alexa Screening and Identification of Salicin Compound from Desmodium gangeticum and its In vivo Anticancer Activity and Docking Studies with Cyclooxygenase (COX) Proteins from Mus musculus
ISSN: 0974-276X
Journal of Proteomics & Bioinformatics

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Screening and Identification of Salicin Compound from Desmodium gangeticum and its In vivo Anticancer Activity and Docking Studies with Cyclooxygenase (COX) Proteins from Mus musculus

Preeti Srivastava1*, Vinay K Singh1, Brahma Deo Singh1, Gaurava Srivastava2, Bhuwan B Misra3 and Vyasji Tripathi3

1School of Biotechnology, Faculty of Science, Banaras Hindu University, Varanasi-221005, Uttar Pradesh, India

2School of Biochemical Engineering, Indian Institute of Technology, Banaras Hindu University, Varanasi-221005, Uttar Pradesh, India

3Department of Chemistry, Faculty of Science, Banaras Hindu University, Varanasi-221005, Uttar Pradesh, India

*Corresponding Author:
Preeti Srivastava
School of Biotechnology
Faculty of Science
Banaras Hindu University, Varanasi-221005
Uttar Pradesh, India
Tel: +91-9236060830
Fax: +91- 542-2368693
E-mail: [email protected]

Received date: March 18, 2013; Accepted date: May 27, 2013; Published date: May 30, 2013

Citation: Srivastava P, Singh VK, Singh BD, Srivastava G, Misra BB, et al. (2013) Screening and Identification of Salicin Compound from Desmodium gangeticum and its In vivo Anticancer Activity and Docking Studies with Cyclooxygenase (COX) Proteins from Mus musculus. J Proteomics Bioinform 6: 109-124. doi: 10.4172/jpb.1000269

Copyright: © 2013 Srivastava P, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Cancer continues to be a worldwide killer, despite the enormous amount of research and rapid developments seen during the past decade. It has been suggested that by 2020 more than 15 million new cases of cancer will be diagnosed. Since it is commonly believed that many are preventable, there is urgent need to identify/develop natural medicines as effective chemopreventive agents. The purpose of this current study was to assess the effect of isolated and characterized salicin on cyclooxygenase (COX) proteins by molecular docking studies and by assessments of the effects of drug-ligand interaction. Salicin isolated from Desmodium gangeticum, a medicinal legume, is a COX inhibitor. The present study report the extraction, isolation and identification of salicin and its interaction with COX-1 and COX-2 derivatives, which may be useful for drug-designing for anti-cancer activities. Molecular modeling and docking studies revealed the binding orientations of salicin into the active sites of COX-1 and COX-2 enzymes. Extraction, isolation and characterization of the compound 2-(hydroxymethyl) phenyl hexopyranoside, also known as ‘salicin’, from the leaves of D. gangeticum first time. Anticancer evaluation of salicin in in vivo mice model.

Keywords

Cyclooxygenase; Salicin; Docking; Molecular modeling; Functional motif; Anti-cancer; Desmodium gangeticum

Abbreviations

COX: Cyclooxygenase; nM: Nanomolar; NSAID: Nonsteroidal Anti-Inflammatory Drug; DG: Desmodium Gangeticum

Introduction

Plants have been utilized as medicines for thousands of years [1], initially as crude drugs like tinctures, teas, poultices, powders and other herbal formulations [1,2]. The identity medicinal plants and the methods of their use were passed down through oral history, but eventually this information was recorded in herbals, and subsequently active compounds were isolated beginning with morphine from opium in the early 19th century [1,3], followed by cocaine, codeine, digitoxin and quinine [1,4,5]. Isolation and characterization of pharmacologically active compounds from medicinal plants continue today, and drug discovery techniques are now being used to standardize herbal medicines and to elucidate analytical marker compounds. Methods used to acquire compounds for drug discovery include isolation from plants and other natural sources, chemical synthesis, combinatorial chemistry and molecular modeling [6-8]. Drug discovery from medicinal plants has contributed to cancer treatment, and most new clinical applications during the last half century relate to cancer [4,5,9]. By 2020, approximately 15 million new cancer cases will be diagnosed, and 12 million these patients will die [10]. Cancer is caused by both internal factors such as inherited mutations, hormones, and immune conditions, and environmental/acquired factors like tobacco, diet, radiation, and infectious organisms [11]. The attractiveness of natural compounds as drugs partly stems from their potential ability to influence multiple components of the carcinogenesis pathway.

Natural products are typically isolated in quantities insufficient for lead optimization, lead development, and clinical trials. Therefore, possibilities of their synthesis or semi-synthesis need to be explored [8,12]. In addition, libraries of natural products and natural-productlike compounds including their features important for combinatorial chemistry may be created [13-15].

There are two well established isoforms of the cyclooxigenase (COX) enzyme that differ in their distribution in the body and in physiological function. COX-1 is constitutively expressed in normal tissues and it is involved in maintaining mucosal integrity, platelet aggregation and gastric cytoprotection [16]. In contrast, COX-2 is not expressed in normal mucosa, but is expressed very early in response to neoplastic and inflammatory stimuli, and is extensively overexpressed in different neoplasms, making it an attractive therapeutic target. Besides the role of COX-2 in the production of inflammatory prostaglandins, its momentous participation in the initiation/propagation of cancer [17-21] and in the development of multidrug resistance is well explored [22,23]. Over-expression of COX-2 probably occurs from the first genetically altered cell, through hyperplasia, dysplasia, carcinoma, and even metastasis of colorectal cancer [24-26]. Number of nonsteroidal anti-inflammatory drugs (NSAIDs) and selective COX-2 inhibitors have been investigated for anticancer activities [27-31].

Pharmacological inhibition of COX can provide relief from inflammation and, as a result, from pain. Non-steroidal antiinflammatory drugs, such as aspirin and ibuprofen, exert their effects through inhibition of COX. Turmeric, ginger, boswellia, hops and some plants exert their anti-inflammatory influences through inhibition of COX-2.

Desmodium gangeticum (L.) DC commonly known as shalparni or Ticktree is a member of Fabaceae, and is used in ‘Ayurvedic’ preparations like ‘Dashmoolarishta’ and ‘Dashmoola kwaath’ for the post-natal care to avoid secondary complications. In Indian system of medicine it is used as a bitter tonic, febrifuge, digestive, anticatarrhal, antiemetic, in inflammatory conditions of chest and various other inflammatory conditions due to vata disorder [32,33] and in treatment of abscess, acne, cataract, dysentery, eye diseases, infections and liver diseases [34]. Aqueous extract of this plant exhibits anti-inflammatory, severe antiwrithing activity, moderate central nervous system (CNS) depressant activity as well as antileshmanial, antibacterial and antifungal activities [34-38]. The ethanolic extract acts as a potent antiulcer agent in all models, mainly more due to its cryoprotective effect than anti-secretory effects [39]. The extracts show wound healing potential and antidiabetic activity [40,41]. D. gangeticum is reported to contain alkaloids, pterocarpenoids, flavones and isoflavanoid glycosides [42], and is supposed have anti-oxidant activities in its aerial parts [43]. The sterols N, N-dimethyltryptamine, 5-methoxy-N, N dimethyltryptamine, their oxides and other derivatives have been isolated from aerial parts [44]. Gangetin, a pterocarponoid from D. gangeticum has been sown to posse’s anti-inflammatory and analgesic activities [45].

White Willow Bark and Meadowsweet are sources of salicin, which has analgesic as well as anti-inflammatory properties. Salicylic acid, released from Salicin in the body, provides anti-inflammatory and painrelieving actions [46], and the same COX-2 inhibition properties as aspirin, but unlike aspirin it does not function as an anticoagulant [47]. Salicin from white willow bark extract showed modest effectiveness in treating pain associated with knee and/or hip osteoarthritis [48] and back pain [49], when administered over a period of weeks in dose of up to 240 mg/day.

Our main objective is to optimize Salicin as a specific inhibitor of COX-1 and COX-2 enzymes in the hope that this molecule may be further explored as novel anticancer, especially anti-colorectal cancer, lead-candidates. As in our other report under in vivo condition salicin is proved a potent anticancer drug. Our strategy is intended to obtain selective inhibition of COX-2 using traditional medicinal chemistry techniques motivated by the comparative modeling of a COX-1 and COX-2 complexed with Salicin together with the available pharmacophore. The modern modeling and docking programs/ software packages e.g. Discovery Studio module DS Modeler, Docking Server and Q-site Finder have been used to determine the active sites of COX-1 and COX-2 proteins. The structure of ligand against this active binding site can be found by Q-site Finder. The exact conformation and configuration of the ligand can be calculated to find the best molecule with minimum binding energy and it can be used to develop potential drug molecules against the disease. This knowledge may be important for the development of novel therapies for the treatment of infectious and other viral diseases in the future.

Materials and Methods

Plant material

The plant D. gangeticum was collected in the month of Nov 2008 from Ayurvedic Garden, Institute of Medical Sciences, B.H.U, Varanasi. This plant occurs naturally on the lower hills and in the plains throughout India. The plants were taxonomically authenticated at the site and collected locally and from surrounding areas as well as from the ayurvedic garden of Banaras Hindu University, Varanasi.

Isolation of Salicin

Dry and finely powdered leaves (5 kg) of D. gangeticum were extracted with methanol (6×5 L) for 36 h using a Soxhlet apparatus at 60-70°C. The residue (536 g) obtained after in vacuo concentration was further fractionated in n-hexane (2 L×2), chloroform (1 L×1), and ethyl acetate (1 L×3) using a mechanical stirrer followed by concentration under reduced pressure to afford crude residue of 152 g, 34 g and 92 g, respectively (Figure 1). Systematic chemical investigation of the methanolic leaf extract enabled isolation of known glycoside, 2-(hydroxymethyl)phenyl hexopyranoside (DG-1), also known as ‘salicin’ which is conventionally isolated from the willow bark [50]; this is the first report of isolation of salicin from leaves of D. gangeticum.

proteomics-bioinformatics-gangeticum

Figure 1: Extraction of D. gangeticum leaves.

Ligand optimization

Salicin is a glycoside, which acts as a precursor for the synthesis of acetyl salicylic acid. For ligand molecule, the structure of salicin, SDF file was retrieved from PubChem site (http://www.ncbi.nlm. nih.gov/pccompound). Salicin.sdf file was converted into PDB file using Discovery Studio visualize and geometry was cleaned by ‘clean geometry’ menu of Discovery Studio 3.0 and saved for further computational analysis. This retrieved ligand file was imported to the Docking Server program for docking with COX-1 and COX-2 proteins of Mus musculus obtained from NCBI database sequence (http://www. ncbi.nlm.nih.gov/) for homology modeling using Discovery Studio 3.1 DS Modeler.

3D Preparation of receptor molecule

The amino acid sequence of COX-1 and COX-2 was used to search template structure using PDB Database (http://www.pdb.org/pdb/ home/home.do). After getting the templates 1CQE with 85% similarity for COX-1 and 1CVU with 97% similarity for COX-2 (Figure 2), they were taken for homology modeling using Discovery Studio 3.1 module DS MODELER [51].

proteomics-bioinformatics-superimposition

Figure 2: Superimposition of docked model with crystal structures for (a) COX1 (1PTH) structure with HEME (protoporphyrin ix containing FE) ligand and (b) COX2 (1CVU) structure with BOG (b-octylglucoside) ligand.

Energy minimization

The 3D modeled structures of COX-1 and COX-2 were used for energy minimization using CHARMm force field based on Conjugate Gradient (CONJ) method that exhibits better convergence than the steepest descent method.

Validation of the modeled protein structures

The validity of protein models was tested using DS Protein Health tool, which verifies a protein structure derived from modeling studies or experimental methods. Profiles-3D Verify program based on Kabsch-Sander method was used to evaluate the likelihood that an amino acid should be present within its current environment. It allows us to browse and correct a suggested list of structural violations, which are mapped and colored to the 3D structure. Then CHARMm-based structural refinement of loops and side chains was performed using DS Protein Refine tool. LOOPER algorithm was used for loop refinement that quickly generated energy optimized variants of the structure and provided a list of proposed loop conformations that have been scored using the CHARMm Energy function. The stereochemical quality of modeled protein was checked by Ramchandaran plot provided by online PDBsum analysis. Model quality assessment was done using RAMPAGE (http://mordred.bioc.cam.ac.uk/). Qmean server (http://swissmodel.expasy.org/qmean/cgi/index.cgi) and quantitative evaluation of protein structure quality were done with VADAR (Volume, Area, Dihedral Angle Reporter) server (http://vadar. wishartlab.com/).

Calculating the active site sequence

Active site analysis was done using ‘detect cavity’ function of Q-site Finder (http://www.modelling.leeds.ac.uk/qsitefinder/). It is an energybased method for the prediction of protein-ligand binding sites.

Sequence alignment and conserved motif prediction:

COX-1 and COX-2 from M. musculus were taken for sequence alignment with homologues from other organisms, viz., Rattus norvegicus, Oryctolagus, Homosapiens, Pongoabelii, Monodelphis domestica, Ornitho rhynchusanatinus, Anoliscarolinensis, Xenopustropicalis, Taenio pygiaguttata, Meleagrisgallopavo, Gallus gallus (Figure 3) and distribution of conserved motifs were identified by means of MEME (http://meme.sdsc.edu).

proteomics-bioinformatics-phylogenetic

Figure 3: Phylogenetic inference of (a) COX1 and (b) COX2 proteins among different species based on UPGMA method using MEGA5.0.

Docking

The binding of ligand molecule with the COX-1 and COX- 2 protein molecules was performed using Docking Server (http://www.dockingserver.com/web) and SwissDock (http://swissdock.vital-it.ch/), which integrates a number of computational chemistry software specifically aimed at correctly calculating parameters needed at different steps of the docking procedure, i.e., accurate ligand geometry optimization, energy minimization, charge calculation, docking calculation and protein-ligand complex representation, and high-quality docking based on a novel optimization technique combined with a user interface experience focusing on usability and productivity. Its advanced visualization and analysis examined ligandreceptor interactions and finely tuned the docking solutions. Docking calculation, coordination and interaction were done using Discovery Studio 3.1.

Transplantation of tumor

EAC cells were obtained from National Centre for Cell Sciences (NCCS), Pune, India. The EAC cells were maintained in vivo in female Swiss albino mice (22-25 g) by intraperitoneal transplantation of 2×106 cells per mouse after every 10 days. Ascitic fluid was drawn out from EAC tumor bearing mice at the log phase (days 7–8 of tumor bearing) of the tumor cells. Each animal received 0.1 ml of tumor cell suspension containing 2×106 tumor cells intraperitoneally.

Treatment schedule

Swiss albino mice were divided into 5 groups (n=20) and were injected with EAC cells (2×106 cells/mouse) intraperitoneally except for the normal group. This was taken as day zero. On the first day normal saline (0.85%, w/v, NaCl) 5 ml/kg/mouse/day i.p. served as Group-I and EAC control (without any treatment) served as Group-II. salicin at 100 mg/kg body weight/day in Group-III and at 200 mg/kg/day in group IV, and the standard drug 5-Flurouracil (5-FU) at 20 mg/kg/day was injected in Group-V. After twenty-four hours from the last dose and 18 h of fasting, 10 animals of each group were sacrificed by cervical dislocation to measure antitumor and hematological parameters. The rest of the animals of each group were maintained to assess their lifespan, and they were provided food and water ad libitum. The effect of isolated and characterized salicin on tumor growth and host’s survival time were examined by studying the parameters like tumor volume, tumor cell count, mean survival time, increase in lifespan of EAC bearing mice.

Antitumor and hematological parameters

At the end of the experimental period, the next day after an overnight fasting blood was collected from freely flowing tail vein and from eye and used for the estimation of hemoglobin (Hb) content, red blood cell (RBC) count and white blood cell (WBC) count and differential count of WBC. Along with ascitic fluid was collected from the peritoneal cavity for tumor volume, tumor weight, percentage increase in life span, tumor cell count, viable/nonviable tumor were measured.

Results

Cancer is one of the life-threatening diseases, and identification of active drug targets against proteins involved in cancer like COX is of great interest. Medicinal compounds like Salicin have antiinflammatory activity, due to which they may serve as an active drug target against many toxic/pathogenic proteins like COX-2 in our study. Interaction of COX proteins with drugs like aspirin and ibuprofen shows pharmacological inhibition of this protein and thus relieve many symptoms of inflammation and pain. Salicin is found to be as active drug target in our study as it shows inhibition of COX-1 and particularly COX-2, indicated that it may be useful in chemoprevention of some cancers like colorectal cancer. The detailed results are discussed here.

Isolation and identification of salicin

Leaf extracts of D. gangeticum showed the active compounds. The sapogenin (DG-HY), obtained after hydrolysis of compound DG-1 was crystallized from CH2Cl2-EtOH to yield white plates (10 mg, m.p. 83-85°C). In 300 MHz 1H NMR spectrum recorded in CDCl3 (Figure 4), the sapogenin (DG-HY) exhibited four aromatic proton resonance signals. A 1, 2-disubstituted benzene ring was evident from the signals observed at δ 7.05 (1H, d, J=7.5) for H-3, 7.22 (1H, m) for H-5, 6.91 (1H, m) for H-4 and 6.86 (1H, d, J=7.5) for H-6. Signal characteristic to phenolic hydroxyl group was observed at δ 7.19, while a broad singlet for aliphatic hydroxyl group at δ 2.17 and a methylene singlet at δ 4.88 evidenced the presence of hydroxyl methyl side chain in the sapogenin DG-HY.

proteomics-bioinformatics-compound

Figure 4: 1H NMR spectra (300 MHz) of compound DG-HY.

The 75 MHz 13C NMR spectrum (Figure 5) of DG-HY recorded in CDCl3 showed a total of seven carbon resonance signals i.e. (>C x 2, >CH- x 4, >CH2 x 1). The two carbon resonances at δ 155.9 and δ 124.6 were assigned for C-1 and C-2, respectively. The signal for hydroxyl methylene resonance was observed at δ 64.5, while the signals at δ 127.8, δ 120.0, δ 129.4 and δ 116.4 were identified for tertiary carbons C-3, C-4, C-5 and C-6, respectively.

proteomics-bioinformatics-compound

Figure 5: 13C NMR spectra (75 MHz) of compound DG-HY.

Finally, the compound DG-1 was identified as 2-(hydroxymethyl) phenyl hexopyranoside, also known as ‘salicin’, on the basis of comparison of physical (melting point and elemental analysis) and spectroscopic data (UV, IR, 1H NMR, 13C NMR and mass spectra) to literature reports [52-55]. In the absence of an authentic sample, a direct comparison was not possible. This is the first report of isolation of salicin, from leaves of D. gangeticum.

Ligand properties computed from structure

Salicin (C13H18O7) (Figure 6) has molecular weight of 286.27782 [g/ mol], having 5 donor and 7 acceptor H-bonds. The monoisotopic mass is 286.105253. The table 1 described all the properties of Salicin compound. IUPAC Name of this compound (2R,3S,4S,5R,6S)-2-(hydroxymethyl)- 6-[2-(hydroxymethyl)phenoxy]oxane-3,4,5-triol with Canonical SMILES: C1=CC=C(C(=C1)CO)OC2C(C(C(C(O2)CO)O)O)O and Isomeric SMILES: C1=CC=C(C(=C1)CO)O[[email protected]]2[[email protected]@H]([[email protected]] ([[email protected]@H]([[email protected]](O2)CO)O)O)O. Retrived Chemical compound (CID_439503) total MMFF94 energy was 62.975 and shape volume was 207.7 obtained from Discovery Studio 3.1. To evaluate better drug likeness within the limits proposed by Lipinski’s rule of five, salicin compound have follows molecular weight, number of hydrogen donor and acceptors bonds according to rule.

proteomics-bioinformatics-visualized

Figure 6: Salicin (a) 2D and (b) 3D view were visualized using PubChem 3D Viewer 2.0 (http://pubchem.ncbi.nlm.nih.gov/pc3d/) and Discovery Studio 3.1 vizualizer.

Characteristics Properties
Molecular weight 286.27782 [g/mol]
Molecular formula C13H18O7
H-bond donor 5
H-bond acceptor 7
Exact mass 286.105253
Monoisotopic mass 286.105253
Topological polar surface area 120
Covalently-bonded unit count 1
Feature 3D acceptor count 7
Feature 3D donor count 5
Feature 3D ring count 2
Effective rotor count 5.2
Conformer sampling RMSD 0.8

Table 1: Ligand properties of salicin for drug targeting.

Model Details

Homology modeling

The three dimensional structures for COX-1 and COX-2 proteins were constructed using PDBID 1CQE X-ray diffraction with resolution of 3.10 Å with E-Value: 0.0 and Score 2596, Identity 84%, Positivity 89% for COX-1 and PDBID 1CVU X-ray diffraction with resolution of 2.40 Å with E-Value 0.0, Score: 2882 Identity 97%, Positivity 97% for COX-2. Based Template 1CQE for COX-1 and 1CVU for COX-2 was used for model construction using homology modeling tool DS MODELER (Figure 7). The Predicted 2D and 3D structures provide valuable insight into functional regulatory region in secondary elements and also enable the identification of possible interaction site for a suitable inhibitor. Among the three conformations generated the one with the least modeller objective function value was considered to be thermodynamically stable and was chosen for further refinement and validation.

proteomics-bioinformatics-minimization

Figure 7: Based on the structural alignment of the amino acid sequence of the (a) COX1 and (b) COX2 proteins, a theoretical model was obtained. The final 3D structures were obtained after energy minimization. The α-helix is represented by red cylinders, β-sheet by cyan arrows and loops by grey lines. The figure was generated using DS Visualizer.

Based on the structural alignment of the amino acid sequences of the COX-1 and COX-2, a theoretical model of these proteins was obtained, corresponding with amino acid residues 34–586 for COX-1 and residues 18-569 for COX-2 of the primary structure (Figure 8).

proteomics-bioinformatics-annotation

Figure 8: The two dimensional structure annotation of (a) COX1 and (b) COX2 protein molecules from M. musculus. The α-helices, β-sheets and coils are indicated in the figure generated using PDBSum.

Evaluation and refinement

The rough models for COX-1 and COX-2 were subjected to energy minimization using conjugate gradient algorithm with maximum steps 200 and RMS gradient 0.1 to eliminate bad contacts between amino acid atoms using simulation tool of Discovery Studio 3.1. The backbone conformation of the rough model was inspected using the Phi/Psi Ramchandaran plot obtained in the PDBSum server (http://www.ebi.ac.uk/pdbsum/). The results of Ramchandaran plot indicate that the rough model generated for COX-1 had no residue in the disallowed region whereas that for COX-2 had two residues, viz., Glu384 and Ser482, in the disallowed region, occurring in the loop. Loop refinement was done using looper and CHARMm based molecular mechanics to generate multiple energy optimized variants of the selected segments of the protein structure. Side chain refinement was done using chi-rotator, a CHARMm based energy minimization, a routine tool to optimize the conformation of the selected amino acid side chain atoms (Table 2).

Before energy minimization for COX-1 (Kcal/mol) After energy minimization for COX-1 (Kcal/mol) Before energy minimization for COX-2 (Kcal/mol) After energy minimization for COX-2 (Kcal/mol)
-15095.82367 -34857.28680 -19369.215661 -35925.71513

Table 2: Discovery Studio energy values for COX-1 and COX-2 proteins.

The Ramchandaran plot statistics showed that 89.9% residues were in the most favored regions with Φ and Ψ angles in the core of favored regions and 10.1% of residues were in additional allowed regions for COX-1, while for COX-2 90.7% residues were in the most favored regions and 9.3% of the residues occurred in additional allowed regions (Figure 9). This result was also verified by RAMPAGE server (http:// mordred.bioc.cam.ac.uk/~rapper/rampage.php). There are no residues either in the generously allowed region and or in disallowed region in COX-1 and COX-2 had two residues, viz., Glu384 and Ser482, in the disallowed region, after evaluation and refinement.

proteomics-bioinformatics-ramachandran

Figure 9: Ramachandran plots of COX1 and COX2 proteins built using Discovery Studio 3.1 software. The plot calculations on the 3D model of COX proteins were computed with the PROCHECK server.

Model quality estimation

ProSA-web server (https://prosa.services.came.sbg.ac.at/prosa. php) shows overall model quality by comparing the potential of mean forces derived from a large set of known NMR and X-ray deciphered structures of similar sizes and group. The model quality assessment is graphically presented in form of Z score; in our study Z scores were found to be −8.86 and −9.23 for COX-1 and COX-2 respectively, suggesting the model being within the permissible range of native conformational structures.

QMEAN server (http://swissmodel.expasy.org/qmean/cgi/index. cgi), model quality estimation, was used to analyze QMEAN score, residue error, energy profiles and plot and volume area dihedral angle for fractional accessible surface area, residue volume, 3D profile and stereo/packing quality index were done with VADAR (http://vadar. wishartlab.com/). QMEAN and VADAR were specially designed for quantitative and qualitative assessment of protein structures determined by X-ray crystallography, NMR spectroscopy, 3D-threading or Homology modeling. QMEAN score of the whole model reflecting the predicted model reliability range from 0 to 1. In this study, the predicted COX-1 model QMEAN score was 0.654 with global scores estimated absolute quality Z-score of -1.32; these results show that the model is reliable. Fractional accessible surface area volumes of all residues close to 1.0 ± 0.1, statistics of hydrogen bonds of predicted model show equal to expected mean H bond distance score of 2.2 sd=0.4 equal to the expected value, Mean H bond energy observed -1.7 sd=1.1 close to the expected -2.0 sd=0.8. Dihedral Angles were observed close to the expected, Total Accessible Surface Area score 23870.3 Angs**2 with expected score 20013.5 Angs**2, Total volume (packing) score observed 85910.2 Angs**3 with expected 77534.2 Angs**3, Stereo/Packing, 3D quality index results show no error residues in the predicted model. In this predicted COX-2 model QMEAN score 0.603 with global scores estimated absolute quality Z-score of -1.94 indicate that the model is reliable. Fractional accessible surface area volumes of all residues is close to 1.0±0.1, statistics of hydrogen bonds of predicted model is equal to the expected mean H bond distance score of 2.2 sd=0.4, Mean H bond energy observed was -1.7 sd=1.1 that is closes to the expected -2.0 sd=0.8. Dihedral Angles were observed to be closes to the expected, Total Accessible Surface Area score was 23652.7 Angs**2 with expected score of 19948.1 Angs**2, Total volume (packing) score was observed 83467.8 Angs**3 with expected of 77179.1 Angs**3, Stereo/Packing, 3D quality index results shows that no error residues occur in the predicted model. After complete reliability test based on quantitative and qualitative assessment, the predicted Models of COX-1 and COX-2 from M. musculus were deposited in Protein Model Database (PMDB) with PMDBID PM0077492 (http://mi.caspur.it/PMDB/user/model_ info.php?id=77492) and PM0077493 (http://mi.caspur.it/PMDB/user/ model_info.php?id=77493), respectively.

Superimposition of the 3D predicted model with template were done with Combinatorial Extension (CE) Method based server (http:// cl.sdsc.edu/). The superimposed backbone traces displayed Z-Score=8.4 and Rmsd=0.3Å with sequence identity=89.5% for COX-1, while for COX-2 Z-Score=8.4 and Rmsd=0.4 Å with sequence identity=99.5% for all atoms calculated locally within the two polypeptide chains (Figure 2). Most bond lengths, bond angles, and torsion angles were between values expected for a naturally folded protein.

Active site residue details

Among the ten sites obtained from Q-site finder, only 3 sites were selected, since they were conserved among different species, and the other sites are not further discussed. In both the proteins, site 2 is highly conserved in the active sites of the template and predicted COX- 1 and COX-2 models (Figure 10). Results from multiple sequence alignment and Motif analysis revealed that at COX-1 site 2, Tyr150, Ala201, Phe202, Ala204, Gln205, Thr208, His209, Phe212, Lys 213, Thr214, Leu296, Tyr350, Asn384, Tyr387, His388, Trp389, His390, Leu392, Met393, Phe397, Tyr406, Phe409, Leu410 and Val446 residues are conserved, and at the COX-2 site 2, Tyr 134, Thr192, His193, Phe196, Lys197, Thr198, Asp199, His200, Lys201, Arg208, Asn217, His 218, Gly221, Glu222, Thr223, Arg226, Gly274, Gln275, Glu276, Val277, Asn368, His372 are conserved (Table 3). Sequence analysis of the proteins depicts low substitution rate and less gap penalty, which indicates that they belong to the same protein family. Thus, site 2 of both COX-1 and COX-2 proteins has been found to be the most favorable site for docking studies. Motifs obtained from MEME tool, 29 for COX-1 and 21 for COX-2 out of selected maximum number of 30 motifs with length 20 to 50 (Figure 11). In which motif 2 and motif 5 represent the functional motif for both COX proteins containing the active site residues and catalytic residues, which are highly conserved and most representative among different species (Figure 12). The sequences which are highly representative and conserved throughout evolutionary studies are marked by red box in figure 11 (FAFFA in COX-1 and QHFTHQ and FFA in COX-2).

proteomics-bioinformatics-alignment

Figure 10: Multiple sequence alignment of COX proteins from different species, the conserved residues across various species are boxed in red.

proteomics-bioinformatics-consensus

Figure 11: Multilevel consensus sequences for the MEME defined motifs observed among different COX proteins from M. musculas.

proteomics-bioinformatics-represented

Figure 12: Highly represented sequence LOGO obtained from MEME/MAST server (http://meme.sdsc.edu/meme4_6_1/cgi-bin/mast.cgi).

COX-1 COX-2
Site 1 Site 2 Site 3 Site 1 Site 2 Site 3
ASN 36 TYR 150 VAL 118 ASN 19 TYR 134 ALA 185
CYS 38 ALA 201 ARG 122 CYS 22 THR 192 PHE 186
CYS 39 PHE 202 TYR 350 SER 23 HIS 193 ALA 188
TYR 41 ALA 204 VAL 351 ASN 24 PHE 196 GLN 189
PRO 42 GLN 205 LEU 354 PRO 25 LYS 197 THR 192
CYS 43 THR 208 SER 355 CYS 26 THR 198 HIS 193
GLN 44 HIS 209 TYR 357 GLN 27 ASP 199 PHE 196
ASN 45 PHE 212 LEU 361 ASN 28 HIS 200 ASN 368
GLN 46 LYS 213 PHE 383 ARG 29 LYS 201 TYR 371
GLY 47 THR 214 LEU 386 GLY 30 ARG 208 HIS 372
VAL 48 LEU 296 TYR 387 GLU 31 ASN 217 TRP 373
CYS 49 TYR 350 TRP 389 CYS 32 HIS 218 HIS 374
VAL 50 ASN 384 PHE 520 MET 33 GLY 221 LEU 377
ARG 63 TYR 387 MET 524 SER 34 GLU 222  
THR 64 HIS 388 ILE 525 ASP 111 THR 223  
TYR 66 TRP 389 GLY 528 THR 115 ARG 226  
ARG 81 HIS 390 ALA 529 TYR 116 GLY 274  
LEU 125 LEU 392 SER 532 GLY 121 GLN 275  
PRO 127 MET 393 LEU 533 TYR 122 GLU 276  
THR 131 PHE 397   LYS 123 VAL 277  
TYR 132 TYR 406   ALA 137 ASN 368  
ASP 137 PHE 409   LEU 138 HIS 372  
TYR 138 LEU 410   PRO 140    
ILE 139 VAL 446   VAL 141    
ILE 153     ALA 142    
LEU 154     CYS 145    
PRO 155     MET 149    
SER 156     GLY 150    
VAL 157     GLN 447    
PRO 158     GLU 451    
LYS 159     TYR 452    
GLN 463     LYS 454    
GLU 467     ARG 455    
LYS 470     SER 457    
ARG 471          
PHE 472          
GLY 473          

Table 3: 3 best predicted active sites for COX1 and COX2 from 10 predicted sites obtained from Qsite Finder http://www.modelling.leeds.ac.uk/qsitefinder/.

Docking study of COX-1 and COX-2 receptors with salicin inhibitor

Docking of COX-1 and COX-2 was performed with salicin inhibitor (2-(hydroxymethyl) phenyl hexopyranoside). The final docked conformation obtained for salicin was evaluated based on the number of hydrogen bonds formed and bond distances between atomic coordinates of the active site and inhibitor. To evaluate the structural similarity of M. musculus COX-1 and COX-2 with related COX proteins of different species, multiple sequence alignment (22 species for COX-1 and 25 for COX-2) was performed by UPGMA. The UPGMA (Unweighted Pair Group Method with Arithmetic Mean) phylogenetic profile based on reliability of an inferred tree is based on Felsenstein’s [56] bootstrap test, which is evaluated using Efron’s [57] bootstrap resampling technique (Figure 3). It was observed that the following stretch Ala201-Phe202-Ala204-Gln205, Thr208-His209, Phe212-Lys213-Thr214, Tyr387-His388-Trp389-His390, Leu392-Met 393 for COX-1 and Ala188-Gln189, Thr192- His193, Phe196, Asn368, Tyr371-His372, His374, Leu377 for COX-2 were conserved and present in catalytic active residues. Among these stretches the Thr208, Tyr387 and Trp389 amino acids residues may be involved in hydrogen bond interaction with salicin in the case of COX-1, while in case of COX- 2 Ala 188, Gln189, Thr192, His193, Phe196, Asn368, Tyr371, His372, His374, Leu377 amino acid residues appear to be involved. Based on docking of COX proteins with salicin inhibitor COX-2 having more hydrogen bond with greater affinity interaction rather than COX-1. The hydrogen bond interactions between inhibitor and COX proteins along with the bond distances are shown in table 4 and figure 13.

COX-1 COX-2
Residue Atom Salicin Distance Å Residue Atom Salicin Distance Å
ALA 204 CB C10 3.45 ALA 188 CB H3 3.17
GLN 205 OE1 O1 3.67 GLN 189 CB H3 3.74
THR 208 OG1 H3 3.87 THR 192 OG1 H2 2.12
HIS 209 NE2 H1 3.60 HIS 193 CE1 O6 3.79
TYR 387 CD1 C11 3.90 PHE 196 CD2 H4 3.67
TRP 389 CB C8 3.75 ASN 368 ND2 H4 3.89
HIS 390 CD2 H4 3.73 TYR 371 CB H2 3.85
LEU 392 CD1 C13 3.16 HIS 372 O6 NE2 3.49
MET 393 CE C12 3.37 HIS 374 CD2 C7 3.38
        LEU 377 CD1 C13 3.68

Table 4: Hydrogen bonds along with their distances between the salicin inhibitor and active site residues of COX proteins as deciphered using Docking server.

proteomics-bioinformatics-interactions

Figure 13: COX protein complex with salicin inhibitor. Surface view of (a) COX1 and (b) COX2, hydrogen bond interactions of (c) COX1 and (d) COX2, Overall bond interactions (e) COX1 and (f) COX2 using DS modeling vizualizer 3.1.

Effect of salicin on tumor volume and survival time

There were no gross behavioral changes and mortality upto a dose level of 200 mg/kg body weight. The LD50 value of salicin compound was found to be > 2g/kg body weight of mice indicating that it has low toxicity to the animal. Treatment with salicin at the dose of 100 and 200 mg/kg body weight increased the lifespan (ILS) and nonviable cell count and significantly reduced the tumor volume, tumor weight and viable tumor cell count when compared to that of EAC control group (Table 5).

Parameters EAC control 100 mg/kg salicin 200 mg/kg salicin 5-FU
Tumor volume (ml) 3.15a 1.68c 0.99e 0.47f
Tumor weight (g) 3.81a 1.52b 0.89c 0.42f
MST (days) 22 34 40 43
%ILS 0.0 54.54 81.81 95.45
Viable cell count 7.9×107a 3.1×107b 1.3×107d 0.9×107e
Nonviable cell count 0.8×107e 1.9×107d 2.8×107b 3.4×107a
Total cell count 8.4×107 5.0 ×107 4.1×107 4.3×107

Table 5: Effect of the isolated salicin compound from leaves of D. gangeticum on tumor volume, tumor weight, mean survival time (MST), percentage increase life span (%ILS), viable and nonviable, tumor cell count in EAC bearing mice.

The effect of salicin on hematological studies

The haemoglobin content, RBC count, lymphocyte (%) and monocyte (%) in EAC bearing mice given salicin at the dose of 100 and 200 mg/kg increased significantly compared with those in EAC control, whereas WBC count and neutrophil (%) showed significant decrease (Table 6). Treatment with salicin restored the hematological parameters to more or less normal values. The number of RBC count and hemoglobin content also increased, while the WBC and the differential count decreased as compared to that of EAC control. Treatment with salicin illustrated the percent increase in tumor cell volume and numbers of viable tumor cells were found to be significantly less when compared to those of the EAC control. Hence, it can be concluded that the extracts by their cytotoxic effect and arresting the tumor growth, increased the life span of EAC bearing mice. The percentage increase in life span in response to the 200 mg/kg body weight of salicin administration was indicating its potent anticancer nature (Table 6). In acute toxicity studies, the administration of salicin at the dose of 100 mg/kg and 200 mg/kg for 14 days did not exhibit any adverse effect.

Parameters Normal Saline (0.5 ml/kg) EAC (2×106 cells) control EAC (2×106 cells) + 100 mg/kg salicin EAC (2×106 cells) + 200 mg/kg salicin EAC (2×106 cells) + 5-FU
Haemoglobin content (g/dl) 13.8a 11.1e 12.1d 12.9c 13.1b
Total RBC* 6.1a 4.2ef 5.0d 5.7bc 5.9b
Total WBC** 8.2e 14.9a 11.2b 9.9c 9.0d
Lymphocyte (%) 65.9a 23.7d 58.8b 63.4c 65.1ab
Neutrophil (%) 32.1f 73.7a 38.5c 33.7d 32.6ef
Monocyte (%) 3.4c 2.2f 3.1d 3.9b 4.2a

Table 6: Effect of salicin of D. gangeticum on hematological parameters of EAC treated mice.

Discussion

In the early 1990s, cyclooxygenase (COX) was demonstrated to exist as two distinct isoforms. COX-1 is constitutively expressed as a housekeeping enzyme in nearly all tissues, and mediates physiological response, e.g., cytoprotection of the stomach, platelet aggregation. COX-2, on the other hand, is expressed by cells that are involved in inflammation, e.g., macrophages, monocytes, synoviocytes, and has emerged as the isoform that is primarily responsible for synthesis of the prostanoids involved in pathological processes, such as acute and chronic inflammatory states [58]. The two known COX isoforms show a high degree of similarity in their amino-acid sequences [59-62] and structural topology [63-65].

Classical NSAIDs like aspirin, ibuprofen, naproxen, but not nimesulide, are non-selective inhibitors of both the COX isozymes (IC50 for COX-1 is similar to that for COX-2) and their prolonged use can cause gastric bleeding and renal failure [66-68]. Hence, there have been sustained effort to identify selective COX-2 inhibitors, i.e., compounds whose IC50 for COX-1 inhibitory activity is significantly greater than that for COX-2. Some COX-2 inhibitors have been evaluated in clinical trials, but some of them showed increased cardiovascular toxicity; celecoxib, however, seems to be relatively safe COX-2 inhibitor [58]. It has meanwhile been hypothesized that there might be other isoforms of the COX enzyme yet to be discovered [67].

Nexrutine is a herbal alternative to COX inhibitor drugs for pain and soreness, and offers a number of advantages over both broad COX-1/2 inhibitors like aspirin and selective COX-2 inhibitors like Celebrex. Nexrutine inhibits the inflammatory COX-2 connected with pain without inhibiting the protective COX-1; thereby having a lower risk of producing gastrointestinal and bleeding side effects compared aspirin and Celebrex [69]. Synthetic compounds like mono-, di-, and triaryl substituted tetrahydropyrans were also reported as COX-2 and tumor growth inhibitors. These compounds exhibit IC50 for COX-2 in the range 0.57-4.0 nM, and their selectivity for COX-2 over COX-1 is better than that of celecoxib and rofecoxib [70].

A number of docking procedures based on different search and scoring algorithms have been proposed [71], but none can treat all biological systems with the same accuracy and efficacy [72-74]. It is thus advisable once the biological target has been selected, to set up an adequate system strategy for the study goal. The bark from white willow and some legumes contain salicin which is a natural pain reliever, is very easy on the stomach and kidneys, while acetylsalicylic acid is known to upset the stomach and in some cases damage kidneys. Scientists believe that this is because salicin is converted to acetylsalicylic acid after the stomach has absorbed it [75]. Putting acetylsalicylic acid directly into the stomach damages its lining and bleeding ulcers can result. Thus salicin is a pro-drug that is gradually transported to the lower part of the intestine, hydrolysed to saligenin by intestinal bacteria, and converted to salicylic acid after absorption. It thus produces an antipyretic action without causing gastric injury [76].

COX-2 produces inflammation causing compounds that lead to swelling for curative and protection. Blocking the COX-2 enzyme completely is not good because COX-2 activity is required for cardiovascular health. Many pain killers in the past ended up blocking all COX-2 activity, which led to heart problems for the patients taking them. Today most pain killers block a part of COX-2 activity but they also block COX-1, which is vital for the health and structure of the stomach lining. The white willow bark derived pain killer does not block COX-1, but it does block COX-2; as a result, it has few reported side effects [77].

Most docking algorithms consider that the enzyme structure is rigid, according to the high computational cost induced by the flexibility of big molecules, while the ligand is free to move. Usually, in the first step, a library of ligand conformers is generated and in the second step, these conformers are docked into the target, each conformer being treated as a new ligand. Any algorithm able to generate in a correct manner the ligand conformers could be used to generate this library. One of them is represented by genetic algorithms. Genetic algorithms attempt to use the rules of natural selection to subset computationally demanding tasks [78,79].

Qualitative and quantitative analyses of predicted 3D-structure of PMDBID PM0077492 and PM0077493 show that total Accessible Surface Area and total volume (packing) have significant reliable scores, which were compared with the experimental data available in VADAR server [80]. Secondary structure element statistics describe 44% and 46% of helices, 13% and 13% of Beta sheets, 41% and 40% of coils and 25% and 26% of turns in PM0077492 and PM0077493, respectively. After complete validation and refinement, stereochemical properties reveal no residues in the disallowed region in COX-1 and COX-2 had two residues, viz., Glu384 and Ser482, in the disallowed region. A good quality model would be expected to have over 90% residues in the most favored regions. In this study PMDBID PM0077492 and PM0077493 contain 89.9% and 90.7% residues in the most favored regions with overall average G-factor value of 0.14 and 0.17, respectively, indicating that the model quality is good.

Evolutionary sequence conservation and protein 3D structures have commonly been used to identify functionally important sites. The identification of a good catalytic active binding site and drug-protein interaction leads to identification of the potential drug target for functional inhibitory activity. The conserved active binding residues proved to be functionally enriched. Therefore multiple sequence alignment and regulatory motif detection were done to measure catalytic active binding sites with evolutionary conservation to get evidence for the best fit of a characterized salicin inhibitor. Multiple sequence alignment of COX-1 and COX-2 of M. musculus with different homologous species were performed (22 species for COX-1 and 25 for COX-2). The evolutionary tree was drawn using UPGMA, which suggests that M. musculus is closely related to Rattus norvegicus. This sequence analysis shows a high degree of evolutionary conservation among the active binding site within sequences of target proteins as well as in highly represented motifs. In both the COX proteins the predicted motifs were found to be conserved and most representative in sequence logo form (Figure 12). Moti10-LMRLVLTVR, Motif 2 - FAFFAQHFTHQFFKT, Motif 7 - IE[ED]YVQ[HQ]LSG, Motif 5 - N[QH]LYHWHPLMPDSF, Motif 1 - FGESM[IV]E[IM]GAPFSLKGL in COX-1, and Motif 4 – YVLTSRSHLI, Motif 5 - FAFFAQHFTHQFFKT, Motif 1 - GETIKIVIEDY, Motif 2 - EFNTLYHWHPLLPDTFQI, Motif 3 - GAPFSLKGLMGNPICSPEYWKPSTFGGEVGFKI in COX-2 were found to be totally conserved within species and also containing the active binding residues. As per earlier evidences PMID 10811226 and PMID 7552725 it has been found that Leu119, Phe207, Ile347, Try350, Val351, Ser354, Try356, Phe382, Try386, Trp388, Phe520, Met524, Gly528, Ala 529, Ser532, Ile533, Leu536 for COX-1 and Leu103, Phe191, Ile331, Try334, Val335, Ser339, Try341, Try371, Trp373, Phe504, Met508,Gly512, Ala513, Ser516, Leu517, Leu520 for COX-2 represented as substrate binding site. Metal binding site was reported in COX proteins as Try150, Ala201, Gln205, Gln210, Phe212, Lys213, Thr214, Leu297, Asn384, Try387, His388, Trp389, His390, Met393, Leu410, His448, Val449, Asp552 for COX-1 and In case of COX-2 Try134, Ala185, Gln189, Phe191, Gln194, Phe196, Lys197, Thr198, Asn386, Try389, His390, Trp391, His292, Leu393.

Based on protein-drug interaction it has been confirmed that salicin docked and interacted with polar residues- Glu205, Thr208, His 209, 390, hydrophobic residues - Ala204, His209, Tyr387, His390, Leu392 and Met393, pi-pi level interactions with TRP389 residue and cationpi interaction containing residues His209 and His390 for COX-1. In the case of COX-2 polar residues-Thr192, His193, Asn368, His372, His374, hydrophobic residues His193, His372, Leu377, pi-pi level interactions with His374 and cation-pi interaction containing residues His193, Phe196, Tyr371 showed better inhibitory activity with salicin. Loll et al. [67] reported that COX-1 (1CQE) receptor are showing interaction complex with HEME (protoporphyrin is containing Fe) ligand, in which Ala167, Gln171, His175, Try353, His354, Trp355 and His356 residues are involved. Kiefer et al. [81] observed that in the case of COX-2 (1CVU) interaction complex with BOG (b-octylglucoside) ligand Ala168, Gln172, Phe174, Try354, His355, Trp356, Leu359 and Leu360 residues act as a catalytic active binding sites. In case of salicin docking interaction with COX-1 and COX-2 it has been found that Ala201, Gln205, Try387, His388, Trp389, His390, Met393 residues of COX-1, and Ala185, Gln189, Try389, His390, Trp391, His292, Leu393 residues of COX-2 involved in interaction. These interacting residues are present in Motif 2 and 5 for both COX proteins and also found conserved in alignment pattern.

Hillarp et al. [82] reported that in case of mutations within the COX-1 gene in aspirin non-responders with recurrence of stroke and carriers and non-carriers of one of the mutations behaved similarly when aggregation and granule content release function were studied using collagen, ADP and arachidonic acid as agonists. Thus their hypothesis do not support that common variants of the COX-1 gene results in unblocked COX-1 molecules in aspirin non-responders.

The present study illustrated the effect of isolated compound salicin from D. gangeticum leaves on EAC bearing mice, which significantly increased the life span of treated animal as compared to the EAC control. The reliable conditions for evaluating the value of any anticancer drug are prolongation of life span and decrease in the WBC count [83]. The ascitic fluid is the direct nutritional source to tumor cells and the rapid increase in ascitic fluid with tumor growth could possibly be a means to meet more nutritional requirements of tumor cells [84]. Furthermore the reduced volume of EAC and increased survival time of mice suggest the delaying impact of extracts on cell division [85]. The treatment with salicin inhibited the tumor volume, viable cell count and enhanced survival time of EAC bearing mice. These finding suggest the antitumor effects of salicin compound against EAC cell line.

Conclusion

The protein-ligand interaction plays a significant role in structural based drug designing. It has been clearly demonstrated that the approach utilized in this study is successful in finding novel anticancer inhibitor from medicinal plant D. gangeticum. The ligand salicin, in particular, from D. gangeticum showed high binding affinity against COX-2 protein (PDB ID: PM0077493) (-5 Kcal/mol) and lesser interaction with COX-1 (PDB ID: PM0077492) (-3.79 Kcal/mol) based on docking score. Therefore, this study states the importance of natural plant compound protein-ligand interaction studies, in silico. From the docking results, we conclude that salicin could be a potential COX inhibitor. Arachidonic acid (mmu00590) and VEGF signaling (mmu04370) pathway key enzymes play an important role during tumor angiogenesis and metastasis in context of COX proteins so it is possible that proteins related to these metabolisms are actively involved in interaction with salicin. However, additional biological and mutational studies would help in prediction of anti-cancerous compounds. The obtained results are useful to understand the structural features inhibitory activities to COX proteins. The extraction, isolation and characterization of bioactive compound salicin from leaves of this plant and its in vivo anticancer activity confirm salicin as potent anticancer drug.

Acknowledgements

The author P.S. wish to thank ICMR, New Delhi for providing financial assistance as SRF. Department of Chemistry, Banaras Hindu University, Varanasi, India, are acknowledged for recording NMR spectra. P.S. is also thankful to Dr. Vinod Tiwari for providing lab facility and guidance for extraction of plant and Dr. Santosh Kumar Singh for providing animal house facility. P.S. is also thankful to Centre of Experimental Medicine & Surgery, BHU, Varanasi for providing animal house facility to perform all experimentation.

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