Nonimmobilized Biomaterial Capillary Electrophoresis for Screening

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Non-immobilized Biomaterial Capillary Electrophoresis for Screening Drugs Targeting hGlut1 Ruijun Wu, Kai Zhu, Xiaodan Zhang, Sufang Zhang, Yanmeng Liu, Jinyu Ren, Cong Li, Min Ye, and Xiaomei Ling Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b03811 • Publication Date (Web): 03 Nov 2017 Downloaded from http://pubs.acs.org on November 5, 2017

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Analytical Chemistry


Non-immobilized Biomaterial Capillary Electrophoresis for Screening Drugs Targeting hGlut1 Ruijun Wu, Kai Zhu, Xiaodan Zhang, Sufang Zhang, Yanmeng Liu, Jinyu Ren, Cong Li, Min Ye, Xiaomei Ling* The State Key Laboratory of Natural and Biomimetic Drugs and School of Pharmaceutical Sciences, Peking University, Beijing 100191, P. R. China ABSTRACT: We report an on-line ligand screening method by targeting human Glucose transporter 1 (hGlut1) under approximately physiological conditions, named non-immobilized biomaterial capillary electrophoresis (NIBCE), and investigated the interactions between drugs/candidate-compounds and the HEK293 cells, hGlut1-overexpressed HEK293 cells, NSCLC A549 cells, A549 tumor tissue, or normal lung tissue by simulating the interactions between drugs and moving target cells or the space-occupying tumor. NIBCE omits the trouble of isolating and purifying target receptors from cell membrane while maintaining their native conformation and binding activity. The biomaterials were intercepted by porous frits in capillary columns and cannot flow through the detection window, thereby solving the problem of interference detection; and also can be renewed anytime flexibly, thus effectively maintaining their surface bioactivity. Furthermore, the binding kinetic parameters (K, ka, kd, and k’) were calculated by non-linear chromatography (NLC) theory, and competitive binding experiments, ligand docking studies, anti-tumor activity assays in-vitro and in-vivo were performed to verify the feasibility of NIBCE.

Due to the disadvantages of traditional biological methods and traditional analytical methods, the cell biochromatography has been developed to study the interactions between small ligands and cell membrane receptors, such as cell membrane liquid chromatography (CMLC), cell membrane capillary electrophoresis 13-15 (CMCE), and cell-immobilized capillary electrophoresis (CICE). However, these methods still have some shortcomings such as complicated preparation, long operation cycle, and short service life, and cannot be applied to screen ligands by other biomaterials except for the receptors on cell membrance. Therefore, in this research, we established a novel on-line ligand screening method by targeting hGlut1, named non-immobilized biomaterial capillary electrophoresis (NIBCE). The frit with controllable aperture was bonded on one end of the inner wall of a capillary, which was closely linked to the other capillary with detection window by a connecting sleeve. The capillary columns with porous frits for intercepting biomaterials were used to rapidly screen compounds by dynamic (Figure 1a), static (Figure 1b) or competitive (Figure 1c) electrophoresis mode. Here, the biomaterials included the HEK293 cells, hGlut1-overexpressed HEK293 cells, A549 cells (non-small cell lung cancer, NSCLC), A549 tumor tissue, and normal lung tissue. Using this new established method, we investigated the interactions between hGlut1-overexpressed HEK293 cells and the flavonoids extracts and monomeric compounds of Scutellaria baicalensis considering their extensive anti-tumor activities. In so doing, the binding kinetic parameters (K, ka, kd, and k’) between the biomaterials and the active compounds

In oncology, the Warburg effect is the observation that most cancer cells require enhanced glucose supply in part due to the less 1 efficient energy production through anaerobic glycolysis. Elevated expression levels of Glut1 have been observed in several cancer types, identifying Glut1 as a crucial prognostic indicator for tumorigenesis and reminding us to formulate a more effective 2-4 anticancer strategy by targeting hGlut1. In 2014, the crystal structure of Glut1 was successfully captured by Professor Nieng 5 Yan, which is very important for us to understand the mechanism of glucose transport and related diseases. The main inhibitors of Glut1 were its antibodies and small molecular ligands, 6 7 8 such as EGCG, fasentin, and apigenin, but in the present there were still no clinically effective inhibitors targeting Glut1. So, it is urgent to find selective and potent small molecular inhibitors of Glut1 for anti-cancer therapy. In traditional Chinese medicine, herb Scutellaria baicalensis Georgi has had a long history for more than 2000 years since “Shen Nong’s Herbal Classic”. The bioactive flavonoids derived from the root of Scutellaria baicalensis have been reported to have anti-inflammatory, anti-oxidant, and anti-tumor effects on 9-11 cancers of lung, colon, liver, etc. Their broad anti-tumor activities are mainly due to the induction of cell cycle arrest, apoptosis 12 in the G0/S phase, and inhibition of signal pathways. And we expect to find more inhibitors of Glut1 by investigating the interactions between flavonoids extracts of Scutellariae baicalensis and Glut1.

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Analytical Chemistry were calculated by non-linear chromatography (NLC). Meanwhile, the results of both qualitative and quantitative characterizations were verified by CICE (Figure S1a). Moreover, to find whether glucose could compete with the active compounds for the binding center of hGlut1, we carried out competitive binding experiments by NIBCE and CICE (Figure S1b). And ligand docking studies were performed by the Glide module to find additional evidence of direct interactions between active compounds and Glut1. Furthermore, it was verified by the anti-tumor assays in cell and animal levels that baicalein and baicalin had high anti-cancer efficiency and low systemic toxicity. All of the results provided a new interpretation for anti-tumor mechanism of flavonoids from Scutellaria baicalensis. In brief, we established a novel on-line ligand screening method by targeting hGlut1, named NIBCE. In this method, the separation and purification of target receptors from cell membranes is needless, and the biomaterials can be renewed anytime, maintaining their natural conformation and activity and making the capillary columns be recycled. And the biomaterials cannot flow through the detection window because of the presence of frits, which solves the problem of interference detection and makes it possible to quickly identify the active components in the mixture by CE-MS. More importantly, only in NIBCE we can perform experiments under approximately physiological conditions, which can better simulate interactions between drugs and target cells/the space-occupying tumor. Therefore, not only NIBCE was a fast, efficient, and flexible drug screening method and will be expected to become a new strategy to screen target drugs, but also its application scope was broadened immensely because different biomaterials could be used as its interaction phase.

were purchased from Beijing Chemical Reagent Factory (Beijing, China). Dimethyl sulfoxide (DMSO) was purchased from Sigma Chemical (St. Louis, MO, USA). Epigallocatechin gallate (EGCG) and 8 compounds extracted from Scutellaria baicalensis were purchased from Beijing Atmeng Technology Ltd. (Beijing, China). A total of 40 mM phosphate buffer (PB, pH 7.4), served as running buffer, was prepared with deionized water derived from a Millipore Milli Q-Plus system (Millipore, Bedford, MA, USA). Samples were diluted with running buffer to the molar concentration. All the CE solutions were filtered through 0.45 μm membranes (Agilent, Germany) before use. Methl thiazolyl tetrazolium (MTT, 25 mg) was obtained from Amresco. RPMI 1640 medium and FBS were purchased from Life Technologies. Silicon dioxide (SiO2 powder, 10 μm, 99.99% metals basis) was purchased from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). Instrumentation. The experiments were performed on a TM Beckman P/ACE MDQ system (Beckman Coulter, Fullerton, CA, USA) equipped with a photodiode array detector as well as the TM 32 Karat software version 5.0 (Fullerton, CA, Beckman). The bare fused silica capillaries (365 μm O.D.; 200 μm I.D.), used for capillary electrophoresis, were purchased from Yongnian Optical Fibers (Hebei, China). Preparation of the capillary column with porous frits. Before preparation of silica-based frits, the capillary with a total length of 30.2 cm was activated by rinsing with methanol, 0.1 M HCl solution, 0.1 M NaOH solution, and deionized water in sequence. After purging the capillary with air, the capillary was cut into two pieces with equal lengths (about 15.0 cm): one piece for preparation of porous frit and the other one for preparation of detection window. SiO2 powder and NaOH solution were mixed homogeneously based on different ratios and the mixture was introduced into one end of the capillary and formed semi-finished product of frit with a thickness of 0.5 mm, and then it was sintered for a few seconds to become a porous frit in the capillary. The capillary with porous frit and the capillary with detection window (20.0 cm to detector) were connected using a connecting sleeve (365 μm I.D.). In order to prepare the silica-based porous frits with controllable aperture, mechanical stability, and pH stability, we optimized the following conditions: the diameters of SiO2 powder (5, 10, 30, 50 μm), the concentration of NaOH solution (0.5, 1, 2, 4, 6, 8 M), the ratios of SiO2 powder to NaOH solution (w/v: 6:1, 5:1, 4:1, 3:1, 2:1 mg/μL), and the sintering time (10, 15, 20, 25, 30 s). The column frits prepared under different conditions were evaluated by trinocular microscope (N-300M, Novel Optics, China) and scanning electron microscope (SEM, JSM-5600LV, JEOL, Japan). According to the results, the optimum conditions were listed as follows: SiO2 powder of 10 μm, NaOH solution of 6 M, SiO2 powder/NaOH solution ratio of 4:1 mg/μL, and sintering time of 20 s. The capillaries with porous frits were kept at room temperature before use. The newly prepared capillary columns with the frits were evaluated by micrographs and HPCE under different washing pressure (5, 10, 15, 20, 25, and 30 psi (1 psi = 6894.76 Pa)), different washing time (5, 10, 15, 20, 25, and 30 min), different voltage (1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 kV), solutions of different pH (1, 3, 5, 7, 11, 12, 13, and 14), different organic solvents (methanol, acetonitrile, and ethanol). At the same time, intraday, interday, and column-to-column RSD% of the peak heights and retention times

Figure 1. Schematic of the NIBCE for screening drugs targeting hGlut1. (a) The dynamic mode. (b) The static mode. (c) The competitive mode.

EXPERIMENTAL SECTION Chemicals and Reagents. All chemicals were analytical grade unless otherwise indicated. Disodium hydrogen phosphate, sodium dihydrogen phosphate, sodium hydroxide, hydrochloric acid, 4% paraformaldehyde, methanol, and absolute ethyl alcohol

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Analytical Chemistry cells were calculated according to the section of “Determination of kinetic parameters” in supporting information. Screening of active compounds targeting hGlut1. We preliminarily screened the flavonoids extracts of Scutellaria baicalensis using hGlut1-overexpressed HEK293 cells as interaction phase by NIBCE. To detect which one interacts with Glut1, we further screened 8 main components of Scutellaria baicalensis flavonoids using the same method and the above-mentioned conditions, according to the ultraviolet (UV) spectra. Competitive binding experiment. The experiments of the competitive binding between glucose and binding active compounds were performed by adding 0, 1, and 5 mM glucose as natural ligand of hGlut1 into running buffer solution and injecting hGlut1-overexpressed HEK293 cells as interaction phase into running capillary columns. According to the electrophoresis behaviors of the EGCG or binding active compounds, we could estimate if they and glucose competitively occupied the same binding sites of hGlut1. Investigating the interactions between compounds and other biomaterials by NIBCE. On the basis of screening results, we chose DMSO, EGCG, and the main compounds with binding activity to further study their interactions with other biomaterials as interaction phase, including A549 cells, A549 tumor tissue, and normal lung tissue. The experiment was performed under the same conditions as mentioned in section “The establishment of NIBCE”. When the tissues were used as interaction phase, they were injected into the capillaries, washed with running buffer solution, pushed to the left end of the frit, and formed a piece of 0.5 mm thickness, successively. Then this experimental system was balanced using running buffer solution and used for investigating the interactions between compounds and other biomaterials by NIBCE. All the biomaterials were renewed anytime by flexibly injecting them into or pushing them out of capillary columns, effectively maintaining the bioactivity of the targets on the cell membrance.

of DMSO under the different experimental conditions were calculated to evaluate the stability of the frits. Praparation of the biomaterials. HEK293 cells were cultured in RPMI 1640 supplemented with 10% FBS, penicillin (100 U/mL), and streptomycin (100 μg/mL) at 37 in the gas mixture of 5% 6 CO2 and 95% air. A total of 4 × 10 /mL HEK293 cells (400 μL) were transfected transiently using 20 μg of the hGlut1-eGFP (enhanced green fluorescent protein) at 123 V for 20 ms by an electric pulse generator (Electro Square PoratorECM830, BTX, San Diego, CA, USA). The cells after electrotransfection were cultured under the same condition as HEK293 cells for 36 - 48 h. The images of hGlut1-eGFP transfected HEK293 cells were captured using Leica TCS-NT confocal fluorescence microscope (Wetzler, Heidelberg, Germany) to detect if the transfection was successful. A549 cells obtained from KenGen BioTech (Jiangsu, China) were cultured in DMEM supplemented with 10% FBS, penicillin (100 U/mL), and streptomycin (100 μg/mL) at 37 in the gas mixture of 5% CO2 and 95% air. The HEK293 cells, hGlut1-overexpressed HEK293 cells, and A549 cells were harvested, washed, and sus7 pended in PBS at 1.0 × 10 /mL cells, fixed with 4% paraformaldehyde, and stored at 4 successively before use. The normal lung tissue and A549 tumor tissue were fixed with 4% paraformaldehyde once isolated for 12 - 24 h and stored in 75% ethanol at 4 before use, respectively. The establishment of NIBCE. Firstly, we optimized the electrophoretic conditions of NIBCE, in particular, with regard to the choice of the running buffer solution (pH 7.4 1×PBS, pH 7.4 2, 10, or 40 mM PB ), the applied voltage (1.0, 1.5, 2.0, 2.5, 3.0, 4.0 kV), separation pressure (0, 0.4, 0.5, 0.6, 0.7 psi), the cell density in4 5 jected into the running capillary column (1.0 × 10 , 1.0 × 10 , 1.0 6 6 7 × 10 , 5.0 × 10 , 1.0 × 10 /mL cells), and the electrophoresis mode when using cells as interaction phase (dynamic mode, static mode). The optimized results are as follows: running buffer solution with 40 mM PB (pH 7.4), separation voltage of 1.0 kV, separation pressure of 0.5 psi, cell density injected into the run7 ning capillary column with 1.0 × 10 /mL cells, and cartridge temperature of 25 . At the same time, intraday, interday, and column-to-column RSD% of the peak heights and retention times of DMSO and EGCG were investigated by renewing the hGlut1overexpressed HEK293 cells on the same or different capillary columns on five consecutive days to evaluate the reusability of the capillary columns. We employed EGCG (the known antagonist of Glut1) as a positive control and DMSO as a negative control to evaluate the established new method. We used cells as interaction phase, and after the cells were injected into capillaries with 2 psi for 10 s 7 with a density of 1.0 × 10 /mL cells, DMSO or EGCG was also injected into the running capillary column, respectively, then NIBCE started running. The electrophoretic behaviors of the two compounds were examined by NIBCE in three different kinds of capillaries, including: (1) without cells, (2) with normal HEK293 cells, and (3) with hGlut1-overexpressed HEK293 cells as interaction phase in running capillary column. In the experiment, the capillaries were washed with 40 mM PB (pH 7.4) between runs, and each kind of the sample was run in duplicate. Each peak profile of EGCG was smoothed and could analyzed using PeakFit software (version 4.11), and the kinetic parameters (K, ka, kd) for the interactions between EGCG and the hGlut1-overexpressed

RESULTS AND DISCUSSION Preparation of the capillary column with porous frits. To get the frits with good permeability and meet the need of intercepting biomaterials, the conditions of preparing column frits were optimized using single factor experiment. Firstly, when the diameter of silica powders was larger than 10 μm, the aperture of frits was too big to intercept cells completely, and cells would remain in the porous frits, and it also caused unfavorable bubbles in the process of electrophoresis in this condition. While when the diameter was less than 10 μm, the too high pressure of columns resulted in more time-consuming. So, 10 μm SiO2 powder was chosen to make the frits. Furthermore, we found that the SiO2 powder can be firmly bonded to the inner wall of the capillary after treatment with NaOH solution. The results showed that the agglomerated globules of SiO2 powders would increase with an increase in the concentration of NaOH (0.5, 1, 2, 4, 6, and 8 M), and when the concentrations of NaOH solution were lower than 6 M, the frits were detached from the capillary inner wall, but when the concentration was higher than 6M, the agglomerated globules of SiO2 powders were firmly bonded to the capillaries, which resulted in the higher pressures of the columns for CE running, so 6M NaOH was used for further experiments. The me-

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Analytical Chemistry chanical strength, permeability, and morphology of silica-based frits can be tuned by changing other conditions such as ratio of silica powder to NaOH solution (w/v: 6:1, 5:1, 4:1, 3:1, and 2:1 mg/μL) and sintering time (10, 15, 20, 25, and 30 s). The results showed that when ratio of silica powder to NaOH was 4:1 mg/μL, and sintering time was for 20 s, the prepared frits could meet the requirements of experiments very well. The SEM images of capillary with silica-based frits prepared under the optimized conditions were shown in Figure 2a and Figure 2b.

fected HEK293 cell membrane. After the HEK293 cells were transfected with the hGlut1-eGFP by electrotransfection and cultured 12, 16, 18, 24, 36, 42, and 48 h, respectively, the electric transfection efficiency of hGlut1-overexpressed HEK293 cells was different at different time points. The number of cells with green fluorescence and the total number of cells were counted by confocal microscopy at each time points. Transfection ratios (the number of cells with green fluorescence on the cell membrane/the total number of cells) and RSD% values were calculated. According to the curve of transfection efficiency - time (Figure S2a), it can be seen that the rate reached 60% at 36, 42, and 48 h after the electroporation, and the difference was not significant at the three time points, consistent with the results of flow cytometry (Figure S2b). So, 36 h was initially selected as the time point for immobilizing (fixed with 4% paraformaldehyde) hGlut1-overexpressed HEK293 cells. Fluorography photos of HEK293 cells transfected with plasmid DNA of GLUT1-eGFP were shown in Figure S2c. And confocal microscopy images of HEK293 cells transfected with GLUT1-eGFP on the inner wall of a capillary for CICE were shown in Figure S3. The cells fixed with 4% paraformaldehyde were stored at 4 and their activity were still observed after keeping for 30 days, and they can be renewed anytime by flexibly injecting them into or pushing them out of running capillary columns. In addition, the research also investigated whether viable cells without immobilization could be applied in this method. The results showed that when viable cells as interaction phase, the baseline was unstable and peak shape was irregular. Thus, living cells could not be employed in this method. It should be noted that when the cells are harvested, we should prevent the formation of cell debris to prevent the small particles to be remained in the porous frits. What’s more, when cells were injected into running capillary columns as interaction phase, there existed two different electrophoresis modes: “dynamic mode” (Figure 2c) and “static mode” (Figure 2d). “Dynamic mode” means cells as interaction phase are constantly mobile in the running capillary column. “Static mode” means the cells as interaction phase are immobile at the left of frit of the running capillary column. The establishment of NIBCE. Optimization of electrophoretic conditions. The experimental results showed that the 200 μm I.D. capillary was not only more suitable for the preparation of the column with frits, but also more suitable for the injection of biomaterials. The larger the diameter of running capillary column is, the more biomaterials injected into per unit area is, i.e., the more biotargets in the same area is. In order to analyze the interactions between ligands and biomaterials under approximately physiological conditions without negative influence on their morphology and bioactivity, pH 7.4 1×PBS as the running buffer solution was first used. However, the high ionic strength limits the applied voltage. Otherwise the low ionic strength will decrease efficiency and increase the analysis time, we tested different concentrations of the PB (pH 7.4 2, 10, and 40 mM PB) as running buffer solution and finally chose 40 mM PB (pH 7.4) owing to its suitable migration time and better peak shape. In order to further optimize migration time under this condition, different running voltages (1.0, 1.5, 2.0, 2.5, 3.0, and 4.0 kV) and running separation pressure (0, 0.4, 0.5, 0.6, and 0.7 psi) were tested. When the applied voltage reached 3.0 kV, overcurrent occurred, and con-

Figure 2. Images of frits and NIBCE mode. (a) The SEM images of the capillary with silica-based frits. (b) The SEM images of the frit prepared under the optimized conditions. (c) The microscopy images of cells in dynamic mode as interaction phase in running capillary column. (d) The microscopy images of cells in static mode as interaction phase in running capillary column.

The prepared capillary columns with the frits were evaluated under different washing pressures [5, 10, 15, 20, 25, and 30 psi (1 psi = 6894.76 Pa)], washing times (5, 10, 15, 20, 25, and 30 min) and voltages (1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 kV) by CE. The microscopy images revealed that there was little change in the morphology of the frits after rinsing with PBS at 30 psi pressure and 4.0 kV voltage for 30 min. In addition, NaOH or HCl solutions with different pH values (1, 3, 5, 7, 11, 12, 13, and 14) and different organic solvents (methanol, acetonitrile, and ethanol) were used to verify the pH tolerance and organic solvent tolerance of the frits. Before each sampling, the running capillary columns with the frits were rinsed reversely by alkali solution, acid solution, or organic solvent for 5 min, and then DMSO was injected into the running capillary column. The peak heights and retention times of DMSO were recorded before and after rinsing and their RSD% were calculated, respectively. It was shown that the capillary column frits had little change under the alkali or acid backlashing at pH 1-14, and had good tolerance to methanol, acetonitrile, and ethanol. Similarly, the reproducibility of the capillary column with frits was assessed by measuring the peak heights and the migration times of DMSO under the same conditions. The intraday RSD% of DMSO (n = 5) for the migration time and the peak height were 4.9% and 2.5%, respectively, their interday RSD% was 6.6% and 4.1%, respectively, and the RSD% of columnto-column (n = 3) was 9.0 and 6.8%, respectively. The results demonstrated that the prepared capillary columns with frits were reliable and could meet the requirements for further experiments. Preparation of the biomaterials. Electrotransfection. The hGlut1-eGFP fusion protein was expressed at the plasmid trans-

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Analytical Chemistry sidering that the properties of biomaterials could change as the voltage increases, 1.0 kV was finally chosen as the running voltage. And with the increase of separation pressure, the analysis time shortened, but the interaction time between ligands and receptors also did, which was unfavorable for interaction study in a certain level. So the separation pressure was set at the moderate one: 0.5 psi. The baseline and peak shape of the electropherograms obtained under the optimized NIBCE conditions were good enough for the qualitative and quantitative analysis. Furthermore, we examined the density of cells injected into the capillary column to confirm if they could affect the interactions between ligand and hGlut1. The hGlut1-overexpressed cells 4 5 6 6 were diluted to 1.0 × 10 , 1.0 × 10 , 1.0 × 10 , 5.0 × 10 , and 1.0 × 7 10 /mL with running buffer solution, respectively. DMSO (the negative control) or EGCG (the known antagonist of Glut1) was

injected into different running capillary columns whose inside contained hGlut1-overexpressed HEK293 cells of different densities. The peak shapes of DMSO in different running capillary columns had no significant difference, but retention times increased slightly with the increase of cell numbers (Figure 3a). When the 4 5 cell density was 1.0 × 10 and 1.0 × 10 /mL, the peak height of EGCG showed a certain decrease, and the broadening was not 6 obvious. When the cell density increased to 1.0 × 10 /mL, the peak shape of EGCG was significantly decreased, broadening, and 7 trailing. When increased to 1.0 × 10 /mL, the peak shape was very flat and attached to the baseline (Figure 3b). The results illustrated that when the number of cells was too small, the interactions between ligand and receptor were unobvious and 7 unreal. Thus, 1.0 × 10 /mL cells were selected as the cell density of the interaction phase for further experimental study. Each experiment was repeated twice with a good reproducibility.

Figure 3. Electropherograms of NIBCE. (a) (b) Electropherograms of DMSO and EGCG on different capillaries with hGlut1-overexpressed HEK293 cells (at different cell density) as interaction phases. (c) (d) Electropherograms of DMSO and EGCG at different electrophoresis mode and on different capillaries. (e) Electropherograms of flavonoids extracted from Scutellaria baicalensis on different capillaries. (f) (g) Electropherograms of the representatively negative compounds (Wogonoside) and positive compounds (baicalein) screened by NIBCE. (h) (i) Electropherograms of EGCG and baicalin in competitive binding experiment with different concentrations of glucose added into running buffer solution. (j) (k) (l) (m) Electropherograms of DMSO, EGCG, baicalein, and baicalin on different capillaries without biomaterials, with A549 cells, normal lung tissue, and A549 tumor tissue as interaction phase. Beckman P/ACE MDQ CE system with DAD, 214 nm. Injection: 1.0 psi for 10 s. Applied voltage: 1.0 kV. Capillary: capillary with frits of 30.2 cm (effective length 20 cm, 15 cm before column frits, 5 cm after column frits), 200 μm i.d. Running buffer solution: 40 mM PB (pH 7.40).

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Analytical Chemistry chromatography, the variation of electrophoretic peak shape in NIBCE is resulted from the interactions between compounds and interaction phase, and the asymmetric nonlinear chromatographic peak shape can be explained by nonlinear chromatography (NLC) model. Each peak profile of EGCG under different concentrations (100, 200, 500, 1000, and 2000 μM, Figure S4a) was smoothed and quantitatively analyzed using PeakFit software (version 4.11). And the kinetic parameters of the interactions between EGCG of different concentrations and the hGlut1overepressed HEK293 cells were calculated. The K and ka significantly increased along with the decrease of EGCG concentration (Figure S4b). That is because the competition between different classes of binding sites is dominated by small population but strong binding sites, which result in the higher values of the K and ka when the EGCG concentrations are low. On the contrary, when the concentrations of EGCG were high, strong binding sites of biomaterials were overloaded whereas large population but weak binding sites became a dominating factor, resulting in the lower values of K and ka. Therefore, lower concentrations of EGCG should be applied and kept below saturation. But because the interaction between EGCG and hGlut1 was so strong that only when the concentration of EGCG increased to 100 μM, could we detect the peak of EGCG on the capillary column with hGlut1overexpressed HEK293 cells as interaction phase. The average K of EGCG (100 μM) achieved by NIBCE was in agreement with that gotten by CICE (Table S1). Screening of active compounds targeting hGlut1. We screened the flavonoids extracted from Scutellaria baicalensis using hGlut1-overexpressed HEK293 cells as interaction phase by NIBCE. The electrophoregrams (Figure 3e) showed that the peaks of some compounds from flavonoids extracts were decreased, broadening, and trailing compared with those of the parallel control group, indicating that there existed binding affinity toward hGlut1 in these compounds. By comparing the UV spectra of electrophoretic peak of the extracts and those of flavonoid monomer compounds, we selected and screened 8 main flavonoids components (Figure S5) via NIBCE to detect which one had interaction with Glut1. Among them, the peak shapes of four compounds (wogonoside, oroxylin A-7-O-β-D-glucoronid, chrysin, and chrysin-7-O-β-D-glucoronid) were similar to that of the negative control, indicating that they didn’t have binding affinity toward hGlut1. In contrast, the peak shapes of the other four compounds (baicalein, baicalin, wogonin, and oroxylin A) were similar to that of the positive control, indicating that they have specific interactions towards hGlut1. The electrophoretogram of the representative compounds wogonoside (negative) and baicalein (positive) were shown in Figure 3f and 3g. The kinetic constants of the four active compounds were calculated by the NLC technique, and the results revealed good consistency with the kinetic constants obtained by CICE (Table S1). Competitive binding experiment. hGlut1 interacts with active compounds or glucose by hydrogen-bond, and this interaction is reversible and relatively weak. In order to find whether the active compounds could compete with glucose for the binding center of hGlut1, we performed competitive binding experiments by NIBCE and CICE (Figure S6). In competitive binding experiments, the concentrations of glucose added to running buffer solutions were in millimole level according to the concentration of glucose in

When cells as interaction phase, “static mode” and “dynamic mode” could lead to different experimental results. Figure 3c showed that peak shapes of DMSO were almost unchanged at “static mode” and “dynamic mode” in NIBCE, while the peak shape of EGCG (Figure 3d) in “static mode” showed more decreased, broadening, and trailing than that in “dynamic mode”, 4 and the binding constant (K = 3.05 × 10 /M) in “dynamic mode” 4 was smaller than that (K = 3.82 × 10 /M) in “static mode”. Therefore, both modes of NIBCE have their own characteristics. In dynamic mode, because cells are electronegative, compounds would pass through the dynamic cells under the dual role of electric seepage and electrophoresis. If the compounds and receptors had binding effects, they would interact with each other. The interactions between compounds and mobile target cells resulted in the binding effects in “dynamic mode”, which can better simulate the interactions between drugs in blood and moving target cells, making the calculated binding constant closer to the true value. In static mode, just like affinity chromatography, the interaction between active compounds and receptors was an iterative process that the compound continuously combines, dissolves, and recombines with the receptors. The interactions between compounds and immobile target cells resulted in the binding effects in “static mode”, which can better simulate the interactions between drugs and moveless target cells, making the calculated binding constants closer to the true value between drugs and the space-occupying tumor. Therefore, in the following investigations, experiments were carried out under “dynamic mode” when using cells as interaction phase, but experiments were carried out under “static mode” when using tumor tissue and normal lung tissue as interaction phase. However, we found that there also existed nonspecific interactions between EGCG and the membrane molecules except for hGlut1 (Figure 3d) by investigating interaction between DMSO or EGCG and three kinds of capillary columns with cells as interaction phase. Herein, the three kinds of capillary columns were without cells, with dynamic HEK293 cells, and with dynamic hGlut1-overexpressed HEK293 cells, as interaction phase respectively. But the peak of interaction between EGCG and hGlut1overexpressed HEK293 cells displayed lower peak height and longer retention time than that of the interaction between EGCG and HEK293 cells. Therefore, the interactions between ligands and receptors could be qualitatively analyzed by the electrophoretic peak shape. These results also demonstrated that the new method was able to identify the specific ligands of hGlut1 by discriminating the effect of nonspecific interactions between a ligand and other cell membrane molecules through the parallel control experiments. We investigated the intraday, interday, and batch-to-batch reproducibilities of the capillary columns. The RSD% of the intraday, interday, and batch-to-batch reproducibilities for the peak heights were 2.9%, 5.3%, 8.2% for DMSO and 5.8%, 9.5%, 12.4% for EGCG, respectively, and that for the migration times were 4.1%, 7.6%, 9.9% for DMSO and 6.9%, 10.7%, 13.5% for EGCG, respectively. Thus, it can be seen that the capillary columns could be recycled, and NIBCE could offer a simple, nontoxic, rapid, and economic way to detect the specific and nonspecific interactions between the ligand and cell membrane molecules. Determination of kinetic parameters. On the basis of affinity

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Analytical Chemistry hGlut1. It is known that the combination of three-dimensional (3D) culture and co-culture, namely 3D co-culture, can maintain the 16 intact structure as well as the activities of cells or tissues, but 3D co-culture also has some disadvantages, such as cumbersome operation, expensive reagents, and rigorous experimental conditions. NIBCE not only overcomes its shortcomings, but also can obtain the more real kinetic parameters than the 3D co-culture system. Therefore, studying the interactions between human tumor tissue and target drugs by NIBCE will be expected to become a new strategy to screen target drugs, provide their optimal kinetic parameters and scientific basis of the clinical anti-tumor therapy. In sum, we think that NIBCE broadens the application by introducing different biomaterials into capillary columns as interaction phase, and can be employed as one of the reliable, fast, effective screening methods in drug discovery, and adopted in capillary array electrophoresis or integrated capillary electrophoresis chips. Docking study. To find additional evidence for direct interactions between positive compounds and hGlut1, ligand docking studies were conducted using the Glide module of FirstDiscovery 2.7 (Schrodinger). Glide conducts flexible ligand docking to a rigid receptor using a grid-based docking method and scoring func17 tion. The compounds that are not inhibitors of hGlut1 could not enter into the activity pocket or had no interactions with the active sites. For example, the docking study revealed that the binding of baicalin to Glut1 involved 4 hydrogen bonds, one with Asn288, one with Gln283, and two with Glu380 (Figure 4). These amino acid residues are located in the central channel region of hGlut1. The results of EGCG, baicalein, baicalin, wogonin, and oroxylin A were shown in Figure S7. In addition, the docking study also revealed that the order of binding strength with hGlut1 was as follows: EGCG > baicalin > baicalein ≈ oroxylin A ≈ glucose (endogenous ligand of Glut1) > wogonin (Table S1). While in the experiment of screening active compounds targeting hGlut1, the order of the binding constants with hGlut1 was as follows: EGCG > baicalein ≈ baicalin > wogonin > oroxylin A.

blood, which are much higher than the concentration of active compounds. When no glucose was added to running buffer solutions, the peak shape of EGCG in the capillary column with hGlut1-overexpressed HEK293 cells as interaction phase was decreased, broadening, and trailing. And with the concentration of glucose increasing, the peak shape of EGCG became higher and narrower than that of no glucose added to running buffer solutions. It is clear that EGCG was releasing gradually from the binding form and when the concentration of glucose increased to 5 mM, the peak heights of EGCG were 28.7% of that without glucose added to running buffer solutions, indicating that EGCG was not completely competed by glucose. This fully explained that EGCG competed with glucose for the same active center of hGlut1, but the binding effect of EGCG was smaller than that of glucose. The experiment phenomena of baicalein and wogonin were similar to that of EGCG, and the electrophoregrams of representative compound EGCG were shown in Figure 3h. On the contrary, the electrophoretic peak shapes of baicalin (Figure 3i) and oroxylin A didn’t change apparently with the increasing concentration of glucose added to running buffer solutions. One situation might be that the two positive compounds had binding effects with hGlut1, but their binding center was different from glucose and hence there existed no competition. The other situation might be that the two positive compounds had binding effects with hGlut1 and they occupied the same binding center with glucose, but the binding effects were so strong that glucose in running buffer solutions could not compete with them anymore. Investigation of the interactions between compounds and other biomaterials by NIBCE. We also used other biomaterials, including A549 cells, A549 tumor tissue, and normal lung tissue as interaction phase to investigate their interactions with ligands by NIBCE (Figure 3j, 3k, 3l, and 3m). When these biomaterials were as interaction phase, the peak shape of negative compound DMSO had no significant difference. But their retention times were prolonged because that the isolated tissues injected into the capillary columns increased the pressure of the system. When normal lung tissue as interaction phase, EGCG exhibited a certain non-specific interaction along with lower peak height and broadened peak shape just like interacting with HEK293 cells. When A549 cells or tumor tissue as interaction phase, the peak shapes of positive compound EGCG were decreased, broadening, and trailing, which were almost consistent with the phenomenon appearing when hGlut1-overexpressed HEK293 cells as interaction phase, indicating that the hGlut1 transporters were overexpressed on A549 cell membrane and tumor tissue. And the binding constants (K) between EGCG and hGlut1-overexpressed 4 HEK293 cells, A549 cells, and tumor tissues were 3.05 × 10 /M, 4 4 2.03 × 10 /M, and 1.59 × 10 /M, respectively. These results robustly demonstrated that the difference of binding constants was resulted from the difference of microenvironment of tumor cells. We chose baicalein and baicalin with larger binding constants among the four active compounds to further study their interactions with A549 cells, A549 tumor tissue, and normal lung tissue by NIBCE. According to their electrophoretograms, it was not difficult to find that they had similar electrophoretic behavior changes with EGCG, indicating that they possessed specific interactions with A549 cells and A549 tumor tissue by targeting

Figure 4. Docked structure and interactions of baicalin binding to hGlut1. (a) The image shows that baicalin binds to the central channel region of hGlut1. (b) The image shows the detailed interactions (formation of 4 hydrogen bonds) between baicalin and amino acid residues of hGlut1.

It was reported that the C domain of hGlut1 provide the primary substrate-binding sites, and D-glucopyranoside of β-NG is hydrogen-bonded to the surrounding polar residues in the C domain, including Gln 282/Gln 283/Asn 288 from TM7, Asn 317 5 from TM8, and Asn 415 from TM11. The results of molecular docking revealed that: (1) the binding of EGCG, baicalein, and wogonin to hGlut1 involved 4, 2, and 2 hydrogen bonds respectively, and Asn 288 from EGCG-Glut1 binding, Asn 288 from bai-

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Analytical Chemistry hGlut1.

calein-Glut1 binding, and Asn 317 from wogonin-Gluti binding were same as the residues from glucose-Glut1 binding; (2) the binding of baicalin to hGlut1 involved 4 hydrogen bonds, and residues Asn 288 and Gln 283 were the same as glucose-Glut1 binding sites and the binding effects of baicalin were so strong that glucose could not compete with it anymore; (3) the binding of oroxylin A to hGlut1 involved 2 hydrogen bonds, which were different from the binding residues of glucose and there existed no competition. Thereout, the results of competitive binding and molecular docking experiments confirmed each other very well. Therefore, we chose EGCG, baicalein, baicalin, and wogonin to further study their anti-tumor effects in cellular and animal levels. Assays of cell proliferation (MTT) and animal anti-tumor. According to the screening results in molecular level, we chose the binding active compounds to perform standard MTT assay to evaluate their influence on the cell proliferation and viability rates, and examined whether there were statistically significant differences between medicated groups and the control group by integrating the results from t-test. The findings showed that only under 100 μM, EGCG had significant difference (n = 3, p < 0.001) compared to the control group. Baicalein in all concentrations tested in our experiment had statistically significant differences, indicating strong inhibitory action on tumor cells. Similarly, compared with the control group, baicalin and wogonin groups in concentrations of 80 μM, 100 μM revealed significant differences. The IC50 values (Table S1) of baicalein (36.08 μM) and baicalin (80.80 μM) were obtained by plotting the inhibitionconcentration curves, providing a reference for animal studies. The IC50 value of baicalein was smaller than that of baicalin, which indicated the inhibitory effect of baicalein on A549 cells was stronger than that of baicalin. What’s more, the screening results mentioned above revealed that the binding constants of baicalein was bigger than that of baicalin, which also indicated the inhibitory effect of baicalein on A549 cells should be stronger than that of baicalin. The results of MTT assay further declared that the method of NIBCE was feasible and reliable. Furthermore, the anti-tumor results of EGCG, baicalein, and baicalin on A549-tumor-bearing mice were shown in Figure 5a, 5b. We summarized the tumor inhibition behavior as follows: The tumor volumes (Figure 5c) and masses (Figure 5d) of medicated groups have significant differences compared with those of the control group, and tumor inhibition rates of EGCG, baicalein, baicalin were 71.51%, 61.73%, and 64.69%, respectively. The antitumor results of baicalein and baicalin in animal level were basically the same as the results in molecular level, which further verified the feasibility and reliability of NIBCE. It is well known that body weight loss of the tested mice is an indicator of systemic toxicity. In this experiment, the body weight (Figure 5e) of the mice in baicalein and baicalin groups showed no significant differences compared with that of 0.9% saline group, indicating that baicalein or baicalin as therapeutic agents did not show toxicity. But the body weight of EGCG group showed significant difference with p < 0.05, suggesting that EGCG may have some side effects at the dose of 80 mg/kg. According to the results of molecular, cellular, and animal levels, a new anti-tumor mechanism of baicalein and baicalin by targeting hGlut1 was verified for the first time, and they were expected to be novel anti-tumor drugs with high anti-cancer efficiency and low systemic toxicity targeting

Figure 5. The anti-tumor effects of EGCG, baicalein, and baicalin in-vivo. (a) Photographs of untreated or EGCG, baicalein, baicalin-treated tumorbearing nude mice with representative tumors. (b) Photographs of tumors in different groups. Photographs of (a) and (b) were taken 9 times after the compounds treatment. (c) Tumor volume changes after treatment with EGCG solution, baicalein solution, and baicalin solution in mice bearing an A549 human lung cancer xenograft. (d) The average tumor masses of different groups after 9 times of compounds treatment. (e) Body weight changes. * p < 0.05, ** p < 0.01, *** p < 0.001. The error bars were added by standard deviation.

CONCLUSIONS Here we present a novel on-line method of screening ligands targeting hGlut1, which we named NIBCE. In this method, capillary columns with porous frits to intercept biomaterials as interaction phase were used to rapidly screen binding active compounds via NIBCE. There are several highlights of this approach. When cells were used as interaction phase in the running capillary column, there existed two modes: “static mode” and “dynamic mode”. In “dynamics mode”, the interaction between compounds and mobile target cells can better simulate that between drugs in blood and target cells, making the calculated binding constant closer to the true value. And for all the biomaterials in NIBCE, the interactions between compounds and immobile target biomaterials resulted in the binding effects in “static mode”, which can better directly simulate the interactions between drugs and the space-occupying tumor. Innovatively, we used A549 cells, normal lung tissue, and A549 tumor tissue as interaction phase for the first time. The isolated tissues retained their intact structure as well as the surface protein activities after immobilization. Compared with the 3D co-culture system, NIBCE avoids cumbersome operation, expensive reagents, and rigorous experimental conditions, but can also obtain the more really physiological data than the 3D co-culture system. Therefore, study on the interaction between human tumor tissue and target

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Analytical Chemistry drugs by NIBCE will be expected to become a new strategy to screen target drugs, provide their optimal kinetic parameters and scientific basis of the clinical tumor-treatment. In summary, we have first characterized the interactions between ligands and receptor of different biomaterials by NIBCE, which was a highly fast, flexible, reproducible, and quantitative method. This new method has several significant advantages compared with other drug screening methods: (i) the biomaterials can be renewed anytime, maintaining their bioactivity, and the capillary columns can be circularly utilized; (ii) the separation, purification, and reconstitution of target receptors from cell membranes is needless, and proteins can maintain their natural conformation; (iii) it is simple and rapid to fabricate the frit; (iv) the biomaterials cannot flow through the detection window, which avoids interfering detections and makes it possible to quickly identify the active components in the mixture by CE-MS; (v) the NIBCE peak profiles are consistent with those fitted by NLC theory and the kinetic parameters (K, ka, kd, and k’) can be obtained using NLC technology; (vi) different biomaterials can be used as interaction phase, broadening the application scope of NIBCE. Ultimately, we hope that this new method will be a powerful tool for high-throughput drug screening of products from combinatorial chemistry and components from traditional Chinese medicine by targeting transporters, receptors, ligands, or proteins of different biomaterials.

ACKNOWLEDGMENT We appreciate professor Ying Wang and professor Dalong Ma (Center for Human Disease Genomics, Peking University), professor Suodi Zhai and associate professor Xianhua Zhang (Peking University Third Hospital), associate professor Yingtao Zhang and professor Heli Liu (The State Key Laboratory of Natural and Biomimetic and School of Pharmaceutical Sciences, Peking University), for their supports.

REFERENCES (1) Alfarouk, K. O.; Verduzco, D.; Rauch, C.; Muddathir, A. K.; Adil, H. H. B.; Elhassan, G. O.; Ibrahim, M. E.; Orozco, J. D. P.; Cardone, R. A.; Reshkin, S. J.; Harguindey, S. Oncoscience 2014, 1, 777-802. (2) Liu, Y.; Cao, Y. Y.; Zhang, W. H.; Bergmeier, S.; Qian, Y. R.; Akbar, H.; Colvin, R.; Ding, J.; Tong, L. Y.; Wu, S. Y.; Hines, J.; Chen, X. Z. Mol. Cancer. Ther, 2012, 11, 1672-1682. (3) Szablewski, K. Bioccchhhimica et Biophysica Acta, 2013, 1835, 164-169. (4) Levine, A. J.; Puzio-Kuter, A. M. Science 2010, 330, 13401344. (5) Deng, D.; Xu, C.; Sun, P. Ch.; Wu, J. P.; Yan, Ch. Y.; Hu, M. X.; Yan, N. Nature 2014, 510, 121-133. (6) Naftalin, R. J.; Afzal, I.; Cunningham, P.; Halai, M.; Ross, C.; Salleh, N.; Milligan, S. R. Br. J. Pharmacol, 2003, 140, 487499. (7) Wood, T. E.; Dalili, S.; Simpson, C. D.; Hurren, R.; Mao, X.; Saiz, F. S.; Gronda, M.; Eberhard, Y.; Minden, M. D.; Bilan, P. J.; Klip, A.; Batey, R. A.; Schimmer, A. D. Mol. Cancer Ther, 2008, 7, 3546-3555. (8) Fang, J.; Bao, Y. Y.; Zhou, S. H.; Fan, J. Mol. Med. Rep., 2015, 12, 6461-6466. (9) Lee, H. Z.; Leung, H. W.; Lai, M. Y.; Wu, C. H. Anticancer Res., 2005, 25, 959–964. (10) Dong, H. M.; Hossain, M. A.; Kang, Y. J.; Jang, J. Y.; Lee, Y. J.; E, I. M.; Yoon, J.H.; Kim, H. S.; Chung, H. Y.; Kim, N. D. Int. J. Oncol., 2013, 43, 1652-1658. (11) Fang, X. Y.; Wu, X. L.; Li, Ch. E.; Zhou, B. W.; Chen, X. Y.; Chen, T. F.; Yang,F. RCS Adv., 2017, 7, 8178-8185. (12) Choi, E. O.; Cho, E. J.; Jeong, J. W.; Cheol, P.; Hong, S. H.; Hwang, H. J.; Moon, S. K.; Son, Ch. G.; Kim, W. J.; Choi, Y. H. Biomol. Ther., 2017, 25, 213-221. (13) Lagerquist, H. C.; Gottschalk, I.; Lundahl, P. J Chromatogr A, 2004, 1031, 113-116. (14) Xie, H.; Wang, Z.; Kong, W.; Wang, L.; Fu, Z. The Analyst 2013, 138, 1107-1113. (15) Yakufu, P.; Qi, H.; Li, M. N.; Ling, X. M.; Chen, W. J.; Wang, Y. Electrophoresis 2013, 34, 531-540. (16) Nagamoto, Y.; Tashiro, K.; Takayama, K. Biomaterials 2012, 33, 4526-4534. (17) Alejandro, C. A.; Anna, M. C.; Jaume, V. Molecules 2017, 22, 136-142.

ASSOCIATED CONTENT Supporting information The Supporting Information is available free of charge on the ACS Publications website at DOI: Extended methods, references of extended methods, and supporting data (Figure S1, S2, S3, S4, S5, S6, S7, and Table S1) (PDF)

AUTHOR INFORMATION Corresponding Author * [email protected] Author Contributions XM.L. conceived this research. RJ.W. designed and performed the experiments, analyzed the data, and wrote the manuscript. K.Z. took part in some of the experiments. XD.Z. designed and performed CICE for screening drug experiments. SF.Z., YM.L., JY.R., and C.L. contributed to collecting samples. XM.L. contributed to revising this manuscript. M.Y. provided some of the compounds needed in the experiment. Funding Sources This work was financially supported by the National Natural Science Foundation of China (Nos. 81373372 and 81673392). Notes The authors declare no competing financial interest.

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Nonimmobilized Biomaterial Capillary Electrophoresis for Screening

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