Identification of influenza polymerase inhibitors targeting polymerase PB2 cap-binding domain through virtual screening

Antiviral Research 144 (2017) 186e195

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Identification of influenza polymerase inhibitors targeting polymerase PB2 cap-binding domain through virtual screening Ming Liu a, Chun-Yeung Lo a, Guoxin Wang b, Hak-Fun Chow c, Jacky Chi-Ki Ngo a, David Chi-Cheong Wan d, Leo Lit-Man Poon e, Pang-Chui Shaw a, * a

Centre for Protein Science and Crystallography, School of Life Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China Research Center of Plasmonic and Near-Infrared Science, Research Institute of Tsinghua University in Shenzhen, Shenzhen, China Department of Chemistry, Center of Novel Functional Molecules and State Key Laboratory of Synthetic Chemistry, The Chinese University of Hong Kong, Hong Kong, China d School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China e School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 24 October 2016 Received in revised form 17 May 2017 Accepted 14 June 2017 Available online 16 June 2017

Influenza A virus is the major cause of epidemics and pandemics worldwide. In this study, virtual screening was used to identify compounds interacting with influenza A polymerase PB2 cap-binding domain (CBD). With a database of 21,351 small molecules, 28 candidate compounds were tested and one compound (225) was identified as hit compound. Compound 225 and three of its analogs (225D1, 426 and 426Br) were found to bind directly to PB2 CBD by surface plasmon resonance (SPR). The evaluation of compounds 426Br and 225 indicated that they could bind to PB2 CBD and inhibit influenza virus at low micromolar concentration. They were predicted to bind the cap binding site of the protein by molecular modeling and were confirmed by SPR assay using PB2 CBD mutants. These two compounds have novel scaffolds and could be further developed into lead compound for influenza virus inhibition. © 2017 Elsevier B.V. All rights reserved.

Keywords: Virtual screening Influenza Inhibitors PB2 cap-binding domain

1. Introduction Influenza is a contagious disease that causes annual epidemics and occasional pandemics. It results in about 3e5 million cases of severe illness and about 250,000 to 500,000 deaths annually. Despite the improvement of the healthcare and treatment, the severity of influenza cannot be underestimated. The use of antivirals can curtail influenza infections. However, drug resistance is emerging as a significant problem, as some circulating influenza strains were found to be resistant to common antivirals used to treat influenza. (Abed et al., 2005; Dharan et al., 2009; Hayden and de Jong, 2011). Viral proteins such as HA, N1, M2, NS1, polymerase proteins (PA, PB1, PB2) and host proteins such as inosine 5'-monophosphate (IMP) dehydrogenase (Sidwell et al., 1972; Robins et al., 1985; Loregian et al., 2014) have been targets for antiviral development. Among these, PB2 CBD has several advantages. Firstly, it has a well-defined structure and function.

* Corresponding author. School of Life Sciences, The Chinese University of Hong Kong, Hong Kong, China. E-mail address: [email protected] (P.-C. Shaw). http://dx.doi.org/10.1016/j.antiviral.2017.06.009 0166-3542/© 2017 Elsevier B.V. All rights reserved.

Secondly, the inhibition of this domain suppresses viral growth effectively as it is involved in the transcription of viral proteins. Thirdly, the conserved parts in PB2 are expected to be less prone to mutations compared to surface proteins such as HA or NA. Therefore, inhibitors of PB2 CBD are expected to be effective against diverse influenza strains. The PB2 CBD is located in the N-terminal region of the PB2 subunit (aa 318e483). It binds the 5’-capped end of host pre-mRNA, which are cleaved by the PA endonuclease after which the 5’-capped primer is used for transcription of the viral genome by the viral PB1 polymerase (Guilligay et al., 2008). The site is also responsible for interaction with acetyl-CoA, similar to eukaryotic histone acetyltransferases (HATs) (Hatakeyama et al., 2014). In this study we aim to identify influenza inhibitors targeting influenza PB2 CBD by computational virtual screening. Among the 21,351 molecules screened, 28 candidates were obtained for testing by surface plasmon resonance, RNP inhibition assay and plaque reduction assays. We have identified two hit compounds (225, 426Br) with novel scaffolds that inhibit influenza virus at low mM range. These novel hit compounds could provide new directions for further antiviral development.

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2.5. Screening the molecular database with Autodock Abbreviations CBD CD HATs IMP m7GTP NA RNP RU SPR SVM

cap-binding domain circular dichroism histone acetyltransferases inosine 50 -monophosphate 7-methylguanosine triphosphate neuraminidase ribonucleoprotein resonance unit surface plasmon resonance support vector machine

2. Material and methods 2.1. Cells and viruses Human kidney 293T and MDCK cells were cultured in Dulbecco's Modified Eagle Medium (DMEM, Gibco) supplemented with 10% (v/v) fetal bovine serum (FBS, Gibco) at 37
C in 95% O2/5% CO2 incubator. Influenza B/Florida/06 was from Prof. Wendy S. Barclay at Imperial College London, UK.

2.2. Plasmids and primers The plasmids pcDNA-PB1(A), pcDNA-PB2(A), pcDNA-PA(A), pcDNA-NP(A) and pPOL-NS-Luci expressing corresponding RNA polymerase subunits of influenza A/WSN/1933(H1N1) for RNP reconstitution were from Dr. Leo L. M. Poon at the University of Hong Kong (Li et al., 2009). The gene encoding PB2 CBD (aa. 318e483) were cloned from the PB2 (A/WSN/1933(H1N1)) (GenBank accession: CY034139) and inserted between the NdelI and NotI site of PET28A (Novagen). Mutations were introduced using Q5 mutagenesis kit (New England Biolabs).

2.3. Preparation of protein receptor The crystal structure of influenza A H3N2 PB2 CBD (pdb code: 2VQZ, Chain A) was chosen as the protein receptor. The macromolecule pdbqt file of the protein was generated by AutodockTools Module (Scripps) (Goodsell et al., 1996). A grid box centered in x: 45.986; y: 23.809; z: 31.059 with the size of x: 34; y: 34; z: 46 was set on the active site with 0.375 Å spacing for docking with Autodock. The position and size of the box were obtained from the prediction of Ligsite (http://projects.biotec.tu-dresden.de/pocket/) (Huang and Schroeder, 2006). Corresponding atom maps for the receptor atoms were created by python script autogrid4 (Goodsell et al., 1996).

2.4. Analysis of the binding site The ligand binding pocket of the structure of PB2 CBD was predicted with DoGSiteScorer (http://dogsite.zbh.uni-hamburg.de/ ) (Schmidtke and Barril, 2010; Volkamer et al., 2010, 2012) and LIGSITEcsc (http://projects.biotec.tu-dresden.de/pocket/) (Huang and Schroeder, 2006). For DoGSiteScorer, 2VQZ.pdb was uploaded to the server with m7GTP as a ligand for reference. For LIGSITEcsc, the 2VQZ.pdb was uploaded to the web server, the grid-space of 1 Å and the radius of probe to get potential binding sites were set to 5 Å.

The SPECS pre-plated library, containing a total number of 21,351 molecules was downloaded from the ZINC website in 3D mol2 format (http://zinc.docking.org/catalogs/specs). The chemicals were filtered by the Lipinski's rule-of-five (Lipinski et al., 2001). The docking process was performed by Autodock 4.2 (Goodsell et al., 1996). The docking parameters were set as follows: ga_num_evals ¼ 1200000; ga_pop_size ¼ 120; ga_run ¼ 12; rmstol ¼ 2.0. All the docking results were scored according to the implemented empirical binding free energy function. The docking results were ranked according to the scores of the lowest binding energy and population of that conformation cluster. The top scoring chemicals were selected for visual inspection of their predicted binding position, where shape complementarity, number of hydrogen bonds formed, number of pi-pi stacking interactions formed, whether both polar and non-polar interactions were included, the proximity to critical residues were considered. 2.6. Purification of PB2 CBD The PB2 CBD (WSN/1933(H1N1)) (aa. 318e486) was expressed in E. coli BL21 (DE3) plysS strain. The soluble fraction of the cells was loaded to a His-Trap column with binding buffer (20 mM TrisHCl, 500 mM NaCl, 20 mM imidazole, pH 8.0), and eluted with elution buffer (20 mM Tris-HCl, 500 mM NaCl, 500 mM imidazole, pH 8.0). The His-tag was proteolytically removed by thrombin (Sigma). The protein was subsequently purified by gel filtration chromatography to >95% purity, as assessed by polyacrylamide gel electrophoresis. The protein was concentrated by ultra-filtration using Amicon Ultra-15 Centrifuge Filter Units (Millipore) with 10,000 MWCO at 4000 rpm at 4
C. 2.7. Circular dichroism (CD) assay The CD spectrum was measured by JASCO J-810 CD spectrometer. The system was purged and equilibrated with nitrogen gas for 20 min at a pressure of 15e20 kPa in the LRM AIR flow meter at 25
C. The protein samples were diluted to 0.1e0.3 mg/ml in PBS. The samples were filled in 110-QS Hellma 350 ml Quartz cuvette 1 mm light path and scanned from 190 to 260 nm. The CD (mdeg) and HT (V) with corresponding wavelengths were recorded. 2.8. Surface plasmon resonance assay BIAcore 3000 surface plasmon resonance biosensor (Pharmacia Biosensor AB) was performed to measure the interaction between PB2 CBD and candidate chemicals. BIAcore 3000 was run by the BIA3000 Control Software and data analysis was carried out by the BIAevaluation Software. Purified PB2 CBD was diluted to 50 ng/ml by immobilization running buffer (20 mM HEPES, 500 mM NaCl, 0.5% DMSO, pH ¼ 7.4) and was immobilized onto CM5 sensor chips using Amine Coupling Kit (Pharmacia). 50 ng/ml PB2 CBD was then injected into the flow cell at 5 ml/min until around 8000 Resonance Unit (RU) was obtained. The chip was equilibrated with running buffer (20 mM Tris HCl, 500 mM NaCl, 1% DMSO, pH ¼ 7.4) before measurement. For rapid evaluation, candidate compounds were injected into the sensor chip at concentrations of 10 mM at a flow rate of 30 ml/ min for 60 s. The SPR responses at report point 2 were recorded. The binding surface was regenerated by 25 mM NaOH, 50 mM NaCl. Shortlisted compounds were serially diluted in running buffer and injected onto the sensor chip surface. The binding affinity was

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Fig. 1. Results of the first round of screening. A. The SPR responses of the 28 compounds from the first round of screening. m7GTP (1 mM) was used as a positive control and 10 randomly selected compounds as negative controls. B. Inhibition of RNP activities (Shown by luciferase signals) of the eight compounds shortlisted by SPR experiments. (***: P < 0.001, **: P < 0.01, *: P < 0.05).

calculated by BIAevaluation software using 1:1 Langmuir binding model. 2.9. Cytotoxicity assay of 293T and MDCK cells Cytotoxicity of candidate compounds was assessed by 3-(4,5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Cells were treated with various concentrations of testing compounds for 24 h (with 293T cells) or 72 h (with MDCK cells). After treatment, 20 ml of MTT solution (5 mg/ml MTT in phosphate buffered saline) per well was added and incubated at 37
C for 3 h. Then the medium was removed and followed by the addition of 100 ml DMSO to each well for solubilizing the formazan. Absorbance at 540 nm was read by a VICTOR 3 Multilabel plate reader (Perkin Elmer). The 50% cytotoxic concentration (CC50) was calculated as the drug concentration causing 50% cell death compared to the control.

were measured by a VICTOR 3 Multilabel plate reader (Perkin Elmer). The 50% effective concentration (EC50) was the drug concentration required to inhibit 50% of RNP activities as reflected by the luciferase activities. 2.11. Plaque reduction assay Confluent MDCK cells were seeded on 6-well plates. Cells were infected with around 100 pfu for 1 h. After washing with PBS twice, the cell layers were then overlaid with agar solution containing the chemicals and incubated at 37
C. After 72 h, the agar was removed and the cell layer was stained and fixed with staining solution (0.25% Coomassie blue, 10% acetic acid, 50% methanol). The number of plaques formed was counted. The 50% effective concentration (EC50) was the drug concentration required to inhibit 50% of influenza plaque formation. 3. Results

2.10. RNP reconstitution assay 2  106 293T cells were seeded on a 6 cm dish and incubated overnight. 1 mg of pcDNA-PB1(A), pcDNA-PB2(A), pcDNA-PA(A), pcDNA-NP(A), pPOL-NS-Luci (A) and pEGFP were transfected into 293T cells. Transfected cells were trypsinized and aliquoted into a 96 well-plate with candidate compounds at 5 h post-transfection. After 24 h, the cells were harvested. The fluorescent signals produced by the expression of GFP proteins and the luciferase signals

3.1. 28 compounds were selected from the database in the first round of screening by virtual screening and rational visualization The SPECS pre-plated library with 21,351 molecules was first archived. The library was filtered by the Lipinski's rule of five (Lipinski et al., 2001). Chemicals that fulfilled the filter requirements were docked to the target site by Autodock 4.2 and ranked according to their predicted binding energies. These

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Table 1 Structure and properties of shortlisted compounds. Compound

Chemical structure

KD (mM)e

SId

RNP assay EC50 (mM)a

Plaque reduction assay (PRA) EC50 (mM)b

vRNP (H1N1 (WSN))

H1N1 (WSN)

H1N1 (PR8)

H3N2 (HK68)

Flu B (B/Florida/06)

293T

MDCK

vRNP

PRA (based on WSN)

225

15.8 ± 5.0

3.8 ± 0.9

7.3 ± 2.2

3.5 ± 0.8

>12.5

>50

>50

>3.16

>13.16

4.2 ± 0.5

361

1.9 ± 0.4

>5

>5

>5

Not tested

10.3 ± 2.5

6.1 ± 0.5

5.42

N/A

Not tested

362

18.8 ± 7.4

>10

>10

>10

Not tested

>50

24.8 ± 3.7

>2.66

N/A

Not tested

225D1

30.0 ± 10.5

17.4 ± 5.8

9.2 ± 3.2

15.4 ± 4.0

Not tested

>100

>100

>3.33

>5.74

14.6 ± 4.7

426Br

23.7 ± 10.8

5.0 ± 1.1

8.4 ± 2.2

9.5 ± 3.0

Not tested

>100

>100

>4.22

>20

1.3 ± 0.3

426

26.4 ± 6.5

10.3 ± 1.6

8.8 ± 2.7

7.4 ± 1.4

Not tested

>100

>100

>3.79

>9.71

27.5 ± 3.3

Cytotoxicity CC50 (mM)c

Data were shown in mean ± SD of three independent experiments. a EC50: Effective concentration for 50% inhibition of RNP activities. Calculated by log(inhibitor) vs. normalized response - Variable slope model. b EC50: Effective concentration for 50% inhibition of influenza plaque formation. Calculated by log(inhibitor) vs. normalized response - Variable slope model. c CC50: Chemical concentration causing 50% cytotoxicity. Calculated by log(inhibitor) vs. normalized response - Variable slope model. d SI: Selectivity index of the chemicals. (vRNP refers to the ratio of CC50 of 293T cells to EC50 of vRNP; PRA refers to the ratio of the CC50 of MDCK cells to EC50 of H1N1(WSN)). e KD: Dissociation constant.

compounds have an average of estimated free binding energy of e6.86 kcal/mol with an SD of 1.15 kcal/mol for the distribution population curve of estimated free binding energy (Supplementary Fig. 1). m7GTP was included as a control to test the validity of the docking process. It had a low estimated free binding energy of 9.40 kcal/mol and ranked among the top 1.3%. The dominating docking pose is similar to that in the crystal structure (RMSD ¼ 0.5 Å) (Supplementary Fig. 2). This control experiment suggested that the docking procedure is able to accurately predict the binding pose of true substrate and is likely capable of selecting active compounds from a pool of chemicals. The top 4% of the molecules (897 molecules) were selected for visual examination. The cut off score was e8.5 kcal/mol. The predicted binding pose of each chemical was compared with the binding pose of m7GTP in the PB2 cap-binding pocket. LIGSITEcsc (http://projects.biotec.tu-dresden.de/pocket/) were used to predict key binding residues of PB2 CBD (Huang and Schroeder, 2006). The key residues predicted by LIGSITEcsc were also taken into consideration during visual inspection. As a result, 28 compounds with diverse structures were selected and purchased.

3.2. A system was developed for fast screening of potential compounds and activity determination in cells using surface plasmon resonance, RNP reconstitution and plaque reduction assay SPR has been shown to be an effective tool for drug screening (Perspicace et al., 2009; Lo et al., 2015). To measure the affinity of

the candidate compounds to PB2 CBD, each compound was allowed to flow over the sensor chip at the concentration of 10 mM for rapid screening. To test the reliability of this system, m7GTP was used as a positive control and 10 randomly selected compounds as negative controls to measure their responses toward the PB2 cap-binding domain. As shown in Fig. 1A, m7GTP binds CBD with 37.4 RU at 1 mM while the other 10 compounds bind CBD with low responses (RU < 10). A concentration dependent experiment determined the KD of m7GTP as 349 ± 9 mM, which is similar to previous findings (Guilligay et al., 2008). Compounds with over 30 RU were shortlisted. Fig. 1B showed their inhibitory effect towards RNP activities by the RNP reconstitution assay. The RNP reconstitution assay and plaque reduction assay were performed using various concentrations to determine the EC50s of active compounds. 3.3. 225 was identified as a hit compound in the first round of screening The SPR response of each compound in the first round of screening was recorded and shown in Fig. 1A. Eight compounds that elicited over 30 RU in SPR screening were shortlisted (Supplementary Fig. 3). Their effects on RNP activities were then tested at their maximum non-cytotoxic concentrations (Supplementary Table 1). Three compounds (225, 361 and 362) showed significant inhibition to RNP activities. Concentration

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dependent experiments were next performed and the EC50s of these compounds were shown in Table 1. As shown in the table, 225 could both inhibit RNP activities and suppress the growth of different influenza strains, albeit its inhibition on influenza B was not significant. At 12.5 mM, it could almost completely inhibit WSN virus in the PRA assay (Supplementary Fig. 4). Thus 225 was identified as a potential hit. On the other hand, compound 361 and 362 did not exhibit inhibitory activities against influenza virus. 3.4. Three compounds (426, 225D1 and 426Br) were identified in the second round of screening 45 analogs of compound 225 were obtained by purchase or synthesis. These compounds were tested using the same procedure. 15 compounds showed significant binding affinity (over 30 RU) towards PB2 CBD by SPR (Fig. 2A). They were further tested for their effect on RNP activity and three of them (426, 225D1, 426Br) exhibit inhibition of RNP activity (Fig. 2B). Their EC50s towards RNP activities and influenza strains are shown in Table 1. 3.5. Determining the dissociation constant (KD) of the chemicals by SPR Compounds 225, 225D1, 426 and 426Br showed inhibition to RNP activities and suppressed influenza virus replication. The dissociation constants (KD) of these chemicals were determined by

SPR (Table 1). The KD was fitted using the 1:1 Langmuir binding model. These chemicals showed mM binding affinity to PB2 CBD (KD ranging from 1.3 to 27.5 mM). 225 and 426Br have the lowest KD (4.2 ± 0.5 and 1.3 ± 0.3 mM) among these compounds. 3.6. Verifying the binding site and key binding residues The binding poses of 426Br and 225 were predicted by Autodock 4.2 (Fig. 3). For 426Br, the imidazolidine ring was stacked with residues His 357 and Phe 404 and formed two hydrogen bonds with Lys 361 and Phe 404. Its carboxyl group on the phenol ring extended to the outer of the pocket and formed two hydrogen bonds with Lys 339 and Arg 355 (Fig. 3A). Similarly, the tricyclc heteroaromatic ring of 225 was stacked between His 357 and Phe 404. At the other end, the carboxyl group on the phenyl ring formed a hydrogen bond with Arg 355 (Fig. 3C). The conformation of m7GTP was provided in Fig. 3B and D for comparison with the docking conformation of 426Br and 225. To examine whether the binding positions of the candidates were similar to their calculated binding pose, KDs of the most active compound 426Br and 225 with wild-type PB2 CBD and two variants (K339T-R355T and H357A-F404A) were determined and compared. These variants had a similar secondary structure to the wild-type, as confirmed by circular dichroism (Supplementary Fig. 5). The KD of 426Br with wild-type PB2 cap-binding domain (1.3 ± 0.3 mM) was lower than that with the variants (7.4 ± 0.9 mM

Fig. 2. Results of the second round of screening. A. SPR responses of the 225 analogs. B. Inhibition of RNP activities (Shown by luciferase signals) of the 15 compounds shortlisted by SPR experiments. (***: P < 0.001, **: P < 0.01, *: P < 0.05).

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Fig. 3. The predicted binding pose of 426Br and 225. A. Predicted binding pose of 426Br (Shown in stick representation). 426Br forms p-p stacking interactions with His 357 and Phe 404 and also forms four hydrogen bonds (shown in red dashes) with PB2 CBD. B. Predicted binding pose of 426Br compared to the actual binding conformation of m7GTP. C. Predicted binding pose of 225 (Shown in stick representation). 225 forms p-p stacking interactions with His 357 and Phe 404, and also forms one hydrogen bond (shown in red dashes) with Arg 355. D. Predicted binding pose of 225 compared to the actual binding conformation of m7GTP. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

and 3.6 ± 0.8 mM), suggesting that 426Br binds the wild-type protein better than the variants. Similar results were obtained for 225. The KD of 225 with wild-type PB2 CBD (4.2 ± 0.5 mM) was also lower than that with the variants (13.1 ± 2.3 mM and 76.5 ± 17.9 mM). It shows that these residues take part in interacting with 426Br and 225. It also supports the validity of the predicted docking pose. We have also tested on single-mutant variants (K339T and H357A), but no significant difference was observed among the KD of wild-type and these variants (data not shown). 4. Discussion 4.1. The screening workflow In this study, we have developed a workflow for identifying hit compounds targeting viral protein by virtual screening. Compounds from a virtual compound database were docked to the PB2cap binding site with Autodock 4.2, their predicted binding scores were ranked and their predicted binding poses were inspected. 28 compounds were obtained for biological evaluation. Their binding affinities were then determined with SPR. Their antiviral activities were further tested by RNP reconstitution assay and plaque reduction assay. m7GTP was used as a positive control in the docking and SPR screening to ensure the reliability of this screening system. The binding affinities of the compounds tested by SPR are consistent with their inhibitory effect tested by RNP inhibition assay. Among the 28 compounds tested in the first round of screening, 20 compounds showed no or low binding affinity towards PB2 CBD. Consequently, no inhibitory effect of these

compounds was detected in the RNP reconstitution assay (data not shown). On the other hand, three out of eight compounds that exhibited binding affinity towards PB2 CBD showed significant inhibition towards RNP activities. The remaining five compounds did not show inhibitory effects in cell-based experiments despite their in-vitro binding to PB2 CBD, this might be due to their poor cell penetration. Lastly, SPR with PB2 CBD variants was used to determine the actual binding position of the hit compounds. Variants were designed according to the predicted binding mode of hit compounds. In conclusion, this workflow allows us to identify virtual hits through in-silico virtual screening. These hit compounds were confirmed to attenuate RNP activities. They could inhibit viral replication and bind to PB2 CBD directly. Their binding positions were determined by SPR study with PB2 CBD variants. Although we have demonstrated the mechanism of action of these hit compounds, these compounds may also act on other viral or cellular targets and further investigation in this aspect is needed. 4.2. Development of PB2 CBD inhibitors PB2 CBD is a potential target for antiviral design. It binds the 5’capped end of host pre-mRNA during the cap-snatching process. The binding cavity has a volume of about 1270 Å3 and a surface area of 1580 Å2. We used DoGSiteScorer (http://dogsite.zbh.unihamburg.de/) and LIGSITEcsc (http://projects.biotec.tu-dresden.de/ pocket/) (Huang and Schroeder, 2006) to better characterize this binding cavity. DoGSiteScorer finds binding pockets on protein surfaces and evaluates their druggability by a support vector

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machine (SVM) model (Schmidtke and Barril, 2010; Volkamer et al., 2010, 2012). It predicted that the m7GTP-binding pocket had the highest druggable score (0.66, maximum ¼ 1) out of three pockets listed all over the protein surface. LIGSITEcsc predicts the binding pocket by solvent exposure of the surface, ranks them by size and lists the key binding residues in the pocket (Huang and Schroeder, 2006). It also predicted the m7GTP-binding pocket as the most promising one for the search of inhibitors. In our studies, 225 and 426Br were promising candidates, which could be developed into lead compounds targeting PB2 CBD. They both bind to the PB2 cap-binding protein with low dissociation constants. They also inhibited RNP activities and suppressed the growth of influenza virus at low mM range. Their inability to inhibit influenza virus B could be due to the dissimilarity between PB2 CBD of influenza A and B viruses, as B/Floria/06 and A/WSN/33 PB2 CBD have only 35.37% sequence identity.

In their predicted binding poses, they fitted well in the pocket of PB2 cap-binding protein (Fig. 2 A,C) and interacted with important residues such as Lys 339, Arg 355, His 357, Lys 361, Phe 404. The importance of these residues has been demonstrated by their involvement in the binding of the endogenous ligand m7GTP (Guilligay et al., 2008; Liu et al., 2013). Their docking positions were supported by SPR studies with PB2 mutants. The predicted binding pose of 426Br and 225 showed some similarities with endogenous ligand m7GTP. The imidazolidine ring of 426Br and the tricyclic heteroaromatic ring of 225 have a similar binding pose with the 7methylguanosine ring of m7GTP. The carboxyl group on the phenyl ring of 426Br and 225 forms hydrogen bonds with polar residues, in resemblance to the triphosphate chain of m7GTP, although the triphosphate chain makes a more extensive hydrogen bond contacts due to its flexibility and polarity. Several compounds have been reported to bind the PB2 cap-

Fig. 4. Chemical structures of all active compounds in comparison with VX-787. All compounds have a planar (or nearly planar) group that forms interactions with His 357 and Phe 404 at one end, and a negatively charged group which establishes polar contact with Lys 339 and Arg 355 at the other end.

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binding domain, such as m7GTP derivatives (Pautus et al., 2013), HAT inhibitors (anacardic acid, garcinol) (Hatakeyama et al., 2014). The most potent one up to date is VX-787, an azaindole derivative (Clark et al., 2014). It binds the PB2 cap-binding protein with a KD of 25 nM and inhibits influenza virus with an EC50 ranging from 0.13 to 3.2 nM. Moreover, the compound was orally bioavailable and its antiviral activity was tested in an in vivo mouse model (Byrn et al., 2015). The structure of VX-787 and our chemicals were compared in Fig. 4. These compounds all have a planar (or nearly planar) group, which interacted with His 357 and Phe 404. VX-787 binds to Lys 339 and Arg 355 by the negatively charged group (highlighted in grey) via the mediation of two crystallographic waters, while 426Br was predicted to bind to Lys 339 and Arg 355 directly (The distance between the carboxy group of 426Br and Lys 339, Arg 355 is about 3 Å). Despite some similarities in the binding mode of these

193

chemicals, our chemicals are distinctly different from VX-787. VX787 has a rigid structure and our chemicals are more flexible. Besides, the scaffolds of our chemicals are different from that of VX787. 4.3. Structure-activity relationship of 225 analogs A series of analogs were purchased or synthesized based on the structure of 225. By comparing the structures and activities of these compounds, we could obtain a better understanding of the structure-function relationship and common features of this active compound. The carboxyl group on position 2 of the phenol ring is critical for retaining binding affinity. As indicated by the arrows in Fig. 5A, changing the carboxyl group (CO2H) to CONH2 (225a1), CO2Me

Fig. 5. Structure-activity relationships of 225 analogs. A. 225 and some of its analogs revealed the importance of the carboxyl group on position 2 of the phenyl ring for retaining binding affinity. Changing the carboxyl group to CONH2 (225-a1), CO2Me (225-a2), Cl (225-W1) significantly reduces the binding affinity of the compound to the PB2 cap binding domain. B. Some of 225 analogs illustrating that bulky groups attaching to the heteroaromatic ring are important for activity. 448 (11.1 RU) has a lower affinity to PB2 cap-binding protein than 436 (113.9 RU) because 436 has a large phenyl group substituted at the 2-position of the 2-thioxo-1,3-thiazolidin-4-one ring.

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Fig. 6. Predicted binding pose of A. 448 and B.436. In B), the bulky phenyl group occupies the pocket formed by the 334e338 loop, while in A) the pocket is not occupied.

(225a2), or Cl (225W1) greatly reduced their binding affinities to PB2 CBD (225: 31.6 RU; 225a1: 9.7 RU; 225a2: 11.4 RU; 225W1: 17.9 RU). The importance of this carboxyl group can be explained by the predicted binding pose of 225. This carboxyl group forms a hydrogen bond with Arg 355. Removal of the carboxyl group attenuated or abolished this hydrogen bond interaction and resulted in a decrease in binding affinity. Compounds with bulky substitution groups substituted at the 2position of the 2-thioxo-1,3-thiazolidin-4-one ring (as indicated by grey arrow in Fig. 5B) may bind PB2 CBD with higher affinities. For instance, 448 and 436 have similar structures, and 436 has an additional N-phenyl group at the 2-position of the thiazolidinone ring. As a result, the activity of 448 (11.1 RU) is much lower than that of 436 (113.9 RU). Therefore either the addition of a N-phenyl ring or changing from an S atom to an N at the 2-position accounts for the activity differences. Comparing the predicted binding pose of 448 and 436 in Fig. 6, it is more possible that the bulky phenyl group of 436 took up the subpocket formed by aa. 334e338 (outlined by red circles), while 448 did not occupy this subpocket. In addition, other analogs, which have phenyl substituents attaching to the heterocyclic ring, also possess good activity (449 104.0 RU, 426 66.8 RU). 5. Conclusion Influenza virus has caused epidemics and pandemics worldwide. It is therefore important to develop inhibitors for combating the virus. In this study, a database of 21,351 molecules was virtually screened and 28 compounds were evaluated. Four compounds were identified to be effective in binding to the PB2 cap-binding protein and inhibiting influenza virus replication (225, 225D1, 426 and 426Br). The interactions between 225, 426Br and the PB2 cap-binding domain were further validated. In support of the docking hypothesis, SPR experiments with PB2 mutants showed that these compounds likely act on PB2-CBD through His 357, Phe404, Lys 339 and Arg 355. In summary, we have developed a screening workflow to discover novel inhibitors of the PB2 cap-binding domain. 426Br and 225 were identified as good hit compounds targeting the PB2 capbinding protein. The hit compounds have novel scaffolds and may serve to assist lead development of novel antiviral agents in the future. Acknowledgments This work was supported by a Health and Medical Research Fund (Project No. 13120052), an Area of Excellence Scheme (Project No. AoE/M-12/06) and a Theme-based grant (Project No. T11-705/

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