of immunosuppression-associated non-Hodgkin’s
lymphomas and lymphoproliferative disease. Most EBV associated
tumors harbor the latent viral genome as a multicopy episome in
the nucleus of the transformed cells. During latent infection, EBV
does not produce progeny virions, but does express a limited set of
viral gene products that promote host-cell survival and prolifer-
ation. In proliferating cells, the maintenance of the latent viral
genome depends on the functions of the Epstein-Barr Nuclear
Antigen 1 (EBNA1) protein . EBNA1 is expressed in all types of
EBV latent infection found in proliferating cells and tumors.
EBNA1 is essential for the immortalization of primary B-
lymphocytes by EBV infection , and its inhibition by siRNA
depletion or by ectopic expression of dominant negative mutants
induce apoptosis in EBV-infected cells [6,7].
EBNA1 is an attractive candidate for targeting inhibition of
EBV latent infection. EBNA1 is consistently expressed in most, if
not all, EBV associated malignancies. EBNA1 is essential for
viral genome maintenance and for infected-cell survival [6,7].
Most importantly, EBNA1 is a viral-encoded protein that has well-
defined biochemical and structural properties. EBNA1 consists of
two major functional domains, a carboxy-terminal DNA binding
domain, and an amino-terminal chromosome tethering domain
[4,9]. The DNA binding domain is essential for interaction with
the viral origin of plasmid replication (OriP) . OriP consists of
a series of 30 bp repeats to which EBNA1 binds an 18 bp
palindromic-sequence as a homodimer [11,12]. The DNA binding
and dimerization interface have been solved by high resolution X-
ray crystallography in the apo- and DNA-bound forms [13,14].
While there are no known cellular homologues of EBNA1, the
three dimensional structure of EBNA1 resembles the overall
PLoS ONE | www.plosone.org1April 2010 | Volume 5 | Issue 4 | e10126
structure of human papillomavirus (HPV) E2 protein, which has
an analogous function to EBNA1 at the HPV origin of DNA
replication . Protein structure prediction programs suggest
that EBNA1 and E2 share structural folds similar to the Kaposi’s
Sarcoma-Associated Herpesvirus (KSHV) LANA protein, which
shares many functional properties with EBNA1, including DNA
binding and episome maintenance of KSHV oriP . These
observations suggest that EBNA1 is a member of a family of viral
origin binding proteins that have no apparent orthologue in the
human genome, and therefore may represent attractive targets for
inhibitors of viral latent replication and persistence.
Identification of small molecules that specifically inhibit protein-
DNA binding activity has had some success [16,17,18,19].
Because of the cost-inefficient and time-consuming process of
conventional drug discovery over the past decade, high through-
put virtual screening (HTVS) has emerged as an attractive and
complementary approach to traditional solution based HTS.
HTVS typically depends on the availability of a high-resolution
crystal structure of the protein target as a template for
computational screening. Over the years, HTVS has been applied
to the successful identifications of biologically active molecules
against targets such as HIV-1 protease, thymidylate, influenza
hemagglutinin, and parasitic proteases [20,21]. The availability of
crystal structure of the EBNA1/DNA complex presents to us
an opportunity to utilize the HTVS strategy. As a proof-of-
principle, we screened about 90,000 low-molecular-weight com-
pounds from a publicly available small molecule database using
the HTVS approach, and after two generations of optimization
from a primary inhibitor lead, we developed a novel series of
compounds with IC50values in twenty micro-molar range against
EBNA1. These results established our virtual screening protocol as
an effective screening strategy for the discovery of potent and
selective inhibitor of EBNA1, and provided a novel scaffold for
future design of more potent and specific EBNA1 inhibitors.
Results and Discussion
High throughout virtual screening procedure
The procedure for HTVS in this study is shown in Fig. 1.
Firstly, residues within a distance of 6 A˚ around the DNA
sequence (TGCTT) among the DNA of Epstein-Barr virus origin
binding protein/DNA complexes (EBNA1, PDB entry: 1B3T)
 were isolated for the construction of a grid for screening by
the use of the DOCK4.0 program . This grid was large
enough to include every residue of the EBNA1 DNA-binding
pocket. Next, to create a library of compounds for screening, we
selected a public database that contained a large number of small
molecule compounds that would be available for subsequent
solution screening at a nominal cost. To this end, we selected the
SPECS database that contained about 300,000 small-molecule
compounds. To refine the database further to include the
compounds that were likely to be soluble in an aqueous solution
and enable eventual testing in solution based assays, we filtered
the database for compounds with a log S value of greater than 24
by in-house software ZLogS, which resulted in a database of
around 90,000 small-molecule compounds. Then to screen these
compounds efficiently within a reasonable time, we initially used
DOCK4.0 , a docking program that had already been
successfully used for the identification of small molecule inhibitors
of the HIV-1 protease, thymidylate synthase, influenza hemag-
glutinin, and parasitic proteases , as the primary molecular
docking program to screen the small molecule database. The top
5000 hits that were generated from the energy scoring function of
DOCK4.0 were docked using three other docking programs that
employed different scoring functions. XScore  (version 1.2.1)
was used for calculating a binding score for a given protein-ligand
complex structure, SLIDE (version 2.3.1) [27,28] was used for the
calculation of hydrogen bonds and the hydrophobic complemen-
tarity while considering the flexibility of both protein and ligand,
and AutoDock3.0 was used for calculating the free energy of
binding. Specifically, the XScore program was first carried out on
the top 5000 candidate compounds that were generated from
DOCK4.0. The top 2000 compounds from XScore were then
selected for reevaluation by the use of the SLIDE scoring
function. The top 500 potential hits from SLIDE were finally
evaluated according to the free energy of binding with the
AutoDock3.0 program. According to their binding modes, free-
energy scores, and scaffold diversity, finally, 30 compounds from
15 manually classified groups were selected for experimental
validation. The 30 compounds were assayed by fluorescence
polarization (FP) and electrophoresis mobility shift assay (EMSA)
for physical inhibition of EBNA1-DNA binding (data not shown).
As a control for specificity, the compounds were rescreened for
there inhibition of an unrelated DNA binding protein, Zta, also
encoded by EBV. Zta is an EBV-encoded b-zip DNA binding
protein that bears no structural resemblance to EBNA1 and is
unlikely to be affected by EBNA1-specific inhibitors. Among the
30 candidates, four compounds were found to have selective
inhibitory activity for EBNA1 and not for Zta. The structure of
the four compounds, referred to as SC7, SC11, SC19, and SC27
are shown in Fig. 2.
Figure 1. Flow chart of virtual and experimental screening
strategy for discovering EBNA1 inhibitors. The EBNA1/DNA
crystal structure was computationally fitted into a 6 A˚grid containing
every residue of the EBNA1 DNA-binding pocket was used to dock a
library of compounds from the SPECS database. Compounds were
preselected for solubility in an aqueous solution using a log S value of
greater than 24. A database of ,90,000 small-molecule compounds
were then analyzed by one primary docking programs and three score
functions to calculate the free energy of binding. 5000 candidates were
then re-examined using Xscore, Slide, and AutoDock programs to select
30 top candidates. The top 30 compounds from 15 manually classified
groups were selected for experimental DNA binding and cell-based
Inhibitors of EBNA1
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Biochemical validation of EBNA1 Inhibitors Identified
through Virtual Screening
The four candidate compounds were further characterized for
their relative potency of inhibiting EBNA1-DNA binding using
both the FP and EMSA. EBNA1 DNA binding domain was
purified to near homogeneity and capable of binding a fluorescent
tagged DNA hairpin containing a consensus EBNA1 binding site
with ,50 nM affinity (data not shown). As a control for selectivity,
the same analysis was performed with purified Zta, and its cognate
fluorescent DNA probe. In the FP assay, SC7, SC11, and SC19
had IC50 ranges between 20–100 mM, while SC27 did not
perform well in the FP assay. However, SC27 showed highly
specific inhibition of EBNA1 in EMSA (Fig. 3D, lower right
panel), suggesting that the poor performance in FP may be due to
fluorescence interference properties or solution solubility prob-
lems. The EMSA analysis confirmed that each compound
inhibited EBNA1-DNA binding with an IC50 between 20–
100 mM, similar to that determined by FP. SC7, SC11, and
SC19 showed no significant inhibition of Zta-DNA binding in
either the FP assay or EMSA, suggesting that these compounds are
selective inhibitors of EBNA1-DNA binding function.
Inhibition of EBNA1 functions in cell-based assays
SC7, SC11, and SC19 were assayed for their ability to inhibit
EBNA1 in two cell-based assays. Transcription activation of the
EBV Cp promoter by EBNA1 is known to be essential for B-cell
immortalization . We therefore assayed the effect of
compounds to inhibit EBNA1 transcription activation of Cp using
a luciferase reporter-based assay in transiently transfected
HEK293T cells (Fig. 4). The luciferase reporter plasmid consisted
of a ,2 kb region of EBV containing both OriP and Cp fused
upstream of the luciferase gene. Cotransfection of this plasmid
with an EBNA1 expression plasmid produced a 4–5 fold increase
in luciferase activity relative to control expression vector lacking
EBNA1 (data not shown). Incubation of transfected cells with
control vehicle DMSO had no effect on EBNA1 transcription
activation. Incubation of transfected cells with 5 mM SC7, SC11,
or SC19 completely blocked EBNA1 transcription activation
(Fig. 4). As a control for specificity, the same compounds were
assayed for their inhibition of Zta transcription activation. Zta is a
potent transcription activator of the EBV BHLF1 promoter. We
therefore assayed these compounds for their effect on Zta
transactivation of BHLF1 promoter fused to luciferase reporter
gene. Cells incubated with 5 mM SC7 and S11 showed ,60%
inhibition of Zta transactivation, indicating that these compounds
were not highly selective inhibitors of EBNA1 transcription
function in vivo. In contrast, cells incubated with 5 mM SC19
had no detectable inhibitory effect on Zta transactivation, yet a
robust inhibition of EBNA1. This indicates that SC19 can
selectively inhibit EBNA1 transcription activation function in a
Elimination of EBV episomes
To further evaluate the ability of these compounds to inhibit the
EBNA1 function required for EBV genome replication, we assayed
their effect on EBV genome copy number in the Raji Burkitt
lymphoma cell line (Fig. 5). Raji cells typically contain ,100 copies
of the EBV genome per cell. Previous studies have demonstrated
that hydroxyurea (HU) can reduce the number of EBV episomes
in Burkitt lymphoma cell lines, including Raji cells. Therefore, we
assessed the effects of HU, SC7, SC11, and SC19 on EBV copy
number in Raji cells. Cells were treated with 10 mM SC7, SC11,
SC19 or with 100 mM HU for six days. The EBV genome copy
number was determined by real time PCR for EBV DNA (DS)
relative to cellular actin DNA. We found that HU treatment
caused ,50% reduction in EBV genome copy number. Treatment
with SC11 or SC19 caused a 75–90% reduction in EBV copy
number, while SC7 had no apparent effect (Fig. 5). These findings
suggest that SC11 and SC19 might be more effective than HU in
promoting loss of EBV genomes from latently infected cells.
Molecular docking interaction analysis
To understand the mode of inhibition of compounds binding
with DNA binding site of EBNA1, we docked the best two
inhibitors (SC7 and SC19, their inhibitory activity against EBNA1
is 23 and 49 mM, respectively) into the DNA binding site of
EBNA1 by using AutoDock3.0, shown in Fig. 6. As shown in
Fig. 6A, SC7 is modeled to bind the DNA-binding site of EBNA1
that forms two hydrogen bonds with the nitrogen of side chain of
Arg469 and one hydrogen bond with oxygen of side-chain of
Tyr518, respectively. In addition, the binding mode suggests that
extensive hydrophobic interactions are formed between SC7 and
hydrophobic region (R1 region in Fig. 7) near the residues Pro535
and Leu536. In particular, from the electrostatic surface contour
analysis shown in Fig. 6A, SC7 matches the binding site very well
inwhich the hydrophobic motif of SC7 interacts with hydrophobic
regions of EBNA1, while the negative-charged oxygen of sulfonyl
and bromide in 2-bromophenyl acetate motifs interact with the
positive charged region near the Arg469 (R3 region in Fig. 7). In
comparison with the EBNA1-DNA crystal structure, the SC7 is
well aligned with the T111, G112 and C113 of the DNA sequence
(shown in Fig. 6E). In particular, the sulfonyl motif mimics the
interaction with the receptor as the phosphate motif of G112 of
DNA sequence. In contrast to SC7, SC19 is modeled to bind to
the EBNA1 active site in a different orientation, which is
apparently due to the bulky phenyl group derivatization on the
benzamide motif (SC19) (Fig. 6C and D). In addition to extensive
hydrophobic interactions between EBNA1 and SC19 with residues
Lys514, Tyr518, Arg522, Leu536 and Leu554, SC19 also makes
three additional hydrogen bonding interactions with Arg469,
Lys514 and Tyr518 of EBNA1. Based on the interaction analysis
of SC7 and SC19 binding with EBNA1, the residue Arg469 and
Tyr518 may play crucial role in the maintaining the inhibitory
activity of inhibitor binding with EBNA1.
Figure 2. The chemical structure of four related compounds
identified by virtual screening that were validated for physical
inhibition of EBNA1-DNA binding.
Inhibitors of EBNA1
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Conclusions and Future Prospects
We have identified four small molecules as novel inhibitors
against EBNA1 by using a HTVS approach from a filtered small
molecule SPECS compound database that contains about 90,000
compounds. Among these novel inhibitors, compound SC7 was
found to inhibit the DNA binding activity of the EBNA1 protein in
FP assays with an IC50 value of 23 mM. On the basis of the
molecular docking of this compound to EBNA1, a fragment scaffold
(the scaffold listed in Fig. 6B) was hypothesized to be the functional
moiety for EBNA1 inhibition. Furthermore, the docking simulation
of SC7 and SC19 into the EBNA1 active site provides some
pharmacophore clues for future inhibitor optimization to increase
EBNA1 inhibitor potency and selectivity (Fig. 6 or 7). In particular,
compounds with modifications that extend the R1 position of the
phenyl group with hydrophobic motifs might enable compound
analogues to reach deeper into the EBNA1-binding pocket that
interacts with residue Pro535 and Leu536 of EBNA1. The
modification of bulky group at the R2 and R4 positions may clash
with the amino acid side-chain residues of the EBNA1 DNA binding
pocket, therefore changes at these positions may be limited to
relatively small substituents. In the R3 position, the substitution of a
bulky group, such as a phenyl, will likely be unfavorable for the
binding of the inhibitor to EBNA1. In contrast, hydrophilic groups
introduced at the R5 and R3 groups could mediate additional
hydrogen bonding interactions with the residues of EBNA1 protein
(Arg469 in R3 position, Gly472 and Tyr518 in R5 position) and
potential enhance the binding affinity of the inhibitors.
Our study demonstrates that an efficient and cost-effective virtual
screening procedure can be used to identify novel EBNA1 inhibitors
that also show considerable selectivity for EBNA1 over other
proteins. Moreover, the promising results that were obtained in this
study will serve as an excellent platform for the further development
of EBNA1 inhibitors with even greater potency and selectivity for
use as therapeutic agents against latent EBV infection.
Materials and Methods
The virtual screening strategy was shown in Fig. 1. The X-ray
crystal structure of the Epstein-Barr virus origin binding protein/
DNA complexes (EBNA1, PDB accession code 1B3T)  was
used as the target structure in this approach. The modified small
Figure 3. Physical inhibition of EBNA1-DNA binding assays. Candidate inhibitors SC7, SC11, SC19, and SC27 were assayed by fluorescence
polarization (FP) for inhibition of EBNA1-DNA binding (panel A) and for inhibition of Zta-DNA binding (panel B). IC50 values were calculated for each
isotherm. Inhibitor concentrations were diluted 2-fold from 833 to 7 mM for each compound. Inhibitors were also assayed using a secondary EMSA
assay to monitor EBNA1-DNA binding (panel C) or Zta-DNA binding (panel D) using the same concentrations of inhibitor compounds (two fold
dilutions from 833 to 7 mM) as that shown for FP assays in panels A and B, above.
Inhibitors of EBNA1
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molecular database containing approximately 90,000 molecules
for virtual screening was generated as a SPECS subset from the
Zinc databases (compounds are available from the SPECS
Company) with a predicted solubility filter by in-house
program ZLogS (log S.24). ZLogS (unpublished) was gifted
from Dr. MY Zheng in Drug Discovery and Design Center,
SIMM, Chinese Academy of Sciences. ZlogS performs solubility
prediction based on the generalized atom additive model and
stepwise multiple linear regression (SMLR). Eight putative
relationships between the atomic solvent assessable surface area,
electro-descriptors and atomic contribution of water solubility
The virtual screening was performed on SGI Origin3800
computer at the Shanghai Institute of Materia Medica. A heuristic
docking and consensus scoring strategy was used to evaluate the
results of the virtual screening. Specifically, we used DOCK4.0 as
the primary screening tool targeting at DNA binding site of the X-
ray crystal structure of EBNA1. Residues around the DNA at
radius of 6 A˚was isolated for the construction of the grid for
docking simulation. This radius was large enough to include all of
the residues that are involved in putative inhibitor site. During the
docking procedure, Kollman-all-atom charges were assigned to
the protein, and Geisterger-Hu ¨ckel charges assigned to the small
molecules in the SPECS database. Furthermore, the conforma-
tional flexibility of the molecules from the database was considered
during the docking simulations. We used 30 configurations per
ligand building a cycle and 50 maximum anchor orientations were
used in the anchor-first docking algorithm. After the protocol was
set up, the modified database was screened and top-5000
molecules were taken as the hits list for further analyses. These
molecules were re-ranked by Xscore (version 1.2.1) and top-
2000 molecules were taken as the hits list for the docking and
scoring mode of SLIDE (version 2.3.1)[27,28]. The binding
affinity of identified top-500 potential hits from SLIDE were
further evaluated by AutoDock3.0. Last, on the basis of the
results of these scoring functions, the top 200 molecules were
extracted and carefully considered for the receptor binding and
scaffold diversity. Finally, we purchased 30 available candidate
compounds from different scaffolds for the in vitro assay.
Score functions with Xscore, SLIDE and Autodock
In this study, the Xscore and SLIDE were performed as score
functions with default parameters. And last, the molecular docking
program AutoDock 3.0 was used for the automated molecular
docking simulations for the prediction of the binding affinity. The
docking scheme is summarized as follows. First, the receptor
molecule was checked for polar hydrogen and was assigned for
partial atomic charges. The PDBQS file was created, and the
atomic solvation parameters were also assigned. Second, a 3D
search grid was created by the use of AutoGrid algorithm to
evaluate the binding energies between the ligands and the EBNA1
receptors. Third, a series of the docking parameters were defined.
The atom types, generations and the run numbers for LGA
algorithm were properly assigned according to the requirement of
the Amber force field. The number of generations, energy
evaluations, and docking runs were set to 370,000, 1,500,000,
and 20, respectively. Kollman all-atom charges were assigned for
the EBNA1 receptors and Gasteiger-Marsili  charges were
Figure 4. Inhibition of EBNA1 transcription activation function in cell-based assays. Soluble compounds SC7, SC11, and SC19 were
assayed for their ability to inhibit either EBNA1 or Zta-dependent transcription activation in transfected 293T cells. Cells were transfected with vector
or EBNA1 expression plasmid and the OriP-Cp-Luciferase reporter plasmid in the presence of 5 mM SC7, SC11, SC19 or DMSO control. 100% inhibition
was equivalent to basal expression levels of OriP-Cp-Luc in the absence of ectopic EBNA1 expression. In parallel experiments, the same compounds
were also assayed for inhibition of Zta transcription activation of the BHLF1-Luciferase reporter plasmid. Percent inhibition of Zta is shown in grey.
Percent inhibition of EBNA1 is shown in black. Error bars represent standard deviation from the mean for at least three experimental replicates.
Inhibitors of EBNA1
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assigned for the ligands. Finally, the docked ligand-receptor
complexes were selected according to the criteria of interacting
energy combined with geometrical matching quality. These
complexes were used as the starting conformation for further
energetic minimization and geometrical optimization before the
final binding models were achieved.
All compounds used were ordered from SPECS company which
reported purities of over 90% for all compounds as analyzed by
LCMS. Compounds were stored as powder in a dessicator and
resuspended to 50 mM in DMSO immediately prior to use.
SPECS catalogue numbers are as follows: SC7: AG-690/
36423053; SC11: AG-690/36749014; SC19: AG-690/36535028;
The EBNA1 DNA binding domain (DBD) (aa 454–607) with a
hexa-histidine amino-terminal fusion protein was expressed in E. coli
and purified over Ni-NTA agarose according to manufacturers
recommendations (Qiagen). The protein was purified from four liters
of E. coli to generate ,20 mg of highly purified EBNA1 protein,
estimated to be .90% pure. Purified protein was then dialyzed into a
buffer consisting of 200 mM NaCl, 20 mM, Tris-HCl pH 7.4 and
20% Glycerol. Hexa-His tagged Zta was purified from E. coli to near
homogeneity, similar to EBNA1 protein. Purified Zta was dialyzed
into 500 mM NaCl, Tris-HCl pH 7.4 and 20% Glycerol.
FP Assay EBNA1
A reaction mix containing 200 mM NaCl, 20 mM Tris-Cl
pH 7.4, 1 mM DTT, 10 ug/mL BSA, 10 nM Cy5 59 modified
or ZTA (Cy5-CACTGACTCATTaatgagtcagtg binding site)
oligonucleotide hairpins (purchased from IDT) and 246 nM
EBNA1 DBD (aa 459–607) or 300 nM ZTA full length purified
recombinant protein was incubated for 20 minutes at room
temperature prior to dispensing (BioTek MicroFlo Select) 30 uL
to each well of a 384 well black opaque microtiter plate
containing the test compounds. Test plates were centrifuged
at 1656g prior to fluoresence polarizaration measurements in
an Envision Xciter multilable plate reader (Perkin Elmer) using
a Cy5 FP 620 excitation and Cy5 FP P/S-pol 688 emission
An EMSA reaction buffer was prepared containing 20%
Glycerol, 200 mM NaCl, 20 mM Tris-Cl pH 7.4, 1 mM DTT,
10 ug/mL BSA, 10 nM Cy5 oligonucleotide probe and with or
without 246 nM EBNA1 DBD or 300 nM Zta full length
purified recombinant protein. This solution was incubated for
20 minutes at room temperature to ensure binding. 30 uL of this
solution was dispensed to eppendorf tubes containing 0.5 uL of
a test compound in DMSO and mixed. Samples were then
loaded onto a 6% polyacrylamide gel in 1/2X Tris-Borate
buffer and electrophoresed for 90 min at 170 V. The gel was
then scanned for flouresence using at Typhoon Imager (GE
For initial screening 2 ul of test compounds resuspended in
DMSO were plated in triplicate wells in a black opaque Optiplate
(Perkin Elmer) at a concentration of 50 mM to achieve a final
Figure 5. Elimination of EBV genomes from Burkitt lymphoma cell lines. EBV-positive Raji Burkitt lymphoma cell lines were treated with
10 mM SC7, SC11, or SC19 or DMSO control for six days. EBV genome copy number was determined by quantitative real-time PCR analysis of EBV DNA
(DS) relative to cellular DNA (actin). Error bars represent standard deviation from the mean for at least three experimental replicates.
Inhibitors of EBNA1
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concentration of 3.33 mM when resuspended in 30 uL of
reaction solution. The plate was assayed using the FP assay
To determine IC50s, an 11- point series of 2-fold dilutions in
DMSO was performed in duplicate starting at an initial
concentration of 50 mM using a Janus Verispan (Perkin Elmer)
to create a master plate. From this master plate 0.5 uL was
transfered to black opaque 384 well Optiplate (Perkin Elmer) using
a Janus MDT (Perkin Elmer) or to microfuge tubes by hand. The
plate or microfuge tubes were assayed using the FP and EMSA
protocols described above. IC50 plots were generated by analyzing
the binding of EBNA1 or Zta with inhibitor compounds ranging
from 833 to 7 uM final concentrations following two fold dilutions
(specifically 833, 417, 208, 104, 52, 26, 13, 7, and 0 mM). The data
was calculated as percentage of EBNA1 binding activity and then
plotted versus the log of the concentration of inhibitor. Using
Figure 6. Docking simulation of two best hits (SC7 and SC19) in the EBNA1 site. (A) Interactions of SC7 with the EBNA1 binding Pocket; (B)
Interaction analysis between SC7 and EBNA1 calculated by LIGPLOT program; (C) Interactions of SC19 with the EBNA1 binding Pocket; (D) Interaction
analysis between SC19 and EBNA1 calculated by LIGPLOT program; (E) The comparison between the binding mode of SC7/EBNA1 and DNA/EBNA1
crystal complex structure, SC7 is shown in yellow stick and DNA is shown in magenta stick.
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GraphPad Prism 5.0 software the plotted data was fit with a Hill-
Slope dose-response curve to calculate the relative IC50.
Raji EBV Genome Copy Number Assay
56106cells/ml in RPMI media supplemented with 10% FBS
and 10 mM Streptomycin and 10 mm Penicillin. Test com-
pounds were added to achieve a final concentration of 10 uM.
Cells were grown at 37uC for three days and then passaged 1:10
into fresh media with the same concentration of drug. After a
second 3-day incubation cells were harvested and the DNA was
isolated using ChIP Lysis Buffer followed by sonication,
phenol:chloroform extraction, and ethanol precipitation. Rela-
tive EBV DNA copy number was quantified by real-time PCR
with primers for cellular actin and the EBV dyad-symmetry
region, as described previously .
fromATCC) weregrown at
EBNA1 Transcription Activation Assay
HEK293T cells (purchased from ATCC) were seeded in 24-well
plates at a density of 50,000 cells/well in DMEM media with 10%
FBS. Following an 18 hr incubation at 37uC, cells were transfected
using 2 ml of lipofectamine with 0.4 ug/well of a pCMV-FLAG-
EBNA1, pCMV-FLAG-ZTA (N362) or a control pCMV-FLAG
vector and 0.2 ug/well of either a Cp-Luciferase (EBNA1-
reporter) or a HP-Luciferase (Zta-reporter) plasmid. All samples
were cotransfected with 100 ng of Renilla expression vector as an
internal control for transfection efficiency. After 6 hrs the
transfection media was replaced and test compounds were added
to achieve a final concentration of 5 uM. Cells were incubated at
37uC for 48 hrs and then harvested. Cells were lysed and prepared
for analysis using the Promega Dual Reporter system and
luminescence was measured using a Perkin Elmer Wallac Victor2
1420 Multilabel reader.
We thank L. Frappier (University of Toronto, Canada) for the generous gift
of EBNA1 protein expression constructs and Cecilia Borestro ¨m and Lars
Rhymo for a Cp-Luciferase reporter plasmid. We thank the Wistar
Institute Cancer Center Protein Expression, Libraries and Molecular
Screening Facility. We also thank Dr. MY Zheng (Shanghai Institute of
Materia Medica, China) for the providing ZLogS program for the
prediction of compounds solubility.
Conceived and designed the experiments: ST CL PML. Performed the
experiments: NL ST DCS WZ HJ CL. Analyzed the data: NL ST DCS
WZ HJ CL PML. Contributed reagents/materials/analysis tools: DCS HJ
CL. Wrote the paper: CL PML.
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