Novel thrombopoietin mimetic peptides bind c-Mpl receptor: Synthesis, biological evaluation and molecular modeling

Bioorganic & Medicinal Chemistry xxx (2016) xxx–xxx

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Novel thrombopoietin mimetic peptides bind c-Mpl receptor: Synthesis, biological evaluation and molecular modeling Yaquan Liu a, Fang Tian a, Dejuan Zhi a, Haiqing Wang a, Chunyan Zhao a,⇑, Hongyu Li b,⇑ a b

School of Pharmacy, Lanzhou University, Lanzhou 730000, China School of Life Science, Lanzhou University, Lanzhou 730000, China

a r t i c l e

i n f o

Article history: Received 24 October 2016 Revised 15 December 2016 Accepted 16 December 2016 Available online xxxx Keywords: Thrombopoietin mimetic peptide c-Mpl receptor Molecular modeling

a b s t r a c t Thrombopoietin (TPO) acts in promoting the proliferation of hematopoietic stem cells and by initiating specific maturation events in megakaryocytes. Now, TPO-mimetic peptides with amino acid sequences unrelated to TPO are of considerable pharmaceutical interest. In the present paper, four new TPO mimetic peptides that bind and activate c-Mpl receptor have been identified, synthesized and tested by DualLuciferase reporter gene assay for biological activities. The molecular modeling research was also approached to understand key molecular mechanisms and structural features responsible for peptide binding with c-Mpl receptor. The results presented that three of four mimetic peptides showed significant activities. In addition, the molecular modeling approaches proved hydrophobic interactions were the driven positive forces for binding behavior between peptides and c-Mpl receptor. TPO peptide residues in P7, P13 and P70 positions were identified by the analysis of hydrogen bonds and energy decompositions as the key ones for benefiting better biological activities. Our data suggested the synthesized peptides have considerable potential for the future development of stable and highly active TPO mimetic peptides. Ó 2016 Published by Elsevier Ltd.

1. Introduction Thrombopoietin (TPO), a growth factor that mediates its effects through the TPO receptor, is the primary physiological regulator of platelet production.1 As a therapeutic agent, TPO has been shown to speed platelet recovery following myelosuppressive therapy in mice,2,3 in non-human primates, 4 and in cancer patients.4,5 Clinical trials with recombinant versions of TPO were shown to increase platelet counts in humans with normal bone marrow and to benefit patients receiving nonmyeloablative chemotherapy.6–8 However, administration of recombinant TPO has not become general clinical practice due to the immunogenicity of the protein.9–13 Motivated by the antibody problems and the desire to develop forms of therapy that might be administered orally or produced more efficiently, two approaches have been used to improve the potential of this therapeutic approach. One approach is the generation of dimeric antibody fragments that induce receptor dimerization and activation.14–16 In addition to this approach, thrombopoietin mimetic peptide (TMP) as alternate thrombopoi-

⇑ Corresponding authors. E-mail addresses: [email protected] (C. Zhao), [email protected] (H. Li).

etic agents, which lack native TPO primary sequences, have been developed to address this concern.17,18 The biological actions of these TPO and TPO mimetic peptides are initiated by specific binding to cell surface receptors expressed on target cells.14 TPO receptor c-Mpl, as the cell surface receptor for thrombopoietin, is a member of the hematopoietic growth factor receptor super family.19 These receptors are characterized by a number of conserved sequence motifs within the extracellular domain, which is typically composed of multiple b-sandwich modules related to the fibronectin type III–immunoglobulin fold, with a characteristic ligand-binding domain formed from two adjacent bsandwich structures.20,21 There are two reduplicated cytokine receptor homology (CRH) domains in TPO receptor c-Mpl. Upon TPO or TPO mimetic peptides binding to the distal CRH domain, steric inhibition is probably released, thereby activating the receptor; deletion of the distal CRH produces a receptor that is constitutively active in the absence of ligand binding.22 Several mimetic peptides that bind and activate the cMpl-R have been identified, with potency equal to that of recombinant human TPO (rhTPO) in cell-based assays.23 The current research on immunogenicity has indicated that immune responses directed against such peptides would not cross react with native TPO in humans24 suggesting that a TPO peptides could be a safe therapeutic strategy.25 Several important alternate TPO mimetic peptides

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have now been reported.15,16,26,27 Cwirla et al. identified one 14amino acid peptide (Ile-Glu-Gly-Pro-Thr-Leu-Arg-Gln-Trp-LeuAla-Ala-Arg-Ala), with amino acid sequences unrelated to TPO, which binds to the TPO receptor with high affinity.23,26,27 Bussel et al. found another TPO mimetic peptide, named as Romiplostim given by subcutaneous injection that activates the TPO receptor by binding to the distal hematopoietic receptor domain just like TPO.28 Frederickson et al. described a rationally designed TPO mimetic peptides (Fab 59) made by engrafting 14-amino acid TPO peptides into a fully human Fab with stable binding activity to the receptor.15 However, the X-ray crystallographic structure of c-Mpl has not yet been obtained, which has led to difficulties in the rational peptide design based on the structure of receptor. Thus, the present paper seeks (1) to synthesize new TPO mimetic peptides with higher affinity to the receptor; (2) to explore the binding behavior and mechanism of TPO mimetic peptides; and (3) to model the structure of the c-Mpl receptor based on molecular modeling methods to improve rational design of TPO mimetic peptides.

2. Material and methods Escherichia coli BL21 (DE3) and the expression vector pGEX-4T-1 were stored and supported by the microbiology laboratory of the pharmacy school at Lanzhou University. Taq polymerase and restriction enzymes (EcoRI, BamHI) were bought from TaKaRa Biotechnology Co., Ltd. (Dalian, China). SanPrep Column Plasmid Mini-Preps Kit, SanPrep Column DNA Gel Extraction Kit and Isopropyl b-d-thiogalactoside (IPTG) were purchased from Sangon Biotech, Shanghai. Glutathione Sepharose 4 Fast Flow was purchased from GE Healthcare, China. Thrombin from human plasma was purchased from Sigma-Aldrich Co. LLC. (China).

2.1. Construction of recombinant plasmid pGEX-4T-1/TMP-L-TMP The four gene fragments TMP-L(1-4)-TMP were synthesized by TaKaRa Biotechnology Co., Ltd. (Dalian, China). The synthesized TMP-L(1-4) gene and the expression vector pGEX-4T-1 were cut with EcoRI and BamHI enzymes and then ligated together to make the recombinant plasmid pGEX-4T-1/TMP-L-TMP.

2.2. Induction and expression of the GST-TMP/L(1-4) fusion proteins Recombinant plasmids pGEX-4T-1/TMP-L-TMP were transformed into E. coli BL21 competent cells, and a single colony was inoculated into 5 mL LB medium containing ampicillin, and incubated at 37 °C for 12 h on a shaker (220 rpm). Bacterial suspension (50 ll) was added to 50 mL LB medium containing ampicillin, incubated at 37 °C with shaking at 220 rpm. The OD600 was checked periodically until it reached 0.5–0.6. One milliliter of the culture was set aside as an uninduced control, and IPTG was added to a final concentration of 0.1 mM to induce protein expression. After four hours, one milliliter of induced bacterial culture was set aside for sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE) detection. The remaining bacterial culture was centrifuged at 8000 rpm for 10 min at 4 °C, and the cell pellet was collected. The cell pellet was resuspended in 40 mL PBS and subjected to ultrasonic lysis in an ice bath (75% amplitude used continuously for 3 s, then stopped for 8 s for a total of 30 cycles). The lysate was centrifuged at 10,000 rpm for 30 min at 4 °C, and the supernatant was collected for purification.

2.3. GST-TMP/L(1-4) fusion protein purification and removal of GST tag GST-TMP/L(1-4) fusion proteins were purified from bacterial lysates by affinity chromatography The bottle containing the Glutathione Sepharose 4 Fast Flow resin was gently shaken until all the resin was completely in suspension. Six milliliters of resin suspension (50% slurry) was transferred to a disposable column and washed with 10 bed volumes of cold PBS (pH 7.4) to equilibrate the column. The supernatant of the lysate containing either the GST-fusion protein or GST was applied to the equilibrated column with a flow rate of 1.5 mL/min. The column was washed with 20 bed volumes of PBS immediately after all the protein solution had entered. The fusion protein was eluted with freshly made 10 mM glutathione elution buffer and analyzed by SDS-PAGE. The fusion proteins GST-TMP/L(1-4) were cleaved by thrombin, and the GST tag was removed with Glutathione Sepharose 4 Fast Flow. The purity of the TMP/L(1-4)peptide fragments was evaluated by Tricine-SDS-PAGE. 2.4. Dual-luciferase reporter assay The transient cell transfection was performed with Lipofectamine 2000 transfection reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. NIH-3T3 cells were cultured in Dulbecco’s modified Eagle’s medium (Invitrogen) supplemented with 10% fetal calfserum (Invitrogen) and seeded in 24-well plates before transfection. Twenty-four hours after plating, the NIH-3T3 cells at approximately 75% confluence were co-transfected with mpl, fos, padva, and renilla plasmid. The TMP/L(1-4) peptides were added 48 h after transfection, with a group without peptides used as a control. The Firefly and Renilla luciferase activities were measured with the Dual-Glo luciferase assay system (Promega). The activity of the Firefly luciferase was normalized to that of the Renilla luciferase. At least three independent experiments were performed in triplicate.29 2.5. Molecular modeling The three-dimensional structures of the c-Mpl were generated using I-TASSER (Iterative Threading Assembly Refinement), a fully automated structure prediction tool.30 The protein sequence of cMpl was retrieved from the NCBI Reference Sequence accession number NP-005364. Erythropoietin receptor (EBP) protein was selected as the template (PDB accession number 1CN4) for homology modeling of TPO receptor, c-Mpl.31 Details of homology modeling can be obtained from Ref. 32 The best model was identified based on the C-score calculated from the relative clustering structural density and consensus significance. In addition, a Ramachandran plot was used to explain the stereo chemical quality of the constructed c-Mpl models by PROCHECK program. Considering that experimental studies have shown that c-Mpl is a dimeric protein, the homology model was dimerized using SymmDock server. The initial 3D structure of c-Mpl obtained from homology modeling was refined by 30 ns’ MD simulation with ff99SB force field. 2.5.1. Molecular dynamics (MD) simulation The peptides were optimized by 50 ns’MD simulation using the Amber ff99SB force field and then docked into the probable binding pockets of c-Mpl using ZDOCK module in Discovery Studio2.5 software. The binding site of c-Mpl was determined based on the one of template protein 1CN4. Molecular dynamics simulations were performed for the peptide-receptor complexes. Hydrogen atoms were added to the initial c-Mpl-TMP complex model using the tleap module, setting ionizable residues as their default protonation states at a neutral pH value. The complex were solvated in a cubic periodic box of explicit

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TIP3P water model that extended a minimum 10 Å distance from the box surface to any atom of the solute. Sodium ions were randomly replaced water molecules in the box to neutralize a total negative charge on the entire system. The particle mesh Ewald (PME) method for simulation of periodic boundaries was used to estimate the long-range electrostatic interactions with a cutoff of 10.0 Å. All bond lengths were constrained using the SHAKE algorithm and integration time step was set to 2 fs using the Verlet leapfrog algorithm.33 For equilibration, the solvent molecules and counterions, the side chain of protein, and the whole systems were successively minimized by 2500 steps of steepest descent method following 5000 steps of conjugated gradient method, while restraining the rest using a force constant of 500, 10, and 0 kcal/mol Å2 respectively. Then each system was gradually heated from 0 to 300 K over a period of 50 ps and maintained at 300 K with a coupling coefficient of 1.0/ps with a force constant of 1.0 kcal/mol Å2 on the complex. Each system was again equilibrated to a free simulation for 500 ps. Finally, each production run for 70 ns was performed using NPT ensemble at 300 K with 1.0 atm pressure. Coordinate trajectories were recorded every 1 ps for the whole MD runs. 2.5.2. Analysis of molecular dynamics trajectories Structural properties, such as root mean-square deviation (RMSD) and root-mean square fluctuation (RMSF), were calculated with the built-in functions of Amber11.34 All frames were aligned with the starting structure prior to the calculations. The internal cavity volume, the solvent accessible surface area of the binding pocket and the distance between helices were calculated with CHIMERA software. 2.5.3. Binding free energy calculations The binding free energy of each system was calculated using molecular mechanics generalized Born surface area (MM/GBSA) approach implemented as script (MMPBSA.py) in AMBER software.35 The first step of MM-GBSA is to generate multiple snapshots from the stable MD production trajectory of the complex. In the present research, 1000 snapshots were extracted from the last 10 ns trajectory for each complex. The DGBind between a ligand and a receptor to form a complex can be calculated as follows:

DGBind ¼ DEMM þ DGSOL  TDD DEMM ¼ DEinternal þ DEelectrostatic þ DEvdw DGSol ¼ DGGB þ DGSA where DEMM is total gas phase energy contains the internal energy term (DEinternal ), the electrostatic energy term (DEelectrostatic ) and the van der Waals energy term (DEvdw ). DGsol is sum of nonpolar (DGSA ) and polar (DGGB ) contributions to solvation calculated by Generalized Born (GB) approaches. TDS is the change of conformational entropy on ligand binding, as our aim is not to obtain the absolute Gibbs energy but to analyze the detailed interaction features, the entropy contribution was not included in this study. 2.5.4. Free energy decomposition The contribution of residues to the binding free energy in the interaction between TMPs and c-Mpl was analyzed using the MM-GBSA decomposition protocol of AMBER software (version 11). All energy components were calculated based on 1000 snapshots, which were extracted from the trajectories of the last 10 ns of MD simulations.36 3. Results and discussion The four gene fragments TMP-L(1-4)-TMP were synthesized and the sequences of the four mimetic peptides were listed in Fig. 1.

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Considering that the conserved 14 amino acid sequence is required to maintain biological activity, the linkers of the four mimetic peptides were optimized. 3.1. Double enzyme digestion of positive clones As shown in Fig. 2A, the purified PCR product was cut into two fragments by the enzymes. The darker fragment below 250 bp was identified as a TMP diad, which was consistent with the expected values of 120 bp, 111 bp, 120 bp and 135 bp. Another band within the 4000-bp to 7000-bp range indicates the pGEX-4T-1 vector cut with both EcoRI and XhoI enzymes. 3.2. Expression and purification of fusion protein GST-TMP/L(1-4) The GST-TMP/L(1-4) proteins were expressed in E. coli BL21 strain induced by IPTG. The expression of GST-TMP/L protein was confirmed by SDS-PAGE analysis. The result showed that the whole cell lysate obtained from the induced E. coli strain containing therecombinant plasmid expressed a GST fusion protein identical to the predicted molecular weight of 30 kDa (Fig. 2B), whereas the cell lysate containing empty vector expressed a GST fusion protein with a molecular weight of 26 kDa. The harvested bacterial cells were subjected to affinity chromatography using immobilized glutathione by Glutathione Sepharose 4 Fast Flow Resin affinity chromatography. The eluted GST-TMP/L(1-4) fusion proteins were then obtained (Fig. 2C) and assessed by the Bradford method after purification with the GSTrap column. The molecular weights of the four purified proteins were all more than 30 kD, which is consistent with the predicted molecular weights of 34.1 kD, 33.8 kD, 33.8 kD and 33.6 kD. 3.3. Synthesis of peptides TMP/L(1-4) and dual-Luciferase reporter gene assay Lastly, the four fusion peptides were treated using the same process and then detected by SDS-Tricine-PAGE. As shown in Fig. 2D, the molecular weights of the four peptide fragment were close to the low molecular weight protein standard of 4.1 kD. This is in agreement with the theoretical values of 3.92 kD, 3.64 kD, 3.61 kD and 3.43 kD. The luciferase activities of firefly and renilla were detected. The luciferase activity of renilla was standardized using the luciferase activity of firefly (Fig. 3). As indicated in the t-test, the bio-activities of three mimetic peptides TMP/L1, MP/L3 and TMP/L4 showed significant in statistics with control one, with TMP/L3 > TMP/ L4 > TMP/L1. While for another peptide TMP/L2, there are non-significant difference of activity can be observed between the groups of TMP/L2 and the control one. Considering these data, the following modeling simulation was applied only to the three active peptides TMP/1, TMP/3 and TMP/4. 3.4. Molecular dynamic modeling 3.4.1. Homology modeling of c-Mpl receptor The results are shown as the mean and standard deviations of three independent experiments performed in triplicate. ⁄⁄ and ⁄ indicate p < 0.01 and p < 0.05, respectively, when compared with control. Considering that the crystal structure of c-Mpl has not yet been obtained, the three-dimensional structure of c-Mpl was predicted using homology modeling to perform structural analysis. Docking and molecular dynamics studies were also performed based on the predicted model. As shown in Fig. S1 in the Supporting Information, five models of c-Mpl were generated based on ten different templates using

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Fig. 1. Amino acid sequences of mimetic peptides.

Fig. 2. (A) Agarose gel electrophoresis analysis of the recombinant plasmid. LaneM: DNA marker DL10000; Lane 1: pGEX-4T-1plasmid; Lane2-5: recombinant plasmidp GEX4T-1/TMP-L(1-4); Lane6-9: pGEX-4T-1/TMP-L(1-4) cut with both EcoRI and XhoI enzymes. (B) SDS-PAGE analysis of the expressed GST-TMP/L(1-4) fusion proteins. Lane M: molecular weight marker; Lane1: GST-TMP/L1 before induction; Lane2: GST-TMP/L1 after induction; Lane3: GST-TMP/L2 before induction; Lane4: GST-TMP/L2 after induction; Lane5: GST-TMP/L3 before induction; Lane6: GST-TMP/L3 after induction; Lane7: GST-TMP/L4 before induction; Lane8: GST-TMP/L4 after induction. (C)SDS-PAGE purification of the GST-TMP/L(1-4) fusion protein. LaneM: molecular weight marker; Lane1: GST-TMP/L1 fusion protein; Lane2: GST-TMP/L2 fusion protein; Lane3: GST-TMP/ L3 fusion protein; Lane4: GST-TMP/L4 fusion protein. (D) Tricine-SDS-PAGE analysis of purified TMP/L(1-4). LaneM: molecular weight marker; Lane 1: purified TMP/L1; Lane 2: purified TMP/L2; Lane 3: purified TMP/L3; Lane 4: purified TMP/L4.

program (Fig. S1, Supporting Information). The model showed 77.1% residues in favored regions, 21.5%residues in allowed regions, and 1.4% residues in outlier regions. Further refinement of the structure improved the stereo-chemical properties (76.2% in favored regions, 23.3% in allowed regions, and 0.5% including Ser residues in outlier regions). Experimental evidence suggests that the receptor is homodimeric and thus was modeled accordingly. The final dimeric structure of the c-Mpl receptor is shown in Fig. 4A. As presented, the cMpl monomer is folded into two domains, D1 (N-terminal) and D2 (C-terminal), which form an L shape. The NH2-terminal domain (D1, residues 10–114) and the COOH-terminal domain (D2, residues 119–220) are connected by a four-residue helical linker. Fig. 3. Detection of four TMP/L(1-4) protein by dual-luciferase reporter assay system. The Firefly and Renilla luciferase activities were measured with the DualGlo luciferase assay system. The activity of the Firefly luciferase was normalized for transfection efficiency to that of Renillaluciferase. The results are shown as the mean and standard deviations of three independent experiments performed in triplicate. ⁄⁄ and ⁄ indicate p < 0.01 and p < 0.05, respectively, when compared with control.

threading programs. Considering that C-score is a confidence score for estimating the quality of predicted models, the best model was selected with the highest C-score of 1.35. The constructed model was also validated by the Ramachandran plot from the PROCHECK

3.4.2. RMSD and RMSF analysis Considering that the mimetic peptides TMP/2 presented nonsignificant activity, the following modeling simulation was applied for only the other three peptides TMP/1, TMP/3 and TMP/4. The three peptides were docked into the binding pocket of c-Mpl, and all peptide-receptor systems were optimized by molecular dynamics simulations for 70 ns. To understand the overall structural stability throughout the simulation, root-mean-square deviations (RMSD) over time for the three systems were analyzed (Fig. S2 in Supporting Information). As shown, all systems reached stability after 50 ns in simulations.

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Fig. 4. (A) Three-dimensional structure of c-Mpl receptor. The blue one was c-Mpl protein and the yellow one was the template protein 1CN4. (B) Detailed analyses of RMSF versus the protein residue numbers. (C) Detailed analyses of RMSF versus the peptides residue numbers. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

To analyze the fluctuations of each residue, root-mean-square fluctuation (RMSF) of the Ca atoms of all the residues of the TMP-receptor complexes were plotted (Fig. 4B). As shown, three complexes shared similar RMSF distributions and similar trends of dynamic features. Some residues generally showed lower fluctuations (RMSF values < 1.5 Å) for all three systems, including residues 18–21, 100–110, 136–142, 238–242, 360–371, 456–464 and 496–510. These peak regions were labeled A - G in the RMSF plot. It is interesting that all of these regions are located at the interface of the binding pocket, which showed rigid behavior for these three complexes. Indeed, the fluctuations of the residues in these two regions will greatly influence the contacts with the peptides via hydrophobic or electrostatic interactions. In addition, the RMSFs of the three mimetic peptides were analyzed. As shown, the RMSF value of the linker part formed a loop region (Fig. 4C) and was much larger, which was consistent with research indicating that protein loops were generally more flexible than regular secondary structures.37 More importantly, for all three peptides, it can be observed that the RMSF value of the residues in the ‘‘P-” position undergoes pronounced conformational changes with an increasing average value and that the residues in the ‘‘P’” position were quite stable with lower average RMSF values of 1.31 Å, 1.36 Å and 1.25 Å, respectively. Especially for P7, P13 and P130 positions with the lowest RMSF values for all the three peptides, these residues presented less fluctuations, which can be explained by some types of interactions including hydrogen bonds formed between P7, P13, P130 residues and the c-Mpl. Furthermore, compared to the three active peptides, the TMP/4 presented the lowest RMSF value of 1.40 Å, which confirmed that TMP/4 peptides would ultimately exhibit the most stable binding behavior with its receptor c-Mpl. 3.4.3. Binding modes analysis In its crystallographic binding site, the peptide dimer was deeply embedded in an inverted-cone shaped cleft at the interface

between the two monomers (Fig. 4A, Supplementary data Video). As predicted, the peptide interacted with both receptor monomers. The peptide-receptor interaction can be grouped into distinct hydrophobic and polar areas. As shown in Fig. 4A, the three peptides presented the same trend on hydrophobic and electrostatic interactions with the receptor. For example, for the c-Mpl-TMP/4 complex, a hydrophobic core was formed between TMP/4 and the c-Mpl dimer, including Phe79, Ile136 and Pro132 from Monomer A, together with Phe341, Ile500 and Phe363 from Monomer B. This indicated that the hydrophobic property was one of the main forces driving the interaction. The polar interactions are located chiefly at the bottom of the binding crevice. For the TMP/4-receptor complex, several polar residues, Glu135, Glu131and Ser104 of Monomer A together with Arg308, Arg466 and Glu467 of Monomer B were inproximity to TMP/4, which also had an important function in stabilizing the peptide-receptor complex via electrostatic interaction as well as hydrogen bonds (Fig. 4B). In addition, to address the structural variation of the three peptides, the corresponding average distances between the centroids of the P-Helix and P’-Helix were measured as presented in Table S1. Compared with TMP/3, the two most active peptides TMP/4 and TMP/1 presented the largest distances of 11.773 Å and 12.087 Å. The two helices moved to binding site of the receptor, which increased the favorability of the binding behavior between the peptides and the protein. This can explain the great biological activity of TMP/4 and TMP/3. Additionally, the volume and the accessible surface areas of the three peptides were calculated in Table S1. As shown, for the most active peptide TMP/4, the surface areas and volumes in hydrophobic core were all greatly expanded compared with the other two peptides, which increased the chance of an interaction with the receptor c-Mpl. The simulation data revealed that for TMP/4 the largest distance, together with the biggest surface area and volume, generally

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Fig. 5. (A) Hydrophobic potential plot on molecular surfaces; the color of blue to white represent decreasing hydrophobic potential; (B) electrostatic potentials plot on molecular surfaces; the color of red to blue represent decreasing electrostatic potential. (C) Common strong receptor-ligand H-bonds for TMP/1, TMP/3 and TMP/4. The blue and brown ribbon represent monomer A and monomer B. The blue dotted line represents H bonds; the red sphere represents residues forming H-bonds. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

made for the best binding behavior with the receptor and thus resulted in the highest biological activity. Hydrogen bonds analysis. Hydrogen bonds (H-bonds) play a key role in the stabilization of protein structures. The statistical analysis of hydrogen bonds was carried out on the trajectories to determine which hydrogen bonds were formed or broken between the mimetic peptides and the c-Mpl receptor (Table S2 in the Supporting Information). In the present research, the hydrogen bond is rigidly defined by distance (<3.5 Å), orientation (the angle A—H-D > 120.0°) and occupancy (>10%). The statistical result of the hydrogen bond analysis was also presented in Fig. 5. As shown, very strong canonical backbone hydrogen bonds were formed between the three peptides and the receptor, especially for the two most active peptides TMP/4 and TMP/1. As shown, in the case of TMP/1, TMP/3 and TMP/4, they formed 7, 4 and 10 canonical backbone hydrogen bonds with the protein, respectively. It should be noted that this conclusion was quite consistent with the results of the luciferase assay, which showed the highest activity for TMP/4 and the lowest activity for TMP/2. This suggested that the formation of canonical backbone hydrogen bonds is favorable for peptide-receptor binding and therefore to biological activity. In addition, quite strong hydrogen bonds were also observed in side-chain interactions. As presented, 20, 17 and 23 hydrogen bonds were constructed for TMP/1, TMP/3 and TMP/4, respectively, especially inP7, P13 and P70 positions. It should be noted that the hydrogen bonds, both for the canonical backbone and the side chain, were observed mainly in P- positions and not in P0 positions. This kept the conformation of these P-residues stable, whereas the P0 residues, especially P30 and P130 , underwent pronounced conformational changes (Fig. 6). This conclusion was in agreement with fluctuations in the RMSF analysis shown in Fig. 4. Additionally, for the most active peptides TMP/4 and TMP/1, four common strong receptor-ligand H-bonds, P13-Pro132, P13-

Pro134, P13-Pro131 and P13-Pro135 were observed (Fig. 4C), whereas two receptor-ligand H-bonds (P13-Pro132 and P13Pro134), were not observed for peptide TMP/2. This indicated that the residues Pro134 and Pro132, together with the corresponding interactions, were absolutely important for peptide binding. The disruption of this hydrogen bond affected the binding behavior greatly, which in turn decreased the activity. Thus, it can be concluded that the peptide binding was preferentially mediated by stabilizing hydrogen bonds between two receptor residues (Pro134 and Pro132) and the peptide reside in the P13 position. All above conclusions were in agreement with the evidence that the peptide with the highest activity constructed the most hydrogen bonds, whereas the peptide with the lowest activity constructed the least hydrogen bonds. 3.4.4. Energy decomposition The binding affinities for the peptide-receptor systems were calculated to understand the interaction force based on MM-GBSA. The energetic contributions of individual amino acids to complex formation were analyzed to search for the dominant factors that dictate the binding specificity of the peptide. To probe the importance of each residue of c-Mpl, the energy contribution difference analysis for the receptor was performed. As shown in Fig. 7, several key residues whose contributions to the binding free energy were more than 3 kcal/mol were identified in the two most active peptides, TMP/4 and TMP/1. These include Glu131, Phe363, Phe79, Phe341 and Ile136. Here, as expected, strongly favorable contributions to the binding were associated with the residues located in the binding site, as identified in Fig. 7. In addition, it was also found that these key residues were the ones that formed the main hydrogen bonds with the peptides, such as the H-bonds of Glu131-P13, Ser501-P130 , Asp498P130 and Phe20-P7 for the TMP/1-receptor system, together with

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Fig. 6. Scheme of hydrogen bonds formed between c-Mpl and peptide substrate. The hydrogen bonds with occupancy of 80%100%, 60%80%, 60%80% and 40%60% are presented in red, blue, yellow and green arrows, respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 7. Per-residue contribution on the binding effective energy of the c-Mpl binding site bound to three different peptides TMP/1, TMP/3 and TMP/4. The per-residue contributions were calculated by applying the MM-GBSA approach

H-bonds Glu135-P13, Glu131-P13, Phe341-P70 and Pro132-P130 for the TMP/4-receptor system. Furthermore, the contribution of the identified key residues was further broken down into polar and nonpolar sections (Fig. 7A). It can be found that for all three systems, the non-polar residues, such as Leu453, Ile388, Phe488, Val433, Leu430 and Leu487, generally contributed more to the binding free energy than the polar residues, such as Asn391. Moreover, as shown, hydrophobic interactions (black bar) were more favorable for the binding behavior, whereas the electrostatic interactions (gray bar) were unfavorable for binding. From these results, we believed that the hydrophobic

interaction was the driving force for the interaction between the peptides and the c-Mpl receptor. Besides it, the energy contribution analysis for the three peptides was also constructed to probe the importance of each position (Fig. 7B). As presented, based on the decomposition results, P7, P13 and P70 have a key contribution to binding in two of the three investigated peptide substrates. Interestingly, these two peptides, TMP/4 and TMP/1 were the most active ones and the only exception was the least active peptide TMP/3. It seemed that P13 has a most important contribution to beneficial binding. Furthermore, the energy decompositions of the peptide structures identi-

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Fig. 8. (A) Polar and nonpolar contributions for key residues. Negative values are favorable and positive values are unfavorable for binding. (B) Per-residue contribution to the binding effective energy of TMP/1, TMP/3 and TMP/4.

fied peptide residues P7, P13 and P70 dominate binding. It also should be noted these P7, P13 and P70 residues were exactly the ones formed the main hydrogen bonds with receptor, which is just in line with the hydrogen analysis.

4. Conclusion In summary, we have synthesized four new TPO mimetic peptides, the biological activities of which were tested using DualLuciferase reporter gene assay. Three peptides showed high affinity to its receptor c-Mpl, especially TMP/4. To understand the mechanism of binding behavior between the mimetic peptides and c-Mpl receptor, the molecular modeling research was also approached. It presented several important issues related with its high biological activities, including (1) Hydrophobic interaction was the driven positive forces for the interaction between the peptides and cMpl receptor proved by analysis of binding modes and energy decomposition; (2) The larger distances between the centroids of the P-Helix and P’-Helix, togather with the bigger surface area and volume of peptides generally did great favor to the binding behavior, thus resulted a highest biological activity; (3) TPO peptide residues in P7, P13 and P70 positions were identified by the analysis of hydrogen bonds and energy decompositions as the key ones for benefiting better biological activities. In all, the data in present research suggested the synthesized peptides have considerable potential for the future development of stable and highly active TPO mimetic peptides.

Acknowledgements This work was financially supported by the National Natural Science Foundation of China (No. 31000017) (No. 21207056) (No. 21307050), the special international cooperation project of MOST (No. 2012DFA30480), the State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences (KF2015-17).

A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.bmc.2016.12.022. Reference 1. Kaushansky K, Lok S, Holly RD, et al. Promotion of megakaryocyte progenitor expansion and differentiation by the c-Mpl ligand thrombopoietin. Nature. 1994;369:568–571. 2. Grossmann A, Lenox J, Deisher TA, et al. Synergistic effects of thrombopoietin and granulocyte colony-stimulating factor on neutrophil recovery in myelosuppressed mice. Blood. 1996;88:3363–3370. 3. Ulich TR, del Castillo J, Yin S, et al. Megakaryocyte growth and development factor ameliorates carboplatin-induced thrombocytopenia in mice. Blood. 1995;86:971–976. 4. Basser RL, Rasko JE, Clarke K, et al. Randomized, blinded, placebo-controlled phase I trial of pegylated recombinant human megakaryocyte growth and development factor with filgrastim after dose-intensive chemotherapy in patients with advanced cancer. Blood. 1997;89:3118–3128. 5. Fanucchi M, Glaspy J, Crawford J, et al. Effects of polyethylene glycolconjugated recombinant human megakaryocyte growth and development factor on platelet counts after chemotherapy for lung cancer. N Engl J Med. 1997;336:404–409. 6. Harker LA, Roskos LK, Marzec UM, et al. Sheridan, Effects of megakaryocyte growth and development factor on platelet production, platelet life span, and platelet function in healthy human volunteers. Blood. 2000;95:2514–2522. 7. Thrombopoietin WHT. Whatever happened to thrombopoietin? Transfusion. 2002;42:279–283. 8. Vadhan-Raj S, Murray LJ, Bueso-Ramos C, et al. Stimulation of megakaryocyte and platelet production by a single dose of recombinant human thrombopoietin in patients with cancer. Ann Intern Med. 1997;126:673–681. 9. Basser RL, O’Flaherty E, Green M, et al. Development of pancytopenia with neutralizing antibodies to thrombopoietin after multicycle chemotherapy supported by megakaryocyte growth and development factor. Blood. 2002;99:2599–2602. 10. Kimura T, Kaburaki H, Tsujino T, Ikeda Y, Kato H, Watanabe Y. A non-peptide compound which can mimic the effect of thrombopoietin via c-Mpl. FEBS Lett. 1998;428:250–254. 11. Kuter DJ, Begley CG. Recombinant human thrombopoietin: basic biology and evaluation of clinical studies. Blood. 2002;100:3457–3469. 12. Li J, Yang C, Xia Y, et al. Thrombocytopenia caused by the development of antibodies to thrombopoietin. Blood. 2001;98:3241–3248. 13. Vadhan-Raj S, Verschraegen CF, Bueso-Ramos C, et al. Recombinant human thrombopoietin attenuates carboplatin-induced severe thrombocytopenia and the need for platelet transfusions in patients with gynecologic cancer. Ann Intern Med. 2000;132:364–368.

Please cite this article in press as: Liu Y., et al. Bioorg. Med. Chem. (2016), http://dx.doi.org/10.1016/j.bmc.2016.12.022

Y. Liu et al. / Bioorganic & Medicinal Chemistry xxx (2016) xxx–xxx 14. Alexander WS. Thrombopoietin and the c-Mpl receptor: Insights from gene targeting. Int J Biochem Cell Biol. 1999;31:1027–1035. 15. Frederickson S, Bowdish KS. A rationally designed agonist antibody fragment that functionally mimics thrombopoietin. Proc Natl Acad Sci U S A. 2006;103:14307–14312. 16. Kuter DJ. Thrombopoietin and thrombopoietin mimetics in the treatment of thrombocytopenia. Annu Rev Med. 2009;60:193–206. 17. Kuter DJ. New thrombopoietic growth factors. Clin Lymphoma Myeloma. 2009;9:S347–356. Suppl 3. 18. Wrighton NC, Farrell FX, Chang R, et al. Small peptides as potent mimetics of the protein hormone erythropoietin. Science. 1996;273:458–464. 19. Vigon I, Mornon JP, Cocault L, et al. Molecular cloning and characterization of MPL, the human homolog of the v-mpl oncogene: Identification of a member of the hematopoietic growth factor receptor superfamily. Proc Natl Acad Sci U S A. 1992;89:5640–5644. 20. Alexander WS, Metcalf D, Dunn AR. Point mutations within a dimer interface homology domain of c-Mpl induce constitutive receptor activity and tumorigenicity. EMBO J. 1995;14:5569–5578. 21. Bazan JF. Structural design and molecular evolution of a cytokine receptor superfamily. Proc Natl Acad Sci U S A. 1990;87:6934–6938. 22. Kuter DJ. Biology and chemistry of thrombopoietic agents. Semin Hematol. 2010;47:243–248. 23. Cwirla SE, Balasubramanian P, Duffin DJ, et al. Peptide agonist of the thrombopoietin receptor as potent as the natural cytokine. Science. 1997;276:1696–1699. 24. Serres MMD, Ellis B, Dillberger JE, et al. Immunogenicity of thrombopoietin mimetic peptide GW395058 in BALB/c mice and New Zealand white rabbits: evaluation of the potential for thrombopoietin neutralizing antibody production in man. Stem Cells. 1999;17:203–209. 25. de Serres M, Yeager RL, Dillberger JE, et al. Pharmacokinetics and hematological effects of the PEGylated thrombopoietin peptide mimetic GW395058 in rats and monkeys after intravenous or subcutaneous administration. Stem Cells. 1999;17:316–326.

9

26. Krause S, Schmoldt HU, Wentzel A, Ballmaier M, Friedrich K, Kolmar H. Grafting of thrombopoietin-mimetic peptides into cystine knot miniproteins yields high-affinity thrombopoietin antagonists and agonists. FEBS J. 2007;274:86–95. 27. Yamane N, Tanaka Y, Ohyabu N, et al. Characterization of novel non-peptide thrombopoietin mimetics, their species specificity and the activation mechanism of the thrombopoietin receptor. Eur J Pharmacol. 2008;586:44–51. 28. Bussel JB, Kuter DJ, George JN, et al. AMG 531, a thrombopoiesis-stimulating protein, for chronic ITP. N Engl J Med. 2006;355:1672–1681. 29. Sambrook J, Russell DW. SDS-polyacrylamide gel electrophoresis of proteins. CSH Protoc. 2006;2006. 30. Zhang Y. I-TASSER server for protein 3D structure prediction. Bmc Bioinf. 2008;9:297–315. 31. Syed RS, Reid SW, Li C, et al. Efficiency of signalling through cytokine receptors depends critically on receptor orientation. Nature. 1998;395:511–516. 32. Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc. 2010;5:725–738. 33. Ryckaert JP, Ciccotti G, Berendsen HJC. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n alkanes,. J Comput Phys. 1977;23:327–341. 34. Dixit A, Verkhivker GM. Hierarchical modeling of activation mechanisms in the ABL and EGFR kinase domains: Thermodynamic and mechanistic catalysts of kinase activation by cancer mutations. PLoS Comput Biol. 2009;5:e1000487. 35. Liu H, Bao W, Ding H, Jang J, Zou G. Binding modes of flavones to human serum albumin: insights from experimental and computational studies. J Phys Chem B. 2010;114:12938–12947. 36. Han C, Fang S, Cao H, et al. Molecular interaction of PCB153 to human serum albumin: insights from spectroscopic and molecular modeling studies. J Hazard Mater. 2013;248–249:313–321. 37. Ke T, Zhang J, Jie L. Fast protein loop sampling and structure prediction using distance-guided sequential chain-growth monte carlo method. PLoS Comput Biol. 2014;10. e1003539.

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