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Reaching beyond

aDivision of Biophysical Chemistry, Lund U

Sweden. E-mail: soumendranath.bhakat@bpbKU Leuven – University of Leuven, Departme

Institute for Medical Research, Laboratory

Leuven, Belgium. E-mail: johan.neyts@regacDepartment of Pharmaceutical Sciences and

Mesra-835215, India. E-mail: venkatesanj@

† Electronic supplementary informa10.1039/c5ra14469h

Cite this: RSC Adv., 2015, 5, 85938

Received 21st July 2015Accepted 5th October 2015

DOI: 10.1039/c5ra14469h

www.rsc.org/advances

85938 | RSC Adv., 2015, 5, 85938–859

HIV/HCV: nelfinavir as a potentialstarting point for broad-spectrum proteaseinhibitors against dengue and chikungunya virus†

Soumendranath Bhakat,*a Leen Delang,b Suzanne Kaptein,b Johan Neyts,*b

Pieter Leyssenb and Venkatesan Jayaprakash*c

Drug repurposing or re-profiling has become an effective strategy to identify novel indications for

already-approved drugs. In this study, peptidomimetic FDA-approved HIV/HCV inhibitors were

explored for their potential to be repurposed for the inhibition of the replication of dengue (DENV)

and chikungunya virus (CHIKV) by targeting the NS2B-NS3 and NSP2 protease, respectively.

MM/GBSA-based binding free energy results put nelfinavir forward as a potential inhibitor of both

dengue and chikungunya virus, which subsequently was further explored in a virus-cell-based assay

for both viruses. Nelfinavir showed modest antiviral activity against CHIKV (EC50 ¼ 14 � 1 mM and

a selectivity index of 1.6) and was slightly more active against DENV-2 (EC50 ¼ 3.5 � 0.4 mM and

a selectivity index of 4.6). Even though the antiviral potency was limited, the fact that some activity

was observed in these assays made it worthwhile exploring the potential and properties of nelfinavir as

a stepping-stone compound: a more detailed computational analysis was performed to understand

the binding mode, interaction, hydrogen bond distance, occupancy and minimum pharmacophoric

features. The comprehensive data set that resulted from these analyses may prove to be useful for the

development of novel DENV and CHIKV protease inhibitors.

1. Introduction

The discovery and development of novel chemical entities fromscratch into a drug for clinical use is a time- and money-consuming task.1–3 Therefore, there is a lot of truth in thefamous quote by Nobel laureate James Black: “The most fruitfulbasis of the discovery of a new drug is to start with an old drug”.1

Taking these words to heart, there is still a lot of potential in themany compounds that are currently on the market and forwhich it is still unknown how they exactly elicit their benecialeffects. Furthermore, even for drugs with a known mechanism,it still makes sense to explore their versatility. Antiviral drugdevelopment for neglected tropical diseases is considered to bechallenging because of the low market value, in spite of theincreasing need.4–6 Drug repositioning or re-proling7–10 may bean attractive and effective process to unlock the clinicalpotential of established molecules for the treatment of

niversity, P.O. Box 124, SE-22100 Lund,

c.lu.se

nt of Microbiology and Immunology, Rega

of Virology and Chemotherapy, B-3000

.kuleuven.be

Technology, Birla Institute of Technology,

bitmesra.ac.in

tion (ESI) available. See DOI:

49

neglected tropical diseases such as dengue (DENV) and chi-kungunya virus (CHIKV).11–14

Dengue and chikungunya virus are the two most prevalenttropical mosquito-borne diseases that affect humans15,16. Caseshave even been reported on the concurrent transmission ofboth viruses amongst travelers.15 DENV (genus Flavivirus, familyFlaviviridae) is endemic in more than 100 countries with anaverage annual global incidence of 390 million cases, of whicharound 96 million develop dengue disease (Bhatt et al., 2013(ref. 17)). In general, DENV infection follows a subclinicalcourse that is characterized by non-specic symptoms.However, a second infection with any of the other four DENVserotypes is strongly correlated with the clinically more severedengue hemorrhagic fever (DHF) and dengue shock syndrome(DSS).18,19 Various vaccine development programs are alreadyongoing for several years,20,21 but this proves to be quite chal-lenging due to the link between secondary infection and theunderlying mechanism of DHF/DSS, i.e. antibody-dependentenhancement of infection. Patients those who suffer fromDENV disease can only be offered symptomatic treatment andintensive care.18 CHIKV belongs to the Alphavirus genus of theTogaviridae family.22,23 This viral infection is mostly character-ized by acute and chronic articular manifestations. AlthoughCHIKV infection is rarely fatal, the disease evolves intoa chronic stage in �50% of the infected patients and is char-acterized by persistent disabling polyarthritis that can severely

This journal is © The Royal Society of Chemistry 2015

Fig. 1 (a) The active site region of the DENV NS2B-NS3 protease is delineated in red. (b) The catalytic triad of the DENV NS2B-NS3 proteaseconsists of His51 (B), Asp75 (A) and Ser135 (C). The ligand-bound closed conformation of the dengueNS2B-NS3 protease (PDB: 3U1I) was used tofathom the position of the active site and catalytic triad.

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incapacitate the patient for weeks up to several years beyond theacute stage.24 Despite its wide spread and high morbidity, at themoment, there is no approved vaccine or antiviral treatmentavailable.22 The administration of analgesics, antipyretics, andanti-inammatory agents is the only way to increase the comfortof the patient.

For viruses, the non-structural (NS) viral proteins areattractive targets for the design of drug-like molecules.15 A lot ofinformation, like the crystal structure, is available for proteases,which, for other viruses, has already proven to facilitate thedevelopment of peptidomimetic inhibitors. The hydrophobicNS2B part is essential for the activation of the DENV NS3, whichcontains the catalytic triad His51, Asp75 and Ser135 within itsN-terminal region (Fig. 1). For CHIKV, NSP2 (Fig. 2), whichcarries three catalytic cysteine residues (Cys1233, Cys1274 and

Fig. 2 The active site region of the CHIKV NSP2 protease (PDB: 3TRK)is delineated in red. The conformation of the active site residues (inred) was deduced by running SiteHound and MetaPocket web servers(see ESI†).

This journal is © The Royal Society of Chemistry 2015

Cys1290) in its C-terminal region as well as four histidine resi-dues (His1222, His1228, His1229 and His136), is also a poten-tial target for the development of peptidomimetic inhibitors.15,22

The HIV/HCV protease inhibitors25–27 (Fig. 3), benchmarkexamples of peptidomimetic inhibitors, target the enzymaticactivity of the respective viral proteases. Building on thisknowledge, extensive studies have been performed to developpeptidomimetic inhibitors that target the DENV NS2B-NS3(Fig. 5) or CHIKV NSP2 protease (Fig. 4). Because all theseinhibitors share common structural features (Fig. 6), itprompted us to explore whether HIV/HCV protease inhibitorscould possibly be re-purposed for the inhibition of the replica-tion of DENV and CHIKV.

In this report, computer-aided drug design (CADD) andenhanced molecular modeling techniques were used to inves-tigate whether HIV/HCV protease inhibitors that are already onthe market could have the potential to inhibit the replication ofDENV and CHIKV by exploration of their capacity to bind to theviral NS2B-NS3 or NSP2 protease, respectively. In parallel, theirbiological potency was evaluated in virus-cell-based assays andwas correlated with the in silico results.

2. Materials and methods2.1. Molecular modeling study

The crystal structure of the DENV NS2B-NS3 protease in itsligand bound conformation (PDB: 3U1I)28 and the CHIKV NSP2protease (PDB: 3TRK)29 was obtained from the protein databank. The closed conformation of the DENV NS2B-NS3 subunit(PDB: 3U1I)28 was preferred over the open conformation withoutligand (PDB: 2FOM)30 as the protease is presumed to remain ina closed conformation when bound to an inhibitor. The struc-tures of the HIV/HCV protease inhibitors that were used in thisstudy were procured from Chemspider database31 and down-loaded in MOL2 format. The receptor and ligands wereprepared as mentioned previous by Maharaj et al.32 Subse-quently, processed ligands were docked in the active site of theDENV NS2B-NS3 and CHIKV NSP2 protease using Autodock

RSC Adv., 2015, 5, 85938–85949 | 85939

Fig. 3 The 2D structures of representative HIV/HCV protease inhibitors that were used in this drug repurposing study. A, B, C, D, E, F, G, H and Irepresents, respectively, lopinavir (LPV), nelfinavir (NFV), amprenavir (AMP), atazanavir (ATV), indinavir (IDV), ritonavir (RTV), saquinavir (SQV),telaprevir (TPV) and darunavir (DRV).

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Vina.33 The top docked conformations were generated usingViewDock34 plugin integrated with Chimera.35

Molecular docking-based binding affinity calculation oenleads to artifacts. Therefore, further molecular dynamics anal-ysis was used for further renement. Molecular dynamics-basedMM/GBSA calculation36–40 has proven to be an effective tool to

Fig. 4 2D representation of the structure (A–D) of some previously-repoof two CHIKV NSP2 inhibitors as predicted in silico by Rashad et al.22

85940 | RSC Adv., 2015, 5, 85938–85949

re-rank protein–inhibitor binding affinity. Therefore, moleculardynamics based MM/GBSA rescoring36,41–43 was used to preciselyrank the HIV/HCV inhibitors against both target enzymes.

All molecular dynamics simulations were performed usingthe GPU version of the PMEMD engine provided with Amber14 (ref. 44) as described by Bhakat et al.45 The H++ server

rted CHIKV NSP2 inhibitors. A and D represent the chemical structures

This journal is © The Royal Society of Chemistry 2015

Fig. 5 Chemical structures of some previously-reported DENV NS2B-NS3 protease inhibitors. (A) R, R1 are the position of substitutions asreported by Nitsche et al.;55 (B) one of the anilide reported by Zhou et al.;56 (C) one of the promising NS2B-NS3 inhibitors reported by Yildiz et al.;57

(D) one of the potent DENV NS2B-NS3 inhibitor reported by Ganesh et al.58

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(http://biophysics.cs.vt.edu/H++) was used to assign correctprotonation states in case of all the systems prior to systempreparation. In brief, the ligands were parameterized usingGAFF force eld, whereas the protein systems were described

Fig. 6 The common peptidomimetic chemical similarity among HIV/HCinspired the repositioning concept.

This journal is © The Royal Society of Chemistry 2015

using FF99SB force eld integrated with Amber 14. The leapmodule integrated with Amber 14 was used to add missinghydrogen atoms and heavy atoms as well as counter ions toneutralize the systems. All the systems were immersed in

V inhibitors, DENV NS2B-NS3 inhibitor/s and CHIKV NSP2 inhibitor/s

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a TIP3P water box so that no atom was within 10 A of any boxedge. Long-range columbic interactions were treated usingparticle mesh Ewald (PME) implemented in Amber 14. Theprepared systems were then subjected to different stages e.g.minimizations, heating and equilibration before proceedingto production runs as described by Bhakat et al.45 Finally,a 30 ns explicit solvent molecular dynamics simulation wasperformed for all the systems using an NPT ensemble witha target pressure set at 1 bar and constant pressure couplingof 2 ps.

The molecular dynamics trajectories were analyzed usingPTRAJ and CPPTRAJ modules46 integrated with Amber 14.Visualization was carried out using VMD47 and Chimera.35

MM/GBSA-based binding energy was calculated usinga singular trajectory approach taking in account 1000 frameswith a regular interval of 30 ps.45 The following set of equationsdescribes the calculation of binding free energy.

DGbind ¼ Gcomplex � Greceptor � Gligand (1)

DGbind ¼ Egas + Gsol � TDS (2)

Egas ¼ Eint + EVdW + Eele (3)

Gsol ¼ GGB + GSA (4)

GSA ¼ gSASA (5)

The notations of these parameters were described in detailby Bhakat et al.45

2.2. DENV and CHIKV cell-based assay

2.2.1. Cells and virus strains. CHIKV Indian Ocean strain899 (Genbank FJ959103.1) was generously provided by Prof. S.Gunther (Bernhard Nocht Institute for Tropical Medicine,Hamburg, Germany). CHIKV was propagated in African greenmonkey kidney cells [Vero cells (ATCC CCL-81)]. Vero-B cellswere maintained in cell growth medium composed ofminimum essential medium (MEM Rega-3, Gibco, Belgium)supplemented with 10% Fetal Bovine Serum (FBS, Integro, TheNetherlands), 1% L-glutamine (Gibco), and 1% sodium bicar-bonate (Gibco). The antiviral assays were performed in assaymedium, which is the respective cell growth medium supple-mented with 2% FBS (instead of 10%). All cell cultures weremaintained at 37 �C in an atmosphere of 5% CO2 and 95–99%humidity.

DENV serotype 2 strain New Guinea C (DENV-2 NGC) waskindly provided by Dr V. Deubel (formerly at Institute Pasteur,Lyon, France). DENV was propagated in C6/36 mosquito cells(from Aedes albopictus; ATCC CCL-1660) at 28 �C in Leibovitz'sL-15 medium (Life Technologies, cat no. 11415049) supple-mented with 10% FBS, 1% non-essential amino acids (LifeTechnologies, cat no. 11140035), 1% HEPES buffer (Life Tech-nologies, cat no. 15630056) and 1% penicillin (100 U ml�1)/streptomycin (100 mg ml�1) solution. Antiviral assays usingDENV were performed on Vero-B cells (obtained from the

85942 | RSC Adv., 2015, 5, 85938–85949

European Collection of Cell Cultures) using the same assaymedium as was described for CHIKV.

2.2.2. Chikungunya virus CPE reduction assay. CHIKVcytopathic effect (CPE) reduction assays were performed asdescribed before (Delang et al., 2014 (ref. 48)). In brief, Vero-Bcells were seeded in 96-well tissue culture plates (Becton Dick-inson, Aalst, Belgium) at a density of 2.5 � 104 cells per well in100 ml assay medium and were allowed to adhere overnight.Next, a compound dilution series was prepared in the mediumon top of the cells aer which the cultures were infected with0.01 MOI of CHIKV 899 inoculum in 100 ml assay medium. Onday 5 post-infection (p.i.), the plates were processed using theMTS/PMS method as described by the manufacturer (Promega,The Netherlands). The 50% effective concentration (EC50),which is dened as the concentration of compound that isrequired to inhibit viral RNA replication by 50%, was deter-mined using logarithmic interpolation. Potential cytotoxic/cytostatic effect of the compound was quantied in unin-fected cells also by means of the MTS/PMS method. The 50%cytotoxic concentration (CC50; i.e., the concentration thatreduces the overall metabolic activity of the cells by 50%) wascalculated using logarithmic interpolation. All assay wells werechecked microscopically for minor signs of virus-induced CPEor alterations of host cell or monolayer morphology that mayhave been caused by the compound.

2.2.3. Dengue virus yield reduction assay. Vero-B cells (5 �104) were seeded in 96-well plates. One day later, medium wasreplaced by 100 ml assay medium containing 100 CCID50 (50%cell culture infectious doses) of DENV-2 and incubated for2 hours, aer which the cell monolayer was washed 3 times withassay medium to remove non-adsorbed virus. Cells were furthercultivated in 200 ml fresh assay medium containing 2-fold serialdilutions of the compounds (50–0.20 mg ml�1) for 4 days.Supernatant was harvested and viral RNA load was determinedby real-time quantitative RT-PCR, as previously described(Kaptein et al., 2010 (ref. 49)). The EC50 value, which is denedas the compound concentration that is required to inhibit viralRNA replication by 50%, was determined using logarithmicinterpolation. Potential cytotoxic/cytostatic effects of thecompounds were evaluated in uninfected cells using theMTS/PMS method similarly as was described for CHIKV.

3. Results and discussions3.1. Insights from MM/GBSA-based rescoring and the virus-cell-based assays

From the docking studies, it could be derived that all theselected HIV/HCV inhibitors are able to physically bind into theactive site of DENV NS2B-NS3 as well as that of the CHIKV NSP2(Fig. 7). To validate the docking protocol, the peptide-likeinhibitor complexed with DENV NS2B-NS3 protease (PDB:3U1I28) was extracted in the conguration as it was bound andwas re-docked into the active site of DENV serine protease(details described in ESI†). Fig. 7 highlights the binding modeof all HIV/HCV inhibitors inside the active site of DENVNS2B-NS3 protease and CHIKV NSP2, which also highlights thepreciseness of the docking protocol used in this study.

This journal is © The Royal Society of Chemistry 2015

Fig. 7 Superimposed docked conformations of HIV/HCV inhibitorsused in this study within the active site of DENV NS2B-NS3 protease(PDB: 3U1I) and CHIKV NSP2 (PDB: 3TRK).

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Subsequently, the docked HIV/HCV protease inhibitors weresubjected to molecular dynamics and post-dynamicsMM/GBSA-based binding free-energy analysis to understandthe binding affinity of these HIV/HCV inhibitors in the activesite of the DENV NS2B-NS3 and CHIKV NSP2 protease. Table 1lists the MM/GBSA-based scoring prole of the respectiveinhibitors. The energies that were derived from differentbinding free-energy components such as electrostatic, van derWaals (VdW) contributions were comparatively higher in case ofnelnavir when compared to the other ligands, and this forboth proteases. An interesting observation in all cases was thatcontributions coming from VdW components are signicantlyhigher than those of electrostatic components, which signiesthat VdW interactions are the main driving force behind thebinding of HIV/HCV inhibitors into the active site of the DENVNS2B-NS3 and CHIKV NSP2 protease.

Table 1 MM/GBSA based binding free energy profile in comparison withstudya

Ligand EVdW Eelect Ggas

AMP �29.6529 � 0.3262{ 0.0619 � 0.1230{ �29.5911 � 0�22.4738 � 0.3892* �1.9473 � 0.2074* �29.7597 � 0

ATV �38.0980 � 0.2978{ �5.2609 � 0.2709{ �43.3584 � 0�24.0476 � 0.6403* �3.7475 � 0.6056* 36.7568 � 0

RTV �53.2588 � 0.2107{ �2.6859 � 0.1617{ �45.9456 � 0�23.9486 � 0.2011* �3.8793 � 0.3810* �35.8369 � 0

LPV �28.9049 � 0.5113{ �8.9503 � 0.2415{ �30.6537 � 0�34.0582 � 0.3940* �4.3948 � 0.2048* �32.8653 � 0

DRV �32.5832 � 0.3492{ �6.5005 � 0.3255{ �39.0837 � 0�27.8572 � 0.4036* �2.7578 � 0.9063* �37.3605 � 0

IDV �33.9221 � 0.5955{ �1.6321 � 0.9335{ �28.7214 � 1�22.8304 � 0.2907* �1.3875 � 0.2038* �28.8467 � 0

SQV �38.2987 � 0.1778{ �15.5666 � 0.5111{ �25.9531 � 0�28.7948 � 0.7207* �3.4743 � 0.6749* �30.9587 � 0

NFV �47.7996 � 0.2034{ �12.1653 � 0.5720{ �29.6342 � 0�37.8567 � 0.2920* �6.4839 � 0.2841* �30.2874 � 0

TPV �41.3499 � 0.2826{ �15.1257 � 0.0990{ �42.4706 � 0�26.8658 � 0.0637* �4.8047 � 0.6862* �36.7490 � 0

a { Indicates ligands complexed with DENV NS2B-NS3 (PDB: 3U1I) where

This journal is © The Royal Society of Chemistry 2015

To explore whether the in silico results are predictive forantiviral activity against the respective viruses, the effect of theHIV/HCV protease inhibitors was evaluated in in vitro virus-cell-based assays with DENV and CHIKV. As shown in Table2, most HIV/HCV protease inhibitors did not inhibit thereplication of CHIKV. Only lopinavir and nelnavir showeda modest antiviral effect (Fig. 8A). None of the compoundsfully inhibited virus-induced cytopathic effects and the anti-viral activity seems to be associated with an adverse effect onthe host cell (MTS cytotoxicity assay and microscopic evalua-tion). Likewise, only two out of the nine HIV/HCV proteaseinhibitors showed some antiviral activity against DENV-2(Table 2, Fig. 8B). The antiviral activity of ritonavir is clearlyassociated with an adverse effect on the host cell, while theantiviral effect of nelnavir against DENV-2 was a bit morepronounced with an EC50 value of 3.5 � 0.4 mM and a selec-tivity index (SI) of 4.6 (SI ¼ CC50/EC50). In general, the antiviraleffect of NFV on DENV-2 replication was better compared tofew previously reported DENV inhibitors.15,50,51

It was interesting to observe that nelnavir, the compoundwhich was found to be the most promising compound in the insilico study, also showed some antiviral activity against bothviruses in cell culture, (Table 2). It is also necessary to mentionthat all HIV/HCV inhibitors displayed a better binding freeenergy prole in complex with DENV NS2B/NS3 protease ascompared to CHIKV NSP2, which can be correlated with slightlybetter anti-DENV as compared to anti-CHIKV activity. A moredetailed modeling analysis of nelnavir bound in both prote-ases (see Section 3.2) provided additional support that, eventhough the antiviral effect in cell culture was rather modest,nelnavir showed some interesting features to further exploreits properties as a stepping-stone towards the development ofinhibitors that could inhibit both DENV and CHIKV replication.

docking score for all re-profiled HIV/HCV inhibitors presented in this

Gsolv DGbind Docking score

.3217{ 6.4800 � 0.1219{ �23.1111 � 0.2546{ �7.3{

.5057* 12.1264 � 0.2073* �12.2947 � 0.2037* �6.3*

.4630{ 14.3965 � 0.2768{ �22.9619 � 0.2981{ �7.2{

.5067* 13.5103 � 0.3604* �14.2848 � 0.2057* �6.2*

.3144{ 13.9597 � 0.1536{ �31.9859 � 0.2457{ �8.6{

.6037* 13.6207 � 0.4903 �14.2072 � 0.3803 �6.4*

.6095{ 9.5843 � 0.2877{ �28.2694 � 0.4378{ �8.4{

.3803* 15.9674 � 0.2047* �22.4856 � 0.2710* �6.2*

.5231{ 16.3381 � 0.3074{ �22.7456 � 0.2876{ �7.5{

.5063* 18.0774 � 0.8057* �12.5376 � 0.7485* �6.6*

.2058{ 12.1607 � 0.8491{ �23.3925 � 0.8491{ �7.1{

.7073* 11.8232 � 0.4063 �12.3947 � 0.1078* �6.6*

.5245{ 25.4092 � 0.4550{ �28.4561 � 0.1639{ �7.6{

.7064* 19.4018 � 0.6539* �12.8673 � 0.3755* �6.6*

.5895{ 25.9687 � 0.5257{ �33.9962 � 0.2118{ �8.9{

.3842* 19.4812 � 0.4201* �24.8594 � 0.1047* �6.7*

.3000{ 28.2651 � 0.1136{ �28.2055 � 0.2803{ �7.6{

.6402* 14.1308 � 0.8473* �17.5397 � 0.2104* �6.2*

as * stands for ligands complexed with CHIKV NSP2 (PDB: 3TRK).

RSC Adv., 2015, 5, 85938–85949 | 85943

Table 2 Antiviral activity of HIV/HCV protease inhibitors against DENV and CHIKV

Protease inhibitors Anti-DENV activity EC50 (mM) CC50 (mM) Anti-CHIKV activity EC50 (mM) CC50 (mM)

Lopinavir 42 � 20 47 � 23 32 � 9 44 � 12Nelnavir 3.5 � 0.4 16 � 0.4 14 � 1 22 � 6Amprenavir >49 >49 >99 >99Atazanavir >71 >71 >71 >71Indinavir >41 >41 >82 >82Ritonavir 22 � 4.4 46 � 27 >69 53Saquinavir 32 � 7.7 >37 >75 54Darunavir >84 >84 >84 >84Telaprevir 43 � 10 >50 >50 >50

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3.2. Molecular analysis of the nelnavir–proteaseinteraction

3.2.1. The nelnavir/DENV NS2B-NS3 interaction. A moredetailed analysis of the interaction of nelnavir with the activesite of the DENV NS2B-NS3 protease delineates a number of

Fig. 8 Dose response curves of the antiviral effect (black bars) and thchikungunya virus CPE reduction assay and (B) lopinavir, nelfinavir and r

85944 | RSC Adv., 2015, 5, 85938–85949

crucial residues involved in the interaction (Fig. 9). Themajorityof the interactions are hydrophobic and polar type interactions.Also, a per-residue footprint analysis conrmed that van derWaals energy is the main driving force for binding, which isexemplied by the high VdW values in binding free-energy(Fig. 9C). The position of three catalytic site residues e.g.

e cytotoxic effect (white circles) of (A) lopinavir and nelfinavir in theitonavir in the dengue virus yield reduction assay.

This journal is © The Royal Society of Chemistry 2015

Fig. 9 (A) Ligand interactionmap of NFV bound in the active site of theDENV NS2B-NS3 protease with indication of the different interactionsbetween protein and inhibitor. (B) The putative position of the catalytictriad and nelfinavir (NFV) in the active site of DENV NS2B-NS3protease. (C) Per-residue footprint of active site residues involved inthe interaction with nelfinavir. Highlighting electrostatic and van derWaals contributions coming from active site residues.

Table 3 Average hydrogen bond distance (A) and % occupancy ofinteracting active site residues with NFV during simulation time

H-bond interaction Average distance (A) % occupancy

Thr83 (OH)/(OH) NFV 2.31 81.3Met 84 (NH2)/(O52) NFV 3.12 85.2Met 84 (O)/(NH) NFV 3.08 72.3Gly 153 (O)/(OH) NFV 2.02 79.3

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His51, Asp75 and Ser135 will play a crucial role in the devel-opment of novel inhibitors using the structural features of NFV(Fig. 9B). NFV formed two backbone hydrogen bond interac-tions with Met84 and one with Gly153. It also formed a pi–pistacking interaction with Tyr161 and a side chain H bondinteraction with Thr83 (Fig. 9A). A molecular dynamics studyhighlights that Met84 and Thr83 formed a stable hydrogenbond interaction with NFV with higher % occupancy during

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simulation time (Table 3). Whereas, the % occupancy of thehydrogen bond interaction between Gly153 is lower (79.3%) ascompared to the other two residues (Table 3). The lower %hydrogen bond occupancy in case of Gly153 can be furtherconrmed from the fact that the electrostatic contributioncoming from Gly153 is slightly lower (�0.15 kcal mol�1) whencompared with Thr83. Thus, the backbone H-bond interactionwith Met84, Gly153 and side chain H-bond interaction withThr83 played a crucial role in capturing the binding orientationof NFV inside the active site of the DENV serine protease.

3.2.2. The nelnavir/CHIKV NSP2 interaction. The bindingmode of NFV with the NSP2 of CHIKV puts forward some inter-esting observations in terms of binding mode as well as residuesthat are involved. It was observed that one of the conservedcysteine residues of the catalytic triad, Cys1290, appears to beinvolved in the binding of NFV in the active site. In addition, NFVinteracts with conserved active site residues His1222, Ser1293,Gly1176 etc. at the C-terminal domain of NSP2 (Fig. 10A). Mostimportantly, the formation of a hydrogen bond between His1222and a carbonyl moiety appears to play an important role in thestability of NFV inside the active site (Fig. 10A). The majority ofthe interactions were polar and hydrophobic in nature, whichcorrelates with the high value of van der Waals contributions tothe total binding free-energy as well as the high contribution ofVdW forces in the per-residue energy decomposition (Fig. 10B).The interaction between NFV and the CHIKV NSP2 was found tobe stable during the simulation time with backbone C-a RMSDand the potential energy of the system was found to be wellconverged during the period of simulation (Fig. S1 and S2, ESI†).To understand the stability of the conserved hydrogen bondbetween His1222 and NFV, the H-bond distance and % occu-pancy between the oxygen atom of the carbonyl group and theHis1222 were monitored during simulation time. From Fig. 10A,it can be clearly stated that the hydrogen bond between these twomoieties was very stable with a % occupancy of 88.2 and anaverage distance of 3.50 A, which further points out the role ofHis1222 in the stability of NFV inside the active site (Table 4). Thebinding conformation of NFV during the simulation time inrespect to conserved cysteine and histidine residues (Fig. 10C)further gives an insight into the binding theme of NFV that canhelp in understanding the development of novel CHIKV inhibi-tors with the NFV template as starting point.

3.3. Conclusive pharmacophore features of nelnavir

The pharmacophore features and hypothesis presented inFig. 11 highlights the minimum pharmacophore requirements

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Fig. 10 (A) Ligand interaction plot showing active site residues of Cterminal CHIKV NSP2 with nelfinavir (NFV). (B) Per-residue footprint ofactive site residues involved in the interaction with nelfinavir (NFV).Highlighting contributions coming from electrostatic and van derWaals interactions in case of each residue. (C) The position of catalyticcysteine residues in the C-terminal domain and His1222 in respectivewith nelfinavir (NFV).

Table 4 Average hydrogen bond distance and % occupancy between–NH2 side chain of His1222 and NFV

H-bond interaction Average distance (A) % occupancy

His1222 (NH2)/(O49) NFV 3.50 88.2

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based on the structural template of NFV and its interaction withactive site residues of DENV NS2B-NS3 and CHIKV NSP2protease will help in the design and identication of novelprotease inhibitors that target the DENV NS2B-NS3 and CHIKV

Fig. 11 (A) and (B) highlights the minimum pharmacophore features ofNFV in bound conformation with DENV NS2B-NS3 protease andCHIKV NSP2, respectively. The artistic representation of the commonpharmacophore feature of NFV for their DENV/CHIKV protease activityis described with the arrows. The yellow highlighted region representsthe core area of the peptidomimetic scaffold. Green, yellow and whiteregions of pharmacophore points represents HP (hydrophobic), HBD

(hydrogen bond donor), HBA (hydrogen bond acceptor) respectively.

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NSP2. The pharmacophoric features presented in Fig. 11 can beused as a template for future pharmacophore-based drugdiscovery efforts and to screen large commercial databases e.g.ZINC Pharmer52 etc. to nd novel leads. Not only that: thecombination of structural similarity and minimum pharmaco-phore features of NFV will be effective in the future to pick newinhibitors from large pools of chemical compounds to identifynovel small-molecule protease inhibitors against these neglec-ted tropical diseases.

4. Conclusion

In the present study, we applied a drug re-proling strategy toexplore the antiviral effect of selected HIV/HCV inhibitorsagainst DENV and CHIKV. The peptidomimetic scaffold ofHIV/HCV inhibitors and its structural similarity with previouslyreported DENV NS2B-NS3 and CHIKV NSP2 protease inhibitorsinspired us to re-prole HIV/HCV inhibitors against the DENVNS2B-NS3 and CHIKV NSP2 protease. MM/GBSA-based bindingfree energy prole analysis highlighted a better binding ofnelnavir to the DENV NS2B-NS3 and CHIKV NSP2 protease,which was further validated by a modest antiviral activity ofnelnavir on CHIKV (EC50 ¼ 14 � 1 mM) and a bit morepronounced antiviral effect on DENV-2 (EC50 ¼ 3.5 � 0.4 mMand SI ¼ 4.6) in virus-cell-based assays. Besides nelnavir,lopinavir displayed a modest antiviral effect against CHIKV butnone of these compounds fully inhibit virus-induced cytopathiceffects. Ritonavir modestly inhibited DENV-2 but its activity isclearly associated with an adverse effect on the host cells. Fromthis study, it can be concluded that NFV has more pronouncedantiviral activity against DENV-2 as compared to CHIKV. Thestructural and pharmacophoric features now could be used toidentify novel leads from chemical databases as well as for thedesign of novel inhibitors that target both DENV and CHIKV.This study also gave credibility to the fact that further optimi-zation of structural and pharmacophore features of nelnavirmay lead to development of multifunctional small-moleculeinhibitor that target both the DENV NS2B-NS3 and CHIKVNSP2 protease. It is also worth to mention that previous reportshighlighted anti-HCV53 and anti-cancer properties54 of nelna-vir. Adding to this the antiviral activity against DENV andCHIKV corroborates that nelnavir has unique properties thatendow it with activity in different systems. Thus, future effortsto understand the structural and pharmacophore features ofnelnavir that are responsible for its diverse activity will beessential to develop novel multi-functional inhibitors.

Therefore, the binding mode, interaction and pharmaco-phore features of nelnavir that have been highlighted in thismanuscript will not only act as a stepping stone to develop novelDENV and CHIKV protease inhibitors, but also may be appliedto identify novel protease inhibitors that target other neglectedviral diseases from large pools of small-molecule inhibitors.

Conflict of interests

Authors declare no potential academic or nancial conict ofinterests.

This journal is © The Royal Society of Chemistry 2015

Acknowledgements

S.B. wish to thank computational support from MSKCC cBiocluster during the academic year of 2013–15. V.J. likes toacknowledge the nancial and infrastructure support fromBirla Institute of Technology, Mesra. We also would like toacknowledge Ruben Pholien, Annelies De Ceulaer and CarolineCollard for their excellent assistance in the generation of theantiviral data.

References

1 http://www.nature.com/drugdisc/news/articles/nrd1766.html.2 C. P. Adams and V. V. Brantner, Estimating the cost of newdrug development: is it really 802 million dollars?, HealthAff., 2006, 25, 420–428.

3 J. A. DiMasi, R. W. Hansen and H. G. Grabowski, The price ofinnovation: new estimates of drug development costs, J.Health Econ., 2003, 22, 151–185.

4 Drug discovery for neglected diseases, Nat. Rev. DrugDiscovery, 2008, 7, 955.

5 E. Chatelain and J.-R. Ioset, Drug discovery and developmentfor neglected diseases: the DNDi model, Drug Des., Dev.Ther., 2011, 5, 175–181.

6 I. H. Gilbert, Drug discovery for neglected diseases:molecular target-based and phenotypic approaches, J. Med.Chem., 2013, 56, 7719–7726.

7 M. D. AbdulHameed, S. Chaudhury, N. Singh, H. Sun,A. Wallqvist and G. J. Tawa, Exploring polypharmacologyusing a ROCS-based target shing approach, J. Chem. Inf.Model., 2012, 52, 492–505.

8 X. Hu, J. R. Compton, M. D. Abdulhameed, C. L. Marchand,K. L. Robertson, D. H. Leary, A. Jadhav, J. R. Hersheld,A. Wallqvist, A. M. Friedlander and P. M. Legler, 3-Substituted indole inhibitors against Francisella tularensisFabI identied by structure-based virtual screening, J. Med.Chem., 2013, 56, 5275–5287.

9 J. Li, S. Zheng, B. Chen, A. J. Butte, S. J. Swamidass and Z. Lu,A survey of current trends in computational drugrepositioning, Briengs Bioinf., 2015, 31, 1–11.

10 M. J. Keiser, V. Setola, J. J. Irwin, C. Laggner, A. I. Abbas,S. J. Hufeisen, N. H. Jensen, M. B. Kuijer, R. C. Matos,T. B. Tran, R. Whaley, R. A. Glennon, J. Hert,K. L. H. Thomas, D. D. Edwards, B. K. Shoichet andB. L. Roth, Predicting new molecular targets for knowndrugs, Nature, 2009, 462, 175–181.

11 T. T. Ashburn and K. B. Thor, Drug repositioning: identifyingand developing new uses for existing drugs, Nat. Rev. DrugDiscovery, 2004, 3, 673–683.

12 S. Ekins, A. J. Williams, M. D. Krasowski and J. S. Freundlich,In silico repositioning of approved drugs for rare andneglected diseases, Drug Discovery Today, 2011, 16, 298–310.

13 Z. Liu, H. Fang, K. Reagan, X. Xu, D. L. Mendrick, W. SlikkerJr andW. Tong, In silico drug repositioning –what we need toknow, Drug Discovery Today, 2013, 18, 110–115.

RSC Adv., 2015, 5, 85938–85949 | 85947

RSC Advances Paper

Publ

ishe

d on

05

Oct

ober

201

5. D

ownl

oade

d by

KU

Leu

ven

Uni

vers

ity L

ibra

ry o

n 17

/11/

2015

09:

12:4

9.

View Article Online

14 D.-L. Ma, D. S.-H. Chan and C.-H. Leung, Drug repositioningby structure-based virtual screening, Chem. Soc. Rev., 2013,42, 2130–2141.

15 S. Bhakat, W. Karubiu, V. Jayaprakash and M. E. S. Soliman,A perspective on targeting non-structural proteins to combatneglected tropical diseases: dengue, West Nile andchikungunya viruses, Eur. J. Med. Chem., 2014, 87, 677–702.

16 M. G. Guzman, S. B. Halstead, H. Artsob, P. Buchy, J. Farrar,D. J. Gubler, E. Hunsperger, A. Kroeger, H. S. Margolis,E. Martinez, M. B. Nathan, J. L. Pelegrino, C. Simmons,S. Yoksan, and R. W. Peeling. Dengue: a continuing globalthreat, Nat. Rev. Microbiol., 2010, S7–S16.

17 S. Bhatt, P. W. Gething, O. J. Brady, J. P. Messina,A. W. Farlow, C. L. Moyes, J. M. Drake, J. S. Brownstein,A. G. Hoen, O. Sankoh, M. F. Myers, D. B. George,T. Jaenisch, G. R. W. Wint, C. P. Simmons, T. W. Scott,J. J. Farrar and S. I. Hay, The global distribution andburden of dengue, Nature, 2013, 496, 504–507.

18 M. G. Guzman and E. Harris, Dengue, Lancet, 2015, 385, 453–465.

19 D. J. Gubler, Dengue and Dengue Hemorrhagic Fever, Clin.Microbiol. Rev., 1998, 11, 480–496.

20 S. Murrell, S.-C. Wu and M. Butler, Review of dengue virusand the development of a vaccine, Biotechnol. Adv., 2011,29, 239–247.

21 S.-W. Wan, C.-F. Lin, S. Wang, Y.-H. Chen, T.-M. Yeh,H.-S. Liu, R. Anderson and Y.-S. Lin, Current progress indengue vaccines, J. Biomed. Sci., 2013, 20, 37.

22 A. A. Rashad, S. Mahalingam and P. A. Keller, Chikungunyavirus: emerging targets and new opportunities for medicinalchemistry, J. Med. Chem., 2014, 57, 1147–1166.

23 O. Schwartz and M. L. Albert, Biology and pathogenesis ofchikungunya virus, Nat. Rev. Microbiol., 2010, 8, 491–500.

24 J. E. Staples, R. F. Breiman and A. M. Powers, ChikungunyaFever: An Epidemiological Review of a Re-EmergingInfectious Disease, Clin. Infect. Dis., 2009, 49, 942–948.

25 M. P. Manns and T. von Hahn, Novel therapies for hepatitisC [mdash] one pill ts all?, Nat. Rev. Drug Discovery, 2013, 12,595–610.

26 J. Pokorna, L. Machala, P. Rezacova and J. Konvalinka,Current and Novel Inhibitors of HIV Protease, Viruses,2009, 1, 1209–1239.

27 E. D. Clercq, The design of drugs for HIV and HCV, Nat. Rev.Drug Discovery, 2007, 6, 1001–1018.

28 C. G. Noble, C. C. Seh, A. T. Chao and P. Y. Shi, Ligand-bound structures of the dengue virus protease reveal theactive conformation, J. Virol., 2012, 86, 438–446.

29 http://www.rcsb.org/pdb/explore/explore.do?structureId¼3TRK.30 P. Erbel, N. Schiering, A. D'Arcy, M. Renatus, M. Kroemer,

S. P. Lim, Z. Yin, T. H. Keller, S. G. Vasudevan andU. Hommel, Structural basis for the activation of aviviralNS3 proteases from dengue and West Nile virus, Nat.Struct. Mol. Biol., 2006, 13, 372–373.

31 http://www.chemspider.com/.32 Y. Maharaj, S. Bhakat and M. E. S. Soliman, Computer-aided

Identication of Novel DprE1 Inhibitors as Potential Anti-TBLead Compounds: A Hybrid Virtual-screening andMolecular

85948 | RSC Adv., 2015, 5, 85938–85949

Dynamics Approach, Lett. Drug Des. Discovery, 2015, 12, 302–313.

33 O. Trott and A. J. Olson, AutoDock Vina: improving the speedand accuracy of docking with a new scoring function,efficient optimization and multithreading, J. Comput.Chem., 2010, 31, 455–461.

34 C. D. Lau, M. J. Levesque, S. Chien, S. Date and J. H. Haga,ViewDock TDW: high-throughput visualization of virtualscreening results, Bioinformatics, 2010, 26, 1915–1917.

35 E. F. Pettersen, T. D. Goddard, C. C. Huang, G. S. Couch,D. M. Greenblatt, E. C. Meng and T. E. Ferrin, UCSFChimera–a visualization system for exploratory researchand analysis, J. Comput. Chem., 2004, 25, 1605–1612.

36 P. D. Lyne, M. L. Lamb and J. C. Saeh, Accurate Prediction ofthe Relative Potencies of Members of a Series of KinaseInhibitors Using Molecular Docking and MM-GBSAScoring, J. Med. Chem., 2006, 49, 4805–4808.

37 G. Rastelli, A. D. Rio, G. Degliesposti and M. Sgobba, Fastand accurate predictions of binding free energies usingMM-PBSA and MM-GBSA, J. Comput. Chem., 2010, 31, 797–810.

38 H. Sun, Y. Li, M. Shen, S. Tian, L. Xu, P. Pan, Y. Guan andT. Hou, Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance usinghigh solute dielectric constant MM/GBSA and MM/PBSArescoring, Phys. Chem. Chem. Phys., 2014, 16, 22035–22045.

39 M. D. Abdulhameed, A. Hamza and C. G. Zhan, Microscopicmodes and free energies of 3-phosphoinositide-dependentkinase-1 (PDK1) binding with celecoxib and otherinhibitors, J. Phys. Chem. B, 2006, 110, 26365–26374.

40 N. Li, R. I. Ainsworth, B. Ding, T. Hou and W. Wang, UsingHierarchical Virtual Screening To Combat Drug Resistanceof the HIV-1 Protease, J. Chem. Inf. Model., 2015, 55, 1400–1412.

41 P. A. Greenidge, C. Kramer, J. C. Mozziconacci andW. Sherman, Improving Docking Results via Reranking ofEnsembles of Ligand Poses in Multiple X-ray ProteinConformations with MM-GBSA, J. Chem. Inf. Model., 2014,54, 2697–2717.

42 S. Sirin, R. Kumar, C. Martinez, M. J. Karmilowicz, P. Ghosh,Y. A. Abramov, V. Martin and W. Sherman, A ComputationalApproach to Enzyme Design: Predicting u-AminotransferaseCatalytic Activity Using Docking and MM-GBSA Scoring, J.Chem. Inf. Model., 2014, 54, 2334–2346.

43 I. Slynko, M. Scharfe, T. Rumpf, J. Eib, E. Metzger, R. Schule,M. Jung and W. Sippl, Virtual Screening of PRK1 Inhibitors:Ensemble Docking, Rescoring Using Binding Free EnergyCalculation and QSAR Model Development, J. Chem. Inf.Model., 2014, 54, 138–150.

44 D. A. Case, V. Babin, J. T. Berryman, R. M. Betz, Q. Cai,D. S. Cerutti, T. E. Cheatham, III, T. A. Darden, R. E. Duke,H. Gohlke, A. W. Goetz, S. Gusarov, N. Homeyer,P. Janowski, J. Kaus, I. Kolossvary, A. Kovalenko, T. S. Lee,S. LeGrand, T. Luchko, R. Luo, B. Madej, K. M. Merz,F. Paesani, D. R. Roe, A. Roitberg, C. Sagui, R. Salomon-Ferrer, G. Seabra, C. L. Simmerling, W. Smith, J. Swails,R. C. Walker, J. Wang, R. M. Wolf, X. Wu and

This journal is © The Royal Society of Chemistry 2015

Paper RSC Advances

Publ

ishe

d on

05

Oct

ober

201

5. D

ownl

oade

d by

KU

Leu

ven

Uni

vers

ity L

ibra

ry o

n 17

/11/

2015

09:

12:4

9.

View Article Online

P. A. Kollman, AMBER 14, University of California, SanFrancisco, 2014.

45 S. Bhakat, A. J. M. Martin andM. E. S. Soliman, An integratedmolecular dynamics, principal component analysis andresidue interaction network approach reveals the impact ofM184V mutation on HIV reverse transcriptase resistance tolamivudine, Mol. BioSyst., 2014, 10, 2215–2228.

46 D. R. Roe and T. E. Cheatham, PTRAJ and CPPTRAJ: Sowarefor Processing and Analysis of Molecular DynamicsTrajectory Data, J. Chem. Theory Comput., 2013, 9, 3084–3095.

47 W. Humphrey, A. Dalke and K. Schulten, VMD: Visualmolecular dynamics, J. Mol. Graphics, 1996, 14, 33–38.

48 L. Delang, N. Segura Guerrero, A. Tas, G. Querat,B. Pastorino, M. Froeyen, K. Dallmeier, D. Jochmans,P. Herdewijn, F. Bello, E. J. Snijder, X. de Lamballerie,B. Martina, J. Neyts, M. J. van Hemert and P. Leyssen,Mutations in the chikungunya virus non-structuralproteins cause resistance to favipiravir (T-705), a broad-spectrum antiviral, J. Antimicrob. Chemother., 2014, 69,2770–2784.

49 S. J. F. Kaptein, T. de Burghgraeve, M. Froeyen, B. Pastorino,M. M. F. Alen, J. A. Mondotte, P. Herdewijn, M. Jacobs, X. deLamballerie, D. Schols, A. V. Gamarnik, F. Sztaricskai andJ. Neyts, A Derivate of the Antibiotic Doxorubicin Isa Selective Inhibitor of Dengue and Yellow Fever VirusReplication In Vitro, Antimicrob. Agents Chemother., 2010,54, 5269–5280.

50 J. Deng, N. Li, H. Liu, Z. Zuo, O. W. Liew, W. Xu, G. Chen,X. Tong, W. Tang, J. Zhu, J. Zuo, H. Jiang, C.-G. Yang, J. Liand W. Zhu, Discovery of Novel Small Molecule Inhibitorsof Dengue Viral NS2B-NS3 Protease Using VirtualScreening and Scaffold Hopping, J. Med. Chem., 2012, 55,6278–6293.

This journal is © The Royal Society of Chemistry 2015

51 R. Takhampunya, S. Ubol, H. S. Houng, C. E. Cameron andR. Padmanabhan, Inhibition of dengue virus replication bymycophenolic acid and ribavirin, J. Gen. Virol., 2006, 87,1947–1952.

52 D. R. Koes and C. J. Camacho, ZINCPharmer:pharmacophore search of the ZINC database, Nucleic AcidsRes., 2012, 40, W409–W414.

53 S. Toma, T. Yamashiro, S. Arakaki, J. Shiroma, T. Maeshiro,K. Hibiya, N. Sakamoto, F. Kinjo, M. Tateyama and J. Fujita,Inhibition of intracellular hepatitis C virus replication bynelnavir and synergistic effect with interferon-alpha,Journal of Viral Hepatitis, 2009, 16, 506–512.

54 M. Kraus, J. Bader, H. Overklee and C. Driessen, Nelnaviraugments proteasome inhibition by bortezomib in myelomacells and overcomes bortezomib and carlzomib resistance,Blood Cancer Journal, 2013, 3, e103.

55 C. Nitsche, V. N. Schreier, M. A. Behnam, A. Kumar,R. Bartenschlager and C. D. Klein, Thiazolidinone–peptidehybrids as dengue virus protease inhibitors with antiviralactivity in cell culture, J. Med. Chem., 2013, 56, 8389–8403.

56 G. C. Zhou, Z. Weng, X. Shao, F. Liu, X. Nie, J. Liu, D. Wang,C. Wang and K. Guo, Discovery and SAR studies ofmethionine–proline anilides as dengue virus NS2B-NS3protease inhibitors, Bioorg. Med. Chem. Lett., 2013, 23,6549–6554.

57 M. Yildiz, S. Ghosh, J. A. Bell, W. Sherman and J. A. Hardy,Allosteric inhibition of the NS2B-NS3 protease fromdengue virus, ACS Chem. Biol., 2013, 8, 2744–2752.

58 V. K. Ganesh, N. Muller, K. Judge, C. H. Luan,R. Padmanabhan and K. H. Murthy, Identication andcharacterization of nonsubstrate based inhibitors of theessential dengue and West Nile virus proteases, Bioorg.Med. Chem., 2005, 13, 257–264.

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