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De Novo computational design for development of a peptide ligand oriented to VEGFR-3 with high affinity and long circulation Hong M. Li, Zhi P. Dong, Qi Y. Wang, Li X. Liu, Bing X. Li, Xiao N. Ma, Ming S. Lin, Tao Lu, and Yue Wang Mol. Pharmaceutics, Just Accepted Manuscript • Publication Date (Web): 16 May 2017 Downloaded from http://pubs.acs.org on May 17, 2017

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Molecular Pharmaceutics

De Novo computational design for development of a peptide ligand oriented to VEGFR-3 with high affinity and long circulation Hong M. Li†, Zhi P. Dong†, Qi Y. Wang†, Li X. Liu†, Bing X. Li†, Xiao N. Ma‡, Ming S. Lin§, Tao Lu*∥, Yue Wang*†

†

Key Laboratory of Biomedical Functional Materials, School of Sciences, China

Pharmaceutical University, Nanjing 211198, Jiangsu Province, China. ‡

Cellular and Molecular Biology Center of China Pharmaceutical University, Nanjing,

China. §

TA Instruments-Waters LLC, Shanghai, China.

∥

State Key Laboratory of Natural Medicines, School of Sciences, China

Pharmaceutical University, Nanjing 211198, Jiangsu Province, China.

KEYWORDS: computational design, peptide ligand, cancer target, long circulation ABSTRACT: The overexpression of VEGFR-3 is correlated with a worse prognosis in lung cancer and has been regarded as a rational target for specific drug delivery. Here, VEGFR-3 homing peptide library was efficiently established by computational design. Strong fluorescent signal of selected peptides were observed in A549 cells, but much weaker in other cells. The positive immunostaining overlapped with VEGFR-3 confirmed high affinity and selectivity of one novel peptide (CP-7). In addition, cell uptake of FITC-CP-7 peptide was significantly blocked by co-injection 1

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of excess CP-7 peptide. After labeled with

131

I, the profile of pharmacology and

biodistribution could be traced in vivo. The 131I-radiolabeled CP-7 peptide conjugates were >85% stable in serum over 4 h and exhibited a specific uptake of 18.04 ± 2.04% ID/g at 0.5 h after injection to high VEGFR-3 expressing A549 tumor mice. More importantly, lower uptake concentration in heart (1.06 ± 0.15%ID/g) after 2 h demonstrated the safety of peptide in vivo. The high uptake in the kidneys revealed that renal clearance was the main route of 131I-CP-7 peptide elimination from the body. Lower accumulation of

131

I-CP-7 peptide in VEGFR-3 negative HeLa tumor mice

further indicated that CP-7 peptide exhibited a higher tumor-homing efficiency. These studies provided a straightforward analytical access to design and screen bioactive peptide based on protein structure and revealed that CP-7 peptide represented a promising homing peptide of VEGFR-3-positive cancer in vitro and in vivo which could be used as a novel target molecule to achieve the efficient drug delivery.

INTRODUCTION Cancer is a kind of devastating disease by its high mortality1-3. Various approaches, such as curative surgery, radiotherapy4 and chemotherapy5, 6, have been used for treatment. The major challenge limiting the success of cancer therapeutics is the low concentration of anticancer agents in the tumor tissue along with high rates of tumor recurrence and metastasis7-9. So to develop new molecules and strategies to target cancerous sites while sparing normal tissues are highly desired and have been actively pursued10. Such molecule should be favorable selective and specific to the related

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tumors11. It can be utilized to achieve selective tumor cellular delivery by targeting cell-surface receptors that subsequently undergo receptor-mediated endocytosis, and hence provide opportunities for targeted delivery, especially where specific receptors are over-expressed. Among them, peptides with small sizes, good biocompatibility and high affinity for protein which are always overexpressed in tumor cells, have been regarded as the promising ligands for targeted therapy12.

Vascular endothelial growth factor receptor-3 (VEGFR-3) is a transmembrane receptor tyrosine kinase that is overexpressed in multiple kinds of tumors, such as non-small-cell lung cancer, myeloid leukemia and ovarian cancer13. VEGFR-3 can be activated by its specific ligand, VEGF-C/D, resulting in promotion of angiogenesis and lymph angiogenesis. Several peptides binding to VEGFR-3 have been reported to modulate VEGF-dependent biological activity

14-16

. The phage displaying peptide

LARGR and CSDSWHYWC exhibited high affinity to VEGFR-3 and could bind to VEGFR-3 specifically in a dose-dependent manner14, 15. Su has also reported two peptides with low toxicity, high selectivity to VEGFR-3 and suppressed VEGF-C-mediated invasion of cancer cells in a more natural way16. Although some peptides have showed the potential affinity to the tumor cells, the binding efficiency in vivo still remain to be explored17. The safety and stability in serum of the promising peptide should also been considered for further application. It is expected that when employed as a tumor targeting agent, peptide could be selectively penetrated in tumor tissue and then further drug will be released in vivo. However, most of these peptides were discovered by phage display screening or 3



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combinatorial peptide libraries with quite long time and cost-consuming18,

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. In

contrast, computationally designing homing peptides through virtual docking is promising and challenging20. It relies on the crystal structures of novel surface proteins and the precision of binding site. Hence, using the de novo peptide design method is feasible and efficient to obtain the peptide that binds to the surface protein. In this study, we attempted to screen and identify peptides with strong affinity to tumors both in vitro and in vivo. The extracellular domain (ECD) of the VEGFR-3 constituted by seven immunoglobulins (Ig)-like domains has been reported13 and provides a basis for further development of target peptide via bioinformatics design. A random 7-mer peptide library was self-constructed by analyzing the crystal structure against the extracellular domain of VEGFR-3. The peptide was synthesized through solid-phase synthesis and labeled with fluorescein isothiocyanate (FITC) for peptide-cell interactions. Human lung adenocarcinoma cell line (A549), human cervical carcinoma cell line (HeLa) and normal human lung fibroblasts cell line (HFL-1) with different expression levels of VEGFR-3 were chosen for screening the peptide14, 29. We found CP-7 (CIQPFYP) peptide showed high uptake by the A549 cells (high expression level of VEGFR-3) and very little affinity for the control HeLa and HFL-1 cells (low expression level of VEGFR-3) as control. Radioactive iodine-131(131I) labeled- CP-7 peptide was utilized to evaluate pharmacokinetic and bio-distribution profiles in A549 xenogeneic mouse models. It showed the enrichment of peptides in tumors compared to other organs. The high specificity of the selected peptide in vitro and in vivo demonstrated its potential as an efficient molecule for

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further application in drug delivery.

RESULTS AND DISCUSSION Peptide design and virtual screening De novo design of homing peptides that can bind to a given target by computational design is challenging. The procedure involved in docking studies usually includes the following steps: (i) representation and definition of the binding site, (ii) conformational analysis of the ligands, (iii) placement of the ligands in the protein (generation of docking poses), (iv) estimation of the fitness of the poses (intermediate scoring), and (v) final scoring of the docked poses. The detection of binding site for virtual screening of a structural library of peptides is not straightforward for the protein flexibility. FT Map is particularly useful and accurate in predicting bound poses of the user-selected molecules and detecting whether a molecule is likely to bind in the hot spot region, and finally providing input for the design of larger ligands21. Three hotspots of the extracellular domain of VEGFR-3 were discovered by FT Map (Figure 1a). The selected binding site region of VEGFR-3 for further peptide design was the site 2, which has a deep pocket and large size for conformational conversion, and particularly far from the natural ligand VEGF binding site region. To better explore the protein-ligand binding interaction, the frequency of both H-bonded for each residue were also calculated (Figure 1b). After global alignment, the active site2 region was surrounded by the amino acid residues, such as (458 TRP, 545 ARG,

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548 TYR) and seems to be suitable for generating the conformational ensembles of bioactive peptide.

Next, the self-constructed peptide library containing 576 peptides was established based on the concept of sense (S) and anti-sense (AS) peptide interactions, driven by the Mekler-Idlis amino acid pairing theory22. The residues surrounding the presume pocket (5 Å) were identified. Anti-sense peptide theories served as a systematic and efficient route to design some types of peptide antagonists, have been reported to support the possible use of some antisense peptides as novel drug leads23. Preliminary experiment data supported the possible use of the antisense peptide theories24-26. We have tried several kinds of sense peptides, such as TYLRK, TYLRKIW, VYLRKTIW. After the simulation, we found that TYLRKIW could fit in the selected binding sites reasonably when it was docked into the region. The major H-bond interactions of TYLRKIW and VEGFR-3 complex occurred (Figure S1). Thus, we used TYLRKIW as the target sense residues. Molecular Docking simulate protein-ligand interaction via algorithms and conformational search, thus providing valuable information on bioactive conformations and attempting to discriminate between similar peptides in known active series27. Glide and Gold software applications with specific parameter settings were employed to virtually docking for cross-validation. The peptides were ranked in order of the scoring function, which relies on regenerated low-energy conformations of the ligands that are rigidly fitted into a defined binding site. Then the selected peptides (Figure 1c) were screened mainly by proper docking scores, accurate pose fitting, hydrogen bonding formation to crucial amino acid, native 6


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physical properties and synthesis capability (Figure 1d). With the computationally designing target peptides as a powerful method to analyze and estimate the protein-peptide interaction, the optimize peptides will be further developed.

Figure 1. (a) FT Map of the VEGFR-3. Protein is represented using surface model. (b) Hydrogen-bond (H-bond) frequency maps of the VEGFR-3. (c) Predicted binding models for represented peptide. (d) Sequence of the optimized peptides selected by binding to VEGFR-3.

Affinity of selected peptides to VEGFR-3 overexpressed tumor cells The selected peptides were synthesized by solid-phase techniques and labeled by 7



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FITC for cell binding experiment (Figure S2). Before that, we analyzed the relationship between VEGF-C-VEGFR3 expression and the survival of non-small cell lung cancer patients. We performed Kaplan−Meier analysis based on the available follow-up data from 196 non-small cell lung cancer patients. The baseline demographic and clinical characteristics of the patients were shown in Figure 2a. The survival analysis revealed that a survival advantage was identified in patients whose tumors had lower expression of VEGF-C-VEGFR-3 compared to those with higher expression (long-rank test, p < 0.05), indicating that VEGFR-3 overexpression is related with poor clinical outcome in non-small cell lung cancer. A549 cell, as one kind of the most widespread non-small cell lung cancer28, was chosen for screening the putative peptides. We then measured the fluorescence signal of FITC labeled peptide that bounded to A549 cells using flow cytometry to assess the affinity of selected peptides. Four peptides, 1(CP-7), 2 (CVQAFDP), 3(CVKPFYP) and 7(CVKTFDP) peptide showed strong binding to A549 cells compared to the positive control peptide (LARGR)15. The results showed that 94.6% of A549 cells were bounded by 1(CP-7) peptide while only 57.8% of A549 cells were bounded by LARGR (Figure 2b), which was obviously distinguished from the background. The remaining peptides caused weak fluorescence signal (Figure S3). The remarkable discrepancy of affinity between the selected peptides evaluated the rationality of peptide design via the virtual screening strategy.

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Figure 2. (a) Kaplan−Meier survival curve of lung cancer patients with VEGF-C-VEGFR3 expression. The long-rank test, p < 0.05. (b) Flow cytometry was performed to analyze the binding ability of the selected peptide to A549 cells.

Immunofluorescence study of the peptide to A549 cells To further evaluate whether CP-7 peptide would bind to the surface of VEGFR-3 over-expressed cells, we used immunohistochemistry to locate the peptides in A549 cells. As shown in Figure 3, A549 cells were stained positively (shown in red) for human VEGFR-3. Overlaid area (shown in orange) revealed that most of FITC labeled CP-7 (FITC-CP-7) peptide (shown in green) co-expressed VEGFR-3 (shown in red). Therefore, CP-7 peptide could be targeted to A549 tumor cells through VEGFR-3.

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Figure 3. Immunofluorescence co-localization of FITC-CP-7 peptide with an antibody specific for VEGFR-3. From left to right: Fluorescence micrograph of A549 cells stained with DAPI (blue), anti-VEGFR-3 (red), FITC (green), light field, and overlay (areas of co-localization are revealed in orange/yellow) (a–e). Scale bar = 20 µm.

Selective binding of the peptides to tumor cells The specific-binding ability of selected peptides was further confirmed by visualization using the confocal microscopy. Three sorts of cells at different levels in expression of VEGFR-3 were exploited to test binding activity of the selected peptides. Western blotting was used to detect the expression of the VEGFR-3 in three cells (A549, HeLa, HFL-1). Among the three cell lines, A549 expressed the higher level of VEGFR-3 while HeLa and HFL-1 expressed the lower14, 29 (Figure S4). FITC was used as control to estimate non-specific background binding30-32. When treated with FITC-CP-7 peptide, intensive green florescent signal was observed in A549 (Figure 4). By contrast, there was only poor florescence signal in HeLa or HFL-1. Similarly, 2 (CVQAFDP), 3(CVKPFYP) and 7(CVKTFDP) peptide displayed the same tendency (Figure S5). As expected, our results evaluated that the selected peptide could positively bind to A549 cells, but neither bound to HeLa nor to HFL-1 cells (Figure 4), which indicate that CP-7 peptide could be considered as a specific peptide for further binding detection. We then explored the receptor-binding affinity of FITC-CP-7 with that of CP-7 peptide using a competitive cell-binding assay. Weak

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fluorescent signal was observed when 1 mM CP-7 peptide was used as a blocking agent before adding the FITC-CP-7 to the cells, but green fluorescent signal was observed with 5 uM of CP-7 peptide. Therefore, cell uptake was significantly blocked by co-injection of excess CP-7 peptide. It is also suggested the specificity of the CP-7 peptide for A549 tumor cells and indicated that the excess administration of CP-7 peptide may result in its efflux from the cancer cells. These results are consistent with the observation that in immunofluorescence staining.

Figure 4. Confocal laser scanning microscope images of subcellular localization of FITC-CP-7 to A549, HeLa, HFL-1 cells. From left to right: Fluorescence micrograph of A549 cells stained with DAPI (blue), FITC (green), light field, and overlay (areas of co-localization are revealed in orange/yellow) (a–d). Scale bar = 10 µm.

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The binding affinity of CP-7 against VEGFR-3 We measured the binding affinity of CP7 peptide against VEGFR-3 through isothermal

titration

calorimetry

(ITC)

experiment.

Dissociation

constant

(Kd=3.47×10-6 ± 5.42×10-6 M) were then calculated from plots of the heat evolved per mole of ligand injected versus the molar ratio of ligand to protein using the software provided by the manufacturer. The n value is 1.028 ± 0.298. Kd (Kd=3.47×10-6

± 5.42×10-6 M) values are within the normal range (10-4-10-8 M-1) displayed by small peptide ligands. A favorable enthalpy (The heat of binding ∆H = −7.099 ± 5.63 KJ/mol) and the entropy changes (∆S = 80.72 J/mol·K) were yield by fitting. The interaction between CP7 peptide and VEGFR-3 was exothermic as indicated by positive peaks (Figure 5). The ITC experiment clearly confirmed the high binding affinity of the CP-7 peptide against VEGFR-3, which is comparable to many other reported peptides14, 16. These results are consistent with the above binding analysis, showing that CP-7 peptide could be targeted VEGFR-3 protein.

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Figure 5. ITC data for CP-7 peptide against VEGFR-3, Raw thermogram (top) and integrated titration curve (bottom) and fits with the one-binding site model.

MTT assay The cytotoxicity of the peptides on HFL-1 cells was evaluated using a traditional MTT assay. As a useful targeting molecule to achieve the effective drug delivery, its nontoxic safety should also be considered for the possible application. The results (Figure 6a) showed that there was a relatively high cell viability (more than 80% at a concentration of 50 µM) in HFL-1 cells which displays low cytotoxicity and favorable cell compatibility. Therefore, CP-7 peptide possesses high safety for tumor targeting under the current dosage.

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Figure 6. (a) Cell inhibition of CP-7 peptide on HFL-1 cells with different concentrations (b) Pharmacokinetic metrics of

131

I-CP-7 peptide in Rats after

Intravenous Administration. Pharmacokinetics analysis was performed with Phoenix WinNonlin 6.3 using a two-compartment model.

In vivo bio-distribution of 131I-labeled peptide The initial in vitro experiments showed that CP-7 peptide specifically bound to VEGFR-3 highly expressed tumor cells. We next sought to determine whether CP-7 peptide could target to tumor in vivo. The CP-7 peptide was firstly radiolabeled with 131

I for investigations. After purification by the centrifuged column procedure,

131

I-CP-7 peptide conjugates were obtained with radiochemical purities over 95% as

determined by Paper chromatography. In addition, we examined the stability of 131

I-CP-7 peptide by incubation CP-7 peptide with serum at 37°C for 4 h. Since about

85% of CP-7 was tested after 4h, it displayed sufficiently stable in serum. The radioactive counts of

131

I would be able to reflect the in vivo bio-distribution and

pharmacokinetic behavior of peptide. The pharmacokinetics of peptide in female rat were performed by administered at a single dose of 3.7×106 Bq and the blood at 14


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several time-points up to 24 h after the dose administration (Figure 6b) were collected. It is shown that the distribution half-life (t1/2α) was 0.91 h (Table 1), suggesting that peptide could be rapidly distributed and reached balance between blood and tissue after injection33, 34. The high MRT (22.67 h) demonstrated the peptide belong with long circulation and moderate drug exposure in vivo, which is essential for target molecule35. The lower concentration of 131I-CP-7 peptide in heart when administrated into the normal mice demonstrated the safety of CP-7 peptide in vivo (Table S1). Table 1. In vivo pharmacokinetic profiles of CP-7 peptide on mice. Best fit model: 2 compartment model C=A× e(-a×t) +B× e(-b×t) 131 parameter unit I-peptide A B a b k10 k12 k21 t1/2 α t1/2 β CL1 AUC0- t AUMC MRT Correlation (R2)

mg/ml mg/ml 1/h 1/h 1/h 1/h 1/h h h 1/h h×mg/ml h2×mg/ml h observed, predicted

0.031466 0.002871 0.762030 0.031048 0.256669 0.444228 0.092181 0.909413 22.32027 2.491546 0.133784 3.033073 22.67135 0.9913

As we know that the major barrier in cancer treatment is the lack of specificity of therapeutic agents to cancer cells in vivo36. Drug efficiency can be improved if the drug is targeted to tumor cells. Thus, it was important to investigate the mobility of this large molecule in vivo. In vivo accumulation of

131

I-CP-7 peptide in the A549

bearing tumor mice were determined (Figure 7a). The average concentrations in the

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tumors were 18.04 ± 2.04 and 6.80 ± 0.41%ID/g at 0.5 h, and 2 h respectively (Table 2), which is much higher than other normal organs, such as the heart, spleen and lung (Figure 7a). CP-7 peptide showed specific homing to tumor with concentrations 9-fold higher than its concentration in the heart, confirming the target property and safety of peptide used in vivo (Table 2). The uptake was high in the kidneys revealed that renal clearance was the main route of 131I-CP-7 peptide elimination from the body. The in vivo targeting property of 131I-CP-7 to HeLa xenograft tumors was assessed by injecting 131I-CP-7 via tail vein to mice. As is shown in Figure 7b, 131I-CP-7 displayed lower accumulation in HeLa tumor cells compared to the uptake of that in A549 tumor cells at 0.5 h. There was no significant difference in CP-7 peptide distribution in other organs (liver, lung, and kidney) when treated with HeLa and A549 tumor models (Figure S8). These results confirmed that CP-7 peptide could home to A549 tumor tissue and significantly potentially enhance drug accumulation in tumor when conjugated with drugs.

Figure 7. (a) Bio-distribution of radioactivity after intravenous administration of 131

I-peptide in A549 tumor mice at 0.5 h, 1 h, 2 h, 4h (b)Bio-distribution of

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radioactivity after intravenous administration of 131I-peptide in A549 and HeLa tumor mice at 0.5 h

Table 2. In vivo bio-distribution profiles of 131I-CP-7 peptide on A549 tumor-bearing mice. %ID/g recover after organ or tissue 0.5 h 1h 2h 4h heart 2.34 ± 0.93 0.51 ± 0.16 1.06 ± 0.15 1.06 ± 0.01 liver 7.55 ± 0.82 1.08 ± 0.20 1.98 ± 0.28 2.06 ± 0.03 spleen 4.58 ± 0.21 1.15 ± 0.17 2.31 ± 0.31 2.07 ± 0.01 lung 3.58 ± 1.14 0.63 ± 0.08 1.87 ± 0.47 1.04 ± 0.02 kidney 9.21 ± 1.92 4.94 ± 1.16 4.17 ± 0.32 3.63 ± 0.35 tumor 18.04 ± 2.04 4.12 ± 1.12 6.80± 0.41 3.47± 0.13

CONCLUSIONS We have developed a novel approach to screen peptides for specific target using molecular docking. A peptide library of 576 peptide sequences was designed based on Mekler-Idlis amino acid pairing theory. Cell binding experiment allowed identification of several peptides including CP-7 peptide that showed higher affinity and specificity for the A549 cancer cells, but not to the HeLa nor to HFL-1 cells as control. The immunofluorescence co-localization of FITC-labeled CP-7 with VEGFR-3 evaluated the CP-7 peptide could be targeted to the specific protein, thus indicating the rational of De Novo peptide design. In vivo distribution experiments demonstrated that CP-7 peptide could be mainly accumulated in the tumors while sparing assembled in other organs. Moreover, CP-7 peptide exhibited low toxicity and achieved long circulation when administrated in vivo. Such a safe and efficient targeting peptide offers new opportunity for cancer diagnosis and treatment. The De 17



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Novo peptide established in this study is not only useful for the discovery of cancer targeting peptides for tumor targeting therapy but also useful for the generation of diagnostic tools for cancer prediction.

MATERIALS AND METHODS Materials Peptides were synthesized by GL Biochem Peptide Ltd. (Shanghai, China). At the N terminus, peptides carried a fluorescein moiety conjugated via an aminohexanoic acid (Ahx) linker. When required, peptides were purified up to 95% purity by preparative reverse phase high-performance liquid chromatography (RP-HPLC) (Grom-SIL 120 ODS-4 HE, 125 mm × 20 mm, C18 column, 5 µm particle diameter; Grom, Herrenberg, Germany). The identity was validated via electrospray mass spectrometry with an LCQ A. Rabbit anti-VEGFR-3 (1:100, mab4391) and Alexa 555-conjugated secondary antibody (A20181, Molecular Probes, Leiden, the Netherlands) were obtained from R&D systems (Shanghai, China). DAPI and MTT was purchased from KeyGEN Biotech. All other chemicals used in this study were of analytical reagent grade and were used as received.

Peptide design and virtual screening The crystal structure of VEGFR-3 was downloaded from the RCSB Protein data bank (code: 4bsj). Missing residues were automatically fixed, and non-active ligands were removed. Crystal waters were maintained in the docking simulation. FT Map, a direct

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computational analogue of the experimental screening approaches, was applied to predict the putative binding site (also called hot spots) of the specific protein. The optimal binding pocket was picked out based on average energy and conformations by employing small organic molecules as probes on the surface of a target protein. The amino acid residue structures inside the hot spots were well-analyzed, and a self-constructed random 7-mer peptide library containing 576 peptides was designed based on Mekler-Idlis amino acid pairing theory. Molecular docking has been confirmed to be a reliable tool to visualize the omitted binding space and access the binding efficiency. Gold docking in the GOLD 3.1 from the Cambridge Crystallographic Data Center (CCDC) and Glide in the Schrodinger 2009 software were adopted for molecular docking analysis. For Gold docking, the space around the crystal ligands within a radius of 12.0 Å was deemed as the docking site. Ligand flexibility options were set with all planar R-NR1R2 flipped and with carboxylic acid deprotonated. The default setting was performed with a maximum of 100,000 genetic operations for each genetic algorithm run. ChemScore were used as scoring functions to distinguish the active conformation. Default cutoff values of 4.0 Å for van der walls (vdw) and 2.5 Å for H-bond interactions were employed. Ten conformations were retained for each ligand. For Glide, the Protein Preparation Wizard workflow was used to optimize the crystallized ligand of VEGFR-3 and other peptides. The specific amino acid residue was centered by an enclosing box by the “Receptor Grid Generation” mode to construct the docking grid files. Standard precision (SP) docking mode was selected for molecular docking. Other parameters remained with default

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settings. Finally, favorable compounds were identified mainly by taking Glide score, binding interactions and native property into consideration.

Peptide synthesis and modification with FITC The sequence for the peptide library is shown in Figure 1d. The synthetic targeting peptide CP-7 (CIQPFYP), other peptides (CVKPFYP, SVKPFYP, GIQPLYP…), and control peptide (LARGR) were synthesized (Gl Biochem (shanghai) Co., Ltd. Inc, China) and purified using reverse-phase high-performance liquid chromatography to 95% purity. The mass of the products was determined by ESI mass spectrometry. Conjugation of these peptides with FITC was performed through the addition of FITC to the peptide N-amino terminus by the aminocaproic acid as spacer.

Cell culture and animals A549, HeLa, and HFL-1 cell lines were provided by KeyGEN Biotech and maintained in Dulbecco's Modified Eagles Medium (DMEM) containing 10% fetal bovine serum (HyClone Laboratories, Inc. Logan, UT, USA) with 100 units mL-1 penicillin, and 100 mg mL-1 streptomycin. The cells were cultured in a humidified incubator at 37 °C, 5% CO2. Female Balb/c mice weighing 18-20 g, adult female mice weighing 18-22 g, female rat weighing 180-220 g were purchased from Nanjing Mu Tu Medical Science and Technology Co. and furnished by Experimental Animal Center, Jiangsu Academy of Traditional Chinese Medicine. Free access to food and water was allowed during housing. All mouse studies adhered to the principles of care

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and use of laboratory animals and were approved by the Institutional Animal Care and Use Committee of China Pharmaceutical University.

The target binding ability of the selected peptides to tumor cells by flow cytometry A549 cells were seeded at 2×105 in the 6-well microtiter plate 24 h to allow the cells to attach. After the cells were washed twice with PBS, 25 µM FITC-labeled peptides were added to the plate and cultured for 12 h in a 37 °C atmosphere containing 5% CO2. FITC (25 µM) was used as control. After cultivation for 24 h, the cells were washed twice with ice-cold PBS and harvested with trypsin-EDTA. The cells were then suspended in PBS and run on FACS Calibur Flow Cytometer (Becton Dickinson, San Jose, CA) to record the fluorescence intensity. FCS data were analyzed using FlowJo 7.6.

The selectivity of the peptides to tumor cells A549 and HeLa were separately seeded at 5 × 104 (HFL-1 cells was seeded at 1 × 104) in 35 mm dishes with glass bottom for 24 h to allow the cells to attach. After the cells were washed twice with PBS, FITC-labeled peptides were added to the dishes in a concentration of 25 µM. For Cell competition experiment, CP-7 peptide (1mM, 5 µM) were blocked for 2 h before incubated with FITC-peptide. After 4 h incubation, the cells were washed several times with PBS to remove the remaining samples and dead cells. Finally, the cells were observed under a confocal laser scanning microscope (CLSM, Carl Zeiss LSM 710) to evaluate the selectivity. 21



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Immunofluorescence staining A549 cells were cultured at 5 × 104 in 35 mm dishes for 24 h. After the cells were washed twice with PBS, FITC-CP7 peptide was introduced to the dishes for 4 h incubation and the cells were fixed in 4% paraformaldehyde at room temperature for 15 min. After washing with PBS, the adherent cell monolayer was permeablilized with 0.1% Triton X-100 in PBS and blocked for 1 h with 10% normal goat serum in 1% BSA/PBS, followed by overnight incubation at 4°C with primary antibodies: mouse anti-VEGFR-3 (1:100, mab4391, R&D). After washing with PBS, cells were incubated with the Alexa 564-conjugated secondary antibody (Fcmacs) for 1 h. Cells were then washed three times with PBS and mounted in DAPI. The slides were analyzed using a confocal laser scan microscope (CLSM, Carl Zeiss LSM 710).

Isothermal Titration Calorimetry (ITC) Experiments. The dissociation constant characterizing the binding of CP-7 peptide to VEGFR-3 was determined by using a Nano-ITC-LV (TA instrument, USA). A CP-7 peptide solution (final concentration 0.3 mM in 50 mM potassium phosphate buffer, pH 7.4) was prepared and titrated into an ITC cell containing VEGFR-3 (0.02 mM in 50 mM potassium phosphate buffer, pH 7.4) at 25°C. The data were recorded automatically and analyzed by NanoAnalyze software from TA instrument. Dissociation constant, binding enthalpy and stoichiometry were obtained by curve fitting with the one binding sites model. The heat of CP-7 dilution into buffer was considered as blank and subtracted before data analysis. 22


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MTT assay The cytotoxicity in vitro was measured by using the MTT assay against HFL-1 cells. In a typical procedure, cells were initially seeded into a 96-well cell culture plate at 1 ×103 per well and then incubated for 24 h at 37 °C under 5% CO2. DMEM solutions of CP-7 peptides at different concentrations were added under the same condition. After incubation for 48 h at 37 °C under 5% CO2. The cells were washed three times with 0.2 mL PBS to remove the unbound peptides. Subsequently, 0.2 mL DMEM and 25 µL MTT (5 mg mL-1) were added to each well and incubated for an additional 4 h at 37 °C under 5% CO2 Then the medium solution was replaced by 0.15 mL DMSO solution. After 10 min, the optical density at 490 nm (absorption value) of each well was measured on a Thermo Scientific Microplate Reader. Paclitaxel was used to be positive control.

Iodide radiolabeling and serum stability assays Briefly, Iodogen (1,3,4,6- tetrachloro-3α,6α-diphenylglycouril), a water-insoluble oxidant, was dissolved in dichloromethane and coated on the walls of the Eppendorf tube. Radioiodination was then initiated by adding 400 µL PBS (pH = 7.4) solution of peptides (1 mg/mL) and 3.7×107 Bq Na131I solution into Iodogen-coated tube. The reaction solution was shaken and incubated at 45°C for 6 h. Radiochemical yield was determined by paper chromatography using Whatman 1 paper strips (eluting solvent: water: propanol). Labeling efficiency was calculated using the equation (radioactivity on filter/total sampled radioactivity×100%). 23



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To ensure

131

Page 24 of 33

I is stable on peptide as a radiotracer, the stability of the

peptide in serum was assayed as follows: 100 µL of

131

131

I-CP-7

I -CP-7 peptide was added to

900 µL of mouse serum and incubated at 37°C. After a certain interval, the radiochemical purity of 131I -CP-7 peptide was examined by the same method.

The pharmacokinetics studies of 131I-CP-7 peptide Pharmacokinetics was investigated using adult female SD rats weighing 200-220 g and the compartmental model was used to calculate the pharmacokinetic parameters for

131

I-CP-7 peptide by fitting the concentration data in blood using the software

WinNonlin. Three rats were intravenously injected with preparation of

131

I-CP-7

peptide (3.7×106 Bq) through the tail vein and then 10 µL of blood samples were collected by means of a tail incision at 0.083, 0.5, 1, 2, 6, 12 and 24 h. Blood samples were measured for radioactive counts in a γ-counter and corrections were made for its background radiation and physical decay during counting. The pharmacokinetic parameters (area under the concentration time curve (AUC), distribution half-lives (t1/2α

in

plasma)

were

determined

from

individual

animal

data

using

second-compartmental analysis in WinNonlin (version 6.3, Phar- sight, CA).

In vivo bio-distribution of

131

I-CP-7 peptide in normal and tumor-bearing

mice Twenty-one mice were randomly divided into seven groups of three animals each. A dose of 3.7 × 105 Bq

131

I-CP-7 peptide (in 0.1 mL saline) was administered

intravenously to each mouse. The bio-distribution studies were performed by 24


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euthanizing the mice at 0.083, 0.5, 1, 2, 4, 12 and 24 h post-injection. The heart, liver, spleen, lung, kidney, and tumor were harvested, weighed, and measured for radioactivity as has been stated above. The organ uptake was calculated as a percentage of the injected dose per gram of wet tissue mass (%ID/g).

A549 tumor cells were harvested by trypsinization, washed three times with PBS. Injections were subcutaneous into the mammary fat pad on the left side and consisted of a single dose (2×106 cells) of A549 tumor cells to establish tumor xenografts. When the xenograft masses reached a size of ~100 mm3, twelve mice were randomly and equally divided into four groups. The tumor diameters were serially measured with calipers thrice per week, and the tumor volumes were calculated as follows: volume = length × (width)2 × 0.5. Each mouse (3 mice) was i.v. injected with 131

I-CP-7 peptide at a dose of 3.7×105 Bq (in 0.1 mL saline). The animals were

euthanized at 0.5, 1, 2, 4 h post-injection, and tumors and organs such as the liver, spleen, kidneys, heart, and lung were excised. The organ uptake was calculated as a percentage of the injected dose per gram of wet tissue mass (%ID/g).

HeLa xenograft tumors was established by the same protocol. When the tumors reached 100 mm3 after 2 weeks, 131I-CP-7 peptide were injected via the tail vein, were used as control. After the same time point, mice were sacrificed by cervical dislocation, organs and tumors were harvested. The organ and tumor uptake was calculated as a percentage of the injected dose per gram of wet tissue mass (%ID/g).

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ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge. Predicted docking model, electrospray mass spectrometry, flow cytometry data, western blotting image, CLSM images, stability data, in vivo bio-distribution profiles.

AUTHOR INFORMATION Corresponding Author *Tao Lu.: State Key Laboratory of Natural Medicines, School of Sciences, China Pharmaceutical University, Nanjing 211198, Jiangsu Province, China. E-mail: [email protected] *Yue Wang.: Key Laboratory of Biomedical Functional Materials, School of Sciences, China Pharmaceutical University, Nanjing 211198, Jiangsu Province, China. E-mail: [email protected]

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENTS The authors gratefully acknowledge the support of the National Natural Sciences Foundation of China (no. 21401216) and Qing Lan Project in Jiangsu Province.

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Page 32 of 33

strategies for enhanced cell uptake, transcellular transport, and circulation: Mechanisms

and

challenges.

Adv

Drug

Deliv

10.1016/j.addr.2016.06.002.

32


Rev

2016,

doi:

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Table of Contents

A novel solution to design bioactive peptide based on bio information tool and the biological evaluation in vitro and in vivo.

33


De Novo Computational Design for Development ... - ACS Publications

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