Computer-Aided Discovery of Trypanosoma brucei RNA-Editing Terminal Uridylyl Transferase 2 Inhibitors

Computer-Aided Discovery of Trypanosoma bruceiRNA-Editing Terminal Uridylyl Transferase 2 Inhibitors

€Ozlem Demir1, Mehdi Labaied2, Chris Merritt2,Ken Stuart2,3 and Rommie E. Amaro1,*

1Department of Chemistry and Biochemistry, University ofCalifornia, San Diego, La Jolla, CA 92093, USA2Seattle Biomedical Research Institute, Seattle, WA 98109,USA3Department of Pathobiology, University of Washington,Seattle, WA 98195, USA*Corresponding author: Rommie E. Amaro,[email protected]

Human African trypanosomiasis (HAT) is a major healthproblem in sub-Saharan Africa caused by Trypanosomabrucei infection. Current HAT drugs are difficult toadminister and not effective against all parasite speciesat different stages of the disease which indicates anunmet pharmaceutical need. TbRET2 is an indispens-able enzyme for the parasite and is targeted here usinga computational approach that combines moleculardynamics simulations and virtual screening. The com-pounds prioritized are then tested in T. brucei viaAlamar blue cell viability assays. This work identified 20drug-like compounds which are candidates for furthertesting in the drug discovery process.

Key words: HAT, human African trypanosomiasis, RET2,sleeping sickness, Trypanosoma brucei, trypanosomes,TUTase, virtual screening

Received 28 October 2013, revised 12 December 2013 andaccepted for publication 7 February 2014

Human African trypanosomiasis (HAT), also known assleeping sickness, is a major health problem threateningthe lives of millions of people in sub-Saharan Africa (1).The disease is caused by either of the two trypanosomesubspecies Trypanosoma brucei rhodesiense or Trypano-

soma brucei gambiense that are transmitted to humans bythe tsetse flies (1,2). The majority of the cases are due toan infection by Trypanosoma brucei gambiense (2). Ifuntreated, HAT is fatal.

In the first stage of HAT, parasites live in blood and lymphas well as in the tissues of the host (3).a Later, in the sec-ond stage, parasites transit the blood–brain barrier andinfect the central nervous system of the host (3).a Early

diagnosis and treatment is desirable, but typically, HAThas reached the second stage at the time of diagnosis (1).

Suramin and pentamidine are currently used to treat earlyphases of the disease (3)a. Although these two drugs aregenerally successful, they can cause undesirable side-effects. For the treatment of the late neurological stages ofHAT, melarsoprol and eflornithine are the only drugscurrently available (3)a. These two drugs are very toxic anddifficult to administer as well as having severe potentialside-effects that can even be fatal (4). Currently, a combina-tion therapy of nifurtimox and eflornithine is the first-linetreatment against second-stage T. brucei gambiense casesof HAT (5–8). However, eflornithine is effective only againstTrypanosome brucei gambiense. Moreover, drug resistanttrypanosomes are emerging which emphasizes the need foraction to discover novel effective drugs against HAT (9).

Trypanosoma brucei is one of the kinetoplastid protozoathat have an unusual mitochondrial DNA, called kDNA,which consists of maxicircles and minicircles (10,11). Themaxicircle DNA encodes for oxidative phosphorylationenzymes and mitochondrial rRNAs (10,11). However, mostof the mRNAs encoded in the maxicircle DNA undergoextensive post-transcriptional editing before their translation.The editing process is performed by a dynamic, heteroge-nous multiprotein machinery which includes ‘the 20S edito-some’ that uses numerous guide RNAs (gRNA) encoded inthe minicircles to specify the sites of editing and the final edi-ted sequence (10,11). Recognition of the editing sites,which are sites of mRNA/gRNA duplex sequence mismatch,is followed by either deletion of uridylates (Us) by an exonu-clease or insertion of Us by a terminal uridylyl transferase(TUTase) depending on the type of mismatch with the gRNAspecifying the number of Us deleted or inserted (10–12).

RNA-editing terminal uridylyl transferase (TUTase) 2 ofT. brucei (TbRET2) is an indispensable part of the edito-some and has been shown to be essential for the viabilityof both the insect and the bloodstream forms of the para-site (13,14). To catalyze insertion of a U to the 30 RNA ter-minus, TbRET2 must bind RNA and UTP at the same timein its deep active site releasing a pyrophosphate group atthe end of the reaction (15,16). A family of seven humanTUTases has been identified recently with some sequencesimilarity to TbRET2 (17–22). However, not much is knownabout their structure due to the lack of data except for

ª 2014 John Wiley & Sons A/S. doi: 10.1111/cbdd.12302 131

Chem Biol Drug Des 2014; 84: 131–139

Research Article

PAPD1 which has less than 20% sequence identity (17).With its recently elucidated high-resolution crystal structureboth in apo and in UTP-bound forms, TbRET2 stands as apromising HAT drug target (15).

In this work, we present 20 drug-like inhibitors of TbRET2that we discovered by integrating relaxed complex scheme(RCS) into our virtual screening protocol. Starting from ahigh-resolution crystal structure (pdbID:2B51) (15), twocopies of 50-ns molecular dynamics (MD) simulations werepreviously used to investigate the dynamics of UTP-boundTbRET2 (23). Using the resulting structures in conjunctionwith the RCS method, we predicted the most promisingcompounds for TbRET2 inhibition. The MD structuralensemble was significantly reduced by including only themost dominant three cluster centroids. Alamar BlueTM(AB)cell viability assays (24–27) confirmed 20 inhibitors withEC50 values in the low lM range. We thus demonstratedthat the use of receptor flexibility in the virtual screeningprocess achieved an enrichment of the set of compoundsto be tested and led to the discovery of several promisingscaffolds as TbRET2 inhibitors.

Methods and Materials

Molecular dynamics simulationsFor this work, two copies of 50 ns molecular dynamics(MD) simulations of UTP-bound TbRET2 are utilized. Thedetails of MD preparation and simulation protocolare described elsewhere (23). Snapshots of the systemextracted at every picosecond were used to obtain a com-bined trajectory of 10 000 frames.

RMSD-based clusteringClustering of 10 000-frame MD trajectory of UTP-boundTbRET2 was performed using the GROMOS algorithm (28)with GROMACS4.0.5 analysis software (29). After superim-posing the protein with respect to Ca atoms to remove over-all translation and rotation, the trajectory was clustered withrespect to the coordinates of all atoms in the TbRET2 activesite as described in Demir et al. (23). After trying differentRMSD cutoff values, an optimum RMSD cutoff of 1.55 �Awas used for clustering which resulted in 27 clusters. Mostpopulated 11 clusters spanned 97.27% of all 10 000frames. Population percentages of the top five clusters were26.22%, 21.99%, 21.74%, 9.35%, and 4.26%, respectively.

The relaxed complex schemeAutodock Vina (30) was used for all docking experiments,and the lowest docking score computed is listed for eachcompound. We docked to the most populated three clus-ter centroids for initial compound selection and used thetop 11 cluster centroids for the relaxed complex schemeto calculate binding affinities. Ensemble-averaged bindingaffinities were computed as the weighted average of

docking scores into the most populated 11 cluster cent-roids using cluster population percentages as weights.

ADME filters for drug-likenessWe filtered compounds for strict adherence to Lipinski’srule of 5 (31,32), Jorgensen’s rule of 3 (33) and logPoct/

wat < 3. Schrodinger’s QikProp module (34) was used topredict and filter for these ADME properties.

Similarity searchA similarity search over the full NCI database for the threelow nanomolar hits using 90% Tanimoto similarity as thecriteria found 33 compounds which were rank-orderedaccording to their ensemble-based binding affinities usingour RCS protocol.

Whole-cell parasite assaysCompounds were obtained from the NCI/DTP OpenChemical Repository (http://dtp.cancer.gov). Stock solu-tions were made in 100% DMSO and fresh aliquots weregenerated. Among the 24 received compounds, seventeenwere easily dissolved, six needed 4 h agitation at roomtemperature (RT) to obtain complete solubility, and one324623 could not be dissolved despite extensive agitationat RT and incubation at 37 °C and thus was not tested.

An Alamar BlueTM (AB) viability assay (24–27) was performedin a 96-well plate format to screen for drug sensitivity of Try-panosoma brucei brucei bloodstream form 427. Parasitesat 2 9 103 cells/mL were incubated with different drugconcentrations (twofold serial dilutions) at 200 lL final vol-ume of HMI-9 with 10% FBS/well for 48 h at 37 °C and 5%CO2. Twenty microliter of Alamar Blue (Invitrogen) was thenadded to each well, and cells were incubated for an addi-tional 4 h under the same conditions. DMSO neverexceeded 0.08% for these assays. Fluorescence signal wasquantified using a SpectraMax M2 fluorescence platereader (Molecular Devices, Sunnyvale, CA, USA) (Excitation544 nm – Emission 590 nm). Background levels of fluores-cence, representing complete parasite death, were deter-mined with wells that contained no parasites and themaximum levels of fluorescence were determined with wellsthat contained parasites with no drug added. The EC50 val-ues were determined using the GraphPad Prism5 software[Log (inhibitor) versus response – Variable slope (fourparameters)]. Compounds were tested with three differentparasite cultures (three biological replicates). The value ofeach biological replicate is the average of three replicatesmade in the same plate (three technical replicates).

An initial screening using a narrow range of concentrationsfrom 8 to 0.5 lM was performed to select compounds withEC50 values ≤4 lM using one replicate. Based on theresults from the initial test, compounds D1, D2, and D3

(Table 1) were selected for additional screening. For the

132 Chem Biol Drug Des 2014; 84: 131–139

Demir et al.

Table 1: The low micromolar hits found in this study. BE: predicted binding energy in kcal/mol

Compd. ID NCI No Molecule

Crystal structure BE

for RNA binding site

RCS BE for RNA

binding site


for UTP binding site

RCS BE for UTP binding

site EC50 (μM)

NCI60 dose response

(μM)

D1 94600 -8.8 -8.10 -9.5 -9.06 0.96 0.0381

P7 643148 -9.1 -8.02 -9.8 -9.22 2-4 51.6

D2 71881 -8.5 -8.14 -9.4 -9.10 2.29 100

D3 329249 -8.4 -8.92 ≥4 3.44

P1 266535 -9.0 -8.39 -9.1 -8.61 0.013 0.0459

P2 132791 -8.6 -8.72 0.028 0.0648

P3 267461 -8.5 -8.28 0.026 0.158

P4 154020 -8.5 -7.93 0.285 8.42

P5 629971 -8.6 -8.24 -9.2 -9.16 0.905 0.052

P6 106193 -8.3 -7.73 -9.1 -8.50 2-4 2.95

Chem Biol Drug Des 2014; 84: 131–139 133

Drug-Like RET2 Inhibitors

three active similar compounds, we performed multiplebiological replicates only if the initial EC50s obtained werelower than 4 lM.

Purity testsTwelve of the twenty drug-like compounds which had thelowest EC50 values were tested for purity. An Agilent(Santa Clara, CA, USA) 1260 HPLC system coupled with a

Thermo LCQ Deca mass spectrometer was employed forLC-UV-MS analysis using positive ion mode electrosprayionization (ESI) as the ion source. A Shiseido MGII C-18column (2.0 mm ID 9 100 mm length, 3 lm particle size)was used for LC separation with flow rate of 0.30 mL/min.2.5% acetonitrile in water with 0.1% formic acid was usedas mobile phase A, and pure acetonitrile with 0.1% formicacid was used as mobile phase B. Details for the LC gra-dient settings are as follows: increased from 10% B to

Compd.

Table 1: (continued)

ID NCI No Molecule


for RNA binding site

RCS BE for RNA

binding site


for UTP binding site

RCS BE for UTP binding

site EC50 (μM)

NCI60 dose response

(μM)

P8 637729 -9.1 -8.49 2-4 5.81

P9 196524 -8.6 -8.16 -9.1 -8.67 2-4 2.89

P10 335142 -8.9 -8.32 -9.1 -8.85 2-4 4.87

P11 634658 -9.1 -8.49 2-4 84

P12 668270 -8.7 -7.84 -9.1 -8.99 2-4 2.4

S1 126765 -7.8 -7.32 -8.9 -7.94 0.023 0.0287

S2 137443 -8.8 -8.82 -8.8 -8.30 0.051 0.0941

S3 217307 -7.8 -7.09 -8.1 -7.91 1.154 7.64

S4 344557 -9.0 -7.58 -8.3 -7.92 1.451 NA

S5 349155 -8.3 -8.04 -8.9 -8.27 0.146 0.184


Demir et al.

95% B in 10 min, held at 95% B for 5 min, then returnedto 10% B in 1 min, and held at 5% B for 6 min. The UVdetection wavelength was set at 254 nm.

Results and Discussion

Control dockingIn the control docking of UTP into the TbRET2 crystal struc-ture (pdbID: 2B51), Autodock Vina predicted the most favor-able binding pose as depicted in Figure 1A with a bindingaffinity of �8.6 kcal/mol. The binding poses of uridine andribose in the crystal structure were reproduced well in thecontrol docking experiment; however, a large heavy-atomRMSD of 5.04 �A was still computed for UTP due to the devi-ation in the flexible triphosphate tail. Excluding the terminaltwo phosphates from the RMSD calculation reduced theheavy-atom RMSD of UTP to 3.79 �A.

Initial set of recommended compoundsFor the initial virtual screening of National Cancer InstituteDiversity Set 2 (NCIDS2), we used the static TbRET2 crys-tal structure (pdbID:2B51) (15) to dock the 1324 com-pounds (1541 entries including stereomers) according totheir predicted binding affinity. To incorporate receptorflexibility into our virtual screening protocol, we alsodocked the NCIDS2 compounds into the most populatedthree cluster centroids of UTP-bound TbRET2 MD simula-tions depicted in Figure 1B and rank-ordered the com-pounds based on their docking scores. For each clustercentroid, 100 compounds with the best docking scoreswere selected and filtered for the ADME propertiesdetailed in the Methods section.

There are two main binding sites in TbRET2 active site:one for UTP and one for the terminal RNA nucleotide. Totarget both binding sites, we performed virtual screening

once in the absence of UTP to target the UTP binding siteand another in the presence of UTP to target the terminalRNA nucleotide-binding site. Filtering the top scoring 100ligands for each of the three cluster centroids left 14unique compounds (16 entries) for the UTP binding siteand 15 unique compounds (18 entries) for the terminalRNA nucleotide-binding site. When combined, these twosets form a set of 24 unique compounds. The bindingaffinities of these 24 compounds were refined using ourrelaxed complex scheme and recommended for experi-mental testing (Table S1).

Low micromolar inhibitors found in round 1One compound in the recommended set, NCI compound324623, was not tested because it was not soluble.Among the 23 tested, three compounds (D1, D2, and D3

in Table 1) had EC50 values lower than or equal to 4 lMcorresponding to 13% hit rate. Of the three, compoundsD1 and D2 were predicted to bind favorably to both bind-ing sites, while compound D3 was predicted to bind favor-ably to the UTP binding site.

If we had selected the same number of compounds to testbased on the crystal structure docking score ranks, 7 of14 compounds for the UTP binding site and 7 of 16 com-pounds for the terminal RNA nucleotide-binding site wouldnot have been tested. Also, among the three compoundswith the lowest EC50 values, compound D3 would nothave been tested based on crystal structure dockingranks, indicating the enrichment achieved by incorporatingactive site flexibility.

Second set of recommended compoundsWe performed a second virtual screening with NCI Platedcompounds (a combined set of the NCI’s Mechanistic Set,Natural Products Set, COMBO Set, and Oncology

A B

Figure 1: Control docking result and receptor structures used for docking compound selection. (A) Docked pose and crystal structurebinding pose of UTP are shown in stick representation and ball-and-stick representation, respectively. Nitrogen, oxygen, carbon, andphosphorus atoms are colored in blue, red, cyan, and tan, respectively. (B) Active sites of the most populated three cluster centroidssuperimposed. UTP is also depicted in stick-and-ball representation for reference. All the active site residues used in clustering aredepicted in lines colored with respect to residue name.



Approved Set). Our ADME filters selected only 307 com-pounds of 805 total. After docking the prefiltered com-pounds into the most populated three cluster centroids, weselected 39 compounds with binding affinities lower than orequal to �8.2 kcal/mol for the RNA nucleotide-binding site,and 52 compounds with binding affinities lower than orequal to �8.6 kcal/mol for the UTP binding site. A combinedset of 60 compounds was selected for experimental testing.

Low nanomolar inhibitors found in round 2Among the recommended set of 60 compounds, 9compounds were not available from NCI, another 10 com-pounds (with NCI codes 11440, 40341, 118732, 157004,314622, 623051, 634568, 5890, 292147, and 634224)could not be tested due to solubility problems, and onecompound (with NCI code 94600) was already tested inNCIDS2 screening. Out of the tested 40 compounds inthe second round (Table S2), 12 compounds had EC50values lower than 4 lM corresponding to 30% hit rate.Three of these compounds (compounds P1, P2, and P3

in Table 1) had EC50 values lower than 30 nM.

Five of the 39 compounds for the terminal RNA bindingsite and 9 of 52 compounds for the UTP binding sitewould not have been tested if we had used crystalstructure docking rank-orders to select the same numberof compounds. One of the three low nanomolar hits,compound P2, would not have been tested if only crys-tal structure ranks were used to select compounds.

Similarity search over the full NCI databaseA similarity search over the full NCI database for the 3 lownanomolar hits using %90 Tanimoto similarity as the crite-rion found 33 compounds which we docked into the topthree TbRET2 cluster centroids and ranked according totheir binding score. Twenty-two of these compounds werenot available from NCI/DTP, and one of the delivered com-pounds (NCI code 609084) could not be tested due to insol-ubility leaving us with 10 compounds to test (Table S3).

Experiments demonstrated that 5 of the compounds haveEC50 values lower than 4 lM (compounds S1 through S5 inTable 1). Notably, S1 and S2 had EC50 values of approxi-mately 22 and 50 nM, respectively.

Purity of compoundsAmong the 20 compounds reported in Table 1, the purityof twelve compounds with the lowest EC50 values wasevaluated via LC-UV-MS analysis. The mass spectrometrydata are presented in the Supplementary Info. The purityof all compounds except one is higher than 88% (Table 2).

Predicted modes of binding for the top three hitsWe identified the best-scoring cluster centroids for each ofthe top three hits in the second round and analyzed the

A

B

Figure 2: Predicted binding poses of top hits at the UTP bindingsite. Best-scoring binding mode for (A) compound P2 and (B)compound P1 is depicted in stick representation. The carbon,oxygen, nitrogen, and hydrogen atoms of the hit compound arecolored in orange, red, blue, and white, respectively. The carbon,oxygen, and nitrogen atoms of the receptor are colored in cyan,red, and blue, respectively. Only the polar hydrogen atoms of thehit compounds are depicted, while no receptor hydrogen atomsare depicted for clarity. The polar water pocket adjacent to UTPbinding site is shown in surface representation.

Table 2: Purity of compounds

CompoundID

NCIno.

Purity(%)

D1 94600 94.09D2 71881 99.14P1 266535 96.86P2 132791 98.39P3 267461 97.20P4 154020 100.00P5 629971 96.55S1 126765 98.38S2 137443 97.38S3 217307 59.40S4 344557 100.00S5 349155 88.74


Demir et al.

most favorable mode of binding predicted. In the predictedbinding mode of compound P2 to the UTP binding site(Figure 2A), part of the compound occupies the polarwater pocket adjacent to the UTP binding site we identi-fied in our previous work (23). There are additional hydro-gen-bonding interactions of the compound to the Asn 248side chain and the Ser289 backbone. The predicted bind-ing mode of compound P1 to the UTP binding site alsoindicates occupation of the polar water pocket adjacent(Figure 2B). There was also very good shape and electro-static complementarity observed between the compoundand the pocket.

When the terminal RNA nucleotide-binding site was tar-geted in the presence of UTP at the active site, the pre-dicted binding poses for compounds P3 and P1 indicatedthe importance of p–p stacking interaction with the UTP

nucleobase (Figure 3). There are additional hydrogen-bonding interactions with Cys83 and Asp267 in the caseof compound P1 and with Glu424 in the case of com-pound P3 (Figure 3).

Overall, these predicted binding poses emphasize thepotential use of adjacent water pocket when targeting theUTP binding site and the importance of p–p stackinginteraction with the UTP nucleobase when targeting theterminal RNA nucleotide-binding site. The polar sidechains in the region could also be used to improvebinding affinities.

Further considerations on the first set of HATinhibitorsDrug discovery is a long and tedious process which musttake into account many aspects for potency, selectivity,and safety. Although a handful of compounds werediscovered that kill the whole-cell T. brucei parasites,further assays with TbRET2 are required to validate theirtarget. In addition, compound P12 has a reactive alkenefunctional group that needs to be addressed for furtheruse in the drug discovery process. Cytotoxicity towardhuman cells is also an important issue in the drug discov-ery process. For the NCI compounds in Table 1, the aver-age EC50 values in the NCI/DTP website against 59different human cancer cell lines are compiled andreported. Three compounds, namely D2, P4, and P11,achieve more than 10 times selectivity against the para-sites meeting the cytotoxicity criteria suggesting them aspromising compounds for HAT drug discovery (35). How-ever, it is known that the sensitivity of cancer cells andhealthy cells to compounds may differ, and thus, thesedata can be taken as a rough estimate for cytotoxicity.Further biological analysis of the compounds describedhere is needed to evaluate and move these scaffoldsfurther in the drug discovery process.

Conclusion

There is an urgent pharmaceutical need to develop noveldrugs against HAT due to the emerging drug resistance inthe relevant T. brucei parasites against current drugs thatare already difficult to administer and cause many seriousside-effects. Indispensable parts of the multisubunit RNA-editing machinery in trypanosomes are considered poten-tial drug targets, and there have been considerable effortsto achieve inhibition of such enzymes such as RNA ligases(36–39). In this work, we present 20 compounds that areactive against T. brucei which could be used as scaffoldsfor further drug design efforts. These compounds werediscovered as potent TbRET2 inhibitors using a computa-tional scheme that combines all-atom molecular dynamicssimulations and virtual screening experiments. Suchensemble-based approaches taking receptor flexibility intoaccount are promising for early drug discovery projects.

A

B

Figure 3: Predicted binding poses of top hits at the terminalRNA nucleotide-binding site. Best-scoring binding mode for (A)compound P3 and (B) compound P1 is depicted in stickrepresentation. The color codes for the receptor and top hits arethe same as in Figure 2. The carbon, nitrogen, and oxygenatoms in the UTP are colored in green, blue, and red,respectively.



Acknowledgments

We would like to thank Ruslan Aphasizhev, Bamboo Dong,Hartmut Luecke for helpful discussions and Yongxuan Sufor the purity tests. This work was funded in part by theNational Institutes of Health (NIH) through the NIH Director’sNew Innovator Award Program DP2-OD007237, a K22Career Transition Award K22-AI081901, and throughthe NSF TeraGrid Supercomputer resources grant RACCHE060073N to REA and NIH Grants AI14102 andAI075641 to KS. Molecular dynamics simulations were per-formed at the Texas Advanced Computing Center.

Conflict of Interest

We declare no conflict of interests.

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Supporting Information

Additional Supporting Information may be found in theonline version of this article:

Figure S1. Mass spectra of the twelve drug-like com-pounds.

Table S1. NCIDS2 compounds tested.

Table S2. NCI Plated compounds tested.

Table S3. Tested similar compounds for three hits.



Documents

Computer-Aided Discovery of Trypanosoma brucei RNA-Editing Terminal Uridylyl Transferase 2 Inhibitors