Research article Received: 5 November 2013,
Revised: 26 March 2014,
Accepted: 9 April 2014
Published online in Wiley Online Library: 15 May 2014
(wileyonlinelibrary.com) DOI 10.1002/bmc.3238
Binding of caffeic acid to human serum albumin by the retention data and frontal analysis Yuxin Ana, Qian Lia, Jiejun Chenb, Xiaokang Gaoa, Hongwei Chena, Chaoni Xiaoa, Liujiao Biana, Jianbin Zhengc, Xinfeng Zhaoa* and Xiaohui Zhenga ABSTRACT: A new mathematical model and frontal analysis were used to characterize the binding behavior of caffeic acid to human serum albumin (HSA) based on high-performance affinity chromatography. The experiments were carried out by injecting various mole amounts of the drug onto an immobilized HSA column. They indicated that caffeic acid has only one type of binding site to HSA on which the association constant was 2.75 × 104/M. The number of the binding site involving the interaction between caffeic acid and HSA was 69 nM. The data obtained by the frontal analysis appeared to present the same results for both the association constant and the number of binding sites. This new model based on the relationship between the mole amounts of injection and capacity factors assists understanding of drug–protein interaction. The proposed model also has the advantages of ligand saving and rapid operation. Copyright © 2014 John Wiley & Sons, Ltd. Keywords: affinity chromatography; drug–protein interaction; human serum albumin; caffeic acid
Introduction
Biomed. Chromatogr. 2014; 28: 1881–1886
* Correspondence to: X. Zhao, Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi’an 710069, China. Email: [email protected] a
Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi’an 710069, China
b
China National Center for Biotechnology Development, Beijing 100036, China
c
Institute of Analytical Science, Northwest University, Xi’an 710069, China Abbreviations used: DSC, disuccinimidyl carbonate; HPAC, highperformance affinity chromatographyl; HSA, human serum albumin; NHS, N-hydroxysuccinimide; PBS, potassium phosphate buffer.
Copyright © 2014 John Wiley & Sons, Ltd.
1881
The binding of a drug to a protein in blood plays an important role in controlling the function (Tsuruda et al., 2010), therapeutic activity (Rajdev et al., 2011) and toxicity (Bal et al., 2013) of the drug in vivo. Recent work (Zinn et al., 2012; Tong et al., 2011; Wang et al., 2011) on drug–protein interaction has attracted increasing attention in several fields including biochemistry, pharmaceutical analysis and pharmacology. Among the widely studied bio-macromolecules, human serum albumin (HSA) is undoubted an outstanding protein for the pursuit of drug– protein interaction for several reasons: (1) it is the most abundant protein in human plasma and is particularly important in the binding and transport of many low-molecular-weight compounds in blood (Gabriella et al., 2012; Yue et al., 2011); (2) the protein is easy to prepare and has good stability after purification (Qian et al., 2008); and (3) the structure of the protein has been well identified (Yang et al., 2013). As a model protein, HSA has a molar mass of around 66,000 g/mol and consists of a single chain of 585 amino acids held together by 17 disulfide bonds (Belgacem et al., 2007). Many drugs with low molecular weight show reversible binding to HSA (Ryan et al., 2011). These drugs include long-chain fatty acids, steroids, warfarin, tryptophan, ketoprofen, propranolol and diazepam. Numerous assays, such as ultrafiltration, equilibrium dialysis, UV–vis spectroscopy, spectrofluorometry, crystallography, capillary electrophoresis and affinity capillary electrophoresis, have been reported for examining the binding of a drug to HSA (Enyedy et al., 2011). Another technique, highperformance affinity chromatography (HPAC) is also largely used for such work owing to its better speed, precision and good correlation vs reference methods (Matsud et al., 2012). This method is typically performed by frontal analysis and competitive displacement technologies. The two HPAC assays
require a constant flush of the immobilized protein with increasing known concentrations of a drug, which causes issues of drug and time consumption. Ongoing work has been focusing on the creation of new mathematical models and the construction of microcolumn to address these issues. Kim and Wainer (2008) combined frontal analysis and competitive displacement on an HPAC column containing immobilized HSA to examine the association constants of various compounds. They have obtained a linear relationship between retention factors of reference compounds collected by competitive displacement and association constants by frontal analysis. The linear relationship is further used for rapid determination of association constants of various drugs and has resulted in a high correlation with literature data obtained by equilibrium dialysis or ultra-filtration. Other works have confirmed that ultrafast affinity chromatography using a microcolumn packed with immobilized HSA has potential for rapid analysis of drug–protein binding (Mallik et al., 2010; Yoo et al., 2010). Although these studies have
Y. An et al. reinforced frontal analysis and competitive displacement for effect analysis of drug–protein interaction, further work is required to substantially decrease the run time and the amounts of ligands when frontal analysis and competitive displacement are used. Caffeic acid (Fig. 1) is abundantly distributed in plant-derived products such as fruits, vegetables tea, olive oil and wine (Zhang et al., 2007; Chung et al., 2006). It possesses a wide variety of biological functions including anti-oxidant (Damasceno et al., 2013) and anti-inflammatory (Tsai et al., 2011). This work is designed to explore the binding of caffeic acid to HSA by an improved HPAC method based on the relationship between the mole amounts of injection and the retention factors.
phase and the mobile phase, respectively; and Vm is the volume of the mobile phase in the column. We can obtain equation (7) by fusing equation (5) with equation (6): k′ ¼
K A Vnmt
(7)
1 þ K A ½L
When A is injected as a solute, the mole amount of A distributed between mobile phase and stationary phase is generally defined as: ½AV m þ ½ALfSg ¼ nI
V m þ fSg
nI ½AL ¼ ½ A A
(8)
where nI is the mole amount of the injected solute. Incorporating equation (5) into equation (8), we have:
Theory In general, if a solute (A) binds to a single type of ligand (L) immobilized on a solid matrix, the mass balance equation describing the binding of A to L is: A þ L ¼ AL
(1)
The association constant during the binding can be presented by equation (2): ½AL KA ¼ ½A½L
(3)
where [A] and [AL] are the concentrations of A and the ligand– protein complex (AL) at the equilibrium; {S} stands for the apparent surface area of the stationary phase; and nt is the total mole amount of binding sites on the immobilized protein. Rearranging equation (3), we have: ½A ¼
nt ½AL fSg
(4)
Combining equation (2) with equation (4), one can foresee: K A fnStg ½AL ¼ ½L 1 þ K A ½L
(5)
In chromatographic system, the capacity factor of a solute can be illustrated as: k′ ¼
ns ½AL fSg ¼ ½L V m nm
(6)
where k’ is the capacity factor of an injection solution; ns and nm represent the mole amounts of the solute in the stationary
(9)
When capacity factor of the solute is greater than zero, equation (9) can be translated to a new form through replacing [A] by the corresponding parameter in equation (7) and a desired arrangement: k′nI 1 ¼ nt k′V m KA 1 þ k′
(2)
Supposing an even distribution of the binding sites on stationary phase, a rapid absorption and desorption, and a neglect of longitudinal diffusion, we characterize the total binding sites on the protein using equation (3) when the number of sites remains constant: ½AfSg þ ½ALfSg ¼ nt
K A V m ½A2 þ ½K A ðnt nI Þ þ V m ½A nI ¼ 0
(10)
In equation (10), k’ is easy to determine by k’ = (tR t0)/t0, where tR and t0 denote the retention time of the solute and the void time of the chromatographic system. Plotting the curve of (k’nI)/(1 + k’) vs k’, one will observe a linear relationship between the two parameters. The association constant and the binding sites during the binding of a ligand to the immobilized protein can be calculated using the intercept and slope of the curve. When two types of binding site occur, deviation of a linear relationship will be viewed and equation (10) can be used to calculate the binding parameters by adding a second term to k’ expression.
Experimental Instruments and reagents The chromatographic system used in this work consisted of a Series of Agilent 1100 HPLC system including a binary pump, a column oven, a diode array detector (Waldbronn, Germany) and a Chemistation 5.2 software installation for data acquisition and processing. The ZZXT-A packing machine was supplied by Dalian Yilite Analytic Instruments Company Limited (Dalian, China). Standard of caffeic acid was purchased from the Institute of Drug and Biological Product Control of China (Beijing, China). L-tryptophan (>98% pure), S-warfarin (>99% pure), tamoxifen (>98% pure) and digitoxin (97% pure) were acquired from Sigma-Aldrich (St Louis, MO, USA). Fatty acid and globulin-free HSA was obtained as lyophilized powder from Sigma-Aldrich (St Louis, MO, USA). Macro-pore silica gel (SPS 300-7; pore size 300 Å, particle size 7.0 μm) was supplied by Fuji Silysia Chemical Company (Tokyo, Japan). All other reagents were of analytic grade unless stated specifically.
Immobilization of HSA
1882
Figure 1. Chemical structure of (E)-3-(3,4-dihydroxyphenyl)acrylic acid, also named caffeic acid.
wileyonlinelibrary.com/journal/bmc
A widely reported N-hydroxysuccinimide (NHS) method (Wu et al., 2013) was employed to covalently attach HSA on the surface of macro-porous silica gel (Fig. 2). Briefly, 2.0 g of the silica gel was pretreated with 16% (v/v) hydrochloric acid through refluxing at 110 °C overnight. Subsequently, the treated gel was rinsed six times with water and filtered using a 0.22 μm
Copyright © 2014 John Wiley & Sons, Ltd.
Biomed. Chromatogr. 2014; 28: 1881–1886
Binding of caffeic acid to human serum albumin
Figure 2. Preparation of N-hydroxysuccinimide (NHS)-activated silica for protein immobilization. Potassium phosphate buffer: 50 mM potassium phosphate buffer (pH 7.2).
nylon filter. The resulting gel was dried overnight under vacuum at 120 °C. The dried gel was further transferred to a 150 mL round-bottom flask and merged with 40 mg disuccinimidyl carbonate (DSC). The mixture was suspended in 30 mL dry acetone and gently agitated with a stirring bar. A solution containing 2.0 mL triethylamine and 20 mL dry pyridine was placed dropwise into the suspension under a nitrogen stream during the course of 30 min. Followed by an additional 60 min agitation, the mixture was washed with acetone to remove the remaining DSC. The final gel was filtered and then dried under vacuum overnight at room temperature. Potassium phosphate buffer (PBS, 50 mM, pH 7.2) was used as slurry solution and propulsive agent to pack stainless steel chromatographic 7 columns (50 × 4.6 mm.) under a pressure of 4.0 × 10 Pa. The immobilization of HSA on the NHS-coated silica gel was performed by cyclically flushing the column for 2.0 h with phosphate buffer (50 mM, pH 7.2) containing 20 mg/mL HSA.
Nonspecific adsorption of HSA column Nonspecific adsorption of the column containing immobilized HSA was examined by comparing the retention behaviors of L-tryptophan, S-warfarin, tamoxifen and digitoxin on immobilized HSA with that on control columns, viz. columns containing bare silica and NHS-activated gel. The mobile phase used for this aim was phosphate buffer (50 mM, pH 7.2). The detection wavelengths were 280 nm for L-tryptophan, 282 nm for S-warfarin, 240 nm for tamoxifen and 220 nm for digitoxin. Each drug was measured three times to achieve a mean capacity factor with a flow rate of 0.2 mL/min and an injection volume of 5.0 μL (1.0 mg/mL).
Results and discussion Immobilization of HSA The activated sites on the surface of NHS-coated gel were determined by measuring the NHS groups released into solution after hydrolysis (Miron and Wilchek, 1982). It presented a value of 12.6 (±0.4) μM activated groups per gram gel. Bicinchoninic acid assay was used to determine the amounts of HSA immobilized on the surface of the stationary phase by the analysis of total protein concentration pro- and post-immobilization. The final content of HSA on the stationary phase was calculated to be 10.3 mg/g silica. This value well corresponded to the coverage of a 0.11 monolayer for HSA on the silica’s surface (480 m2/g) based on the size of 140 × 40 Å for HSA (Lu et al., 2008). Kim et al. (2006) investigated the immobilization of HSA on the surface of the same kind of silica gel using an off-line NHS method and obtained a value of 125 nM HSA per gram silica during the immobilization. Compared with their work, the current on-line assay was believed to be more efficient owing to a higher amount of immobilized HSA on the gel. Nonspecific adsorption of HSA column
Interaction between caffeic acid and HSA The binding of caffeic acid to HSA was studied by the mathematical model we proposed above. In this case, the mole amounts of injected caffeic acid were 20.0, 15.0, 10.0, 5.0, 2.5, 1.25, 0.63, 0.32 and 0.16 nM. The mobile phase was phosphate buffer (50 mM, pH 7.2) with a flow rate of 0.2 mL/min. The detection wavelength was set at 323 nm. All the experiments were performed at 37 °C to imitate the temperature for a drug binding to HSA in vivo.
Validation of the proposed mathematical model
The next item studied in this work was to assess the nonspecific adsorption of immobilized HSA synthesized by the on-line NHSattaching method. In this case, the retention properties of caffeic acid on bare silica, NHS-coated gel and immobilized HSA columns were measured in triplicate. Caffeic acid gave approximate capacity factors on bare silica and NHS-coated gel (Table 1). This result indicated that the silica gel itself was the main source of weak nonspecific interaction during the binding of caffeic acid to immobilized HSA. This result was expected because NHS can only activate a small amount of silicanols on the silica and the rest of the surface was available as the adsorption sites for a drug. The reason for the similar capacity factors of caffeic acid on the two control columns may be partly behind the direct reaction between bare silica and DSC. During the reaction, DSC directly reacted with silianols on the surface of silica to form an active NHS ester, whereby we believe no spacers or any other active groups were present at the silica surface. The remaining active sites were removed by hydrolysis (Kim et al., 2006) after these NHS-activated sites were further used for HSA immobilization. It was also notable that caffeic acid illustrated a retention time of 4.0 min on the column containing immobilized HSA.
Copyright © 2014 John Wiley & Sons, Ltd.
wileyonlinelibrary.com/journal/bmc
1883
The next set of experiment was designed to confirm the validation of the mathematical model we proposed using frontal analysis, which is widely known to be a powerful and classic tool for revealing drug–protein interaction in affinity chromatography. Caffeic acid was dissolved in ethanol to prepare a stock solution of 10 mM, and further diluted with phosphate buffered solution (50 mM, pH 7.2) to obtain a series of chromatographic mobile phases containing 1.0, 2.0, 4.0, 6.0, 8.0 and 10.0 μM of the drug. All the mobile phases were totally degassed by ultrasonic wave in prior to be used. Frontal analysis was performed using the chromatographic mobile phase at a flow rate of 0.2 mL/min. A correction for the system void time was made by performing similar experiments using sodium nitrite (1.0 μM) as a nonretained solute. The column was
Biomed. Chromatogr. 2014; 28: 1881–1886
regenerated between each study by passing phosphate buffered solution (50 mM, pH 7.2) through the column. All experiments were performed in triplicate under each set of test conditions.
Y. An et al. Table 1. Nonspecific binding of caffeic acid and probe drugs to various silica-based stationary phases
Caffeic acid L-Tryptophan S-Warfarin Tamoxifen Digitoxin
Capacity factors Bare silica control column
NHS control column
0.23 ± 0.03 0.08 ± 0.01 0.28 ± 0.03 0.16 ± 0.02 0.43 ± 0.05
0.24 ± 0.02 0.07 ± 0.03 0.27 ± 0.05 0.18 ± 0.01 0.41 ± 0.06
HSA column 4.00 ± 0.10 3.83 ± 0.18 4.41 ± 0.16 2.16 ± 0.12 2.50 ± 0.07
All of these capacity factors were measured at 37 °C. The void time of the system was determined to be 1.2 min using sodium nitrite as a nonretention solute. NHS, N-hydroxysuccinimide; HSA, human serum albumin.
Taking all the results into account, nonspecific adsorption was believed to have little effect on the binding of caffeic acid to HSA for the reason that it was easily subtracted from the capacity factors of the drug on immobilized HSA. Nonspecific binding of the HSA column was tested by the retention behaviors of L-tryptophan, S-warfarin, tamoxifen and digitoxin. The four drugs are well known to have clear binding to HSA and are commonly used as site-selective ligands to probe drug–HSA interaction. For all four drugs, no substantial differences in the capacity factors were found between the values determined from the bare silica column and the NHS-coated gel column. This result is in good agreement with the data for the binding of caffeic acid to HSA immobilized by the same method. Therefore, we concluded that the nonspecific adsorption of the immobilized HSA can be mainly attributed to the silica gel itself. Since the nonspecific adsorption arose from the bare silica, the second comparison was only made between the capacity factors of the four drugs on the bare silica column and HSA column. Compared with the retention on bare silica, all the drugs presented good retentions on HSA column. Nonspecific bindings of L-tryptophan, S-warfarin, tamoxifen and digitoxin contributed 2.1, 6.3, 7.4 and 17.2% to their retention on immobilized HSA. Based on these results, the immobilized HSA using NHS-activated method was supposed to be capable of probing the drug–HSA interaction.
Absorbance 323 nm
Drugs
50 40 30 20 10 0 0
2
4
6
8
10
12
14
16
18
Time (min) Figure 3. Representative chromatograms of caffeic acid on the immobilized human serum albumin (HSA) column when varied mole amounts of the drug were injected. From left to right, the amounts of caffeic acid were 30.0, 20.0, 10.0, 15.0, 10.0, 5.0 and 2.5 nM.
Table 2. Capacity factors of caffeic acid on conlumn containing immobilized HSA when declining mole amounts of caffeic acid are injected as solutes Mole amounts of injection (nM) 30.0 25.0 20.0 15.0 10.0 7.50 5.00 2.50 1.25
Capacity factors
3.60 3.84 4.22 4.45 4.78 4.90 5.11 5.27 5.37
3.61 3.87 4.21 4.46 4.75 4.88 5.12 5.30 5.34
3.62 3.86 4.21 4.47 4.76 4.89 5.10 5.28 5.35
Mean capacity factors 3.61 3.86 4.21 4.46 4.76 4.89 5.11 5.28 5.35
k′nI 1þk′
23.48 19.84 16.17 12.25 8.27 6.23 4.18 2.10 1.05
Interaction between caffeic acid and immobilized HSA
1884
The representative chromatograms of caffeic acid on the column containing immobilized HSA are pictured in Fig. 3, when varied mole amounts of the drug were used as the injection solutes. They show that the retention times of caffeic acid negatively corresponded to the injection volumes in the range 0.16 20.0 nM. The capacity factors of the drug decreased with increasing injection amounts of the drug used. These results accord well with the prediction of our model, providing a proof of applying the current model in realizing drug–protein interaction. Capacity factors of caffeic acid on HSA column are listed in Table 2 when increasing injection amounts of the drug were performed. It was found that the capacity factors grew when shrinking amounts of the drugs were injected. Equation (10) was accordingly used to plot the curve of k′nI/(1 + k′) against k′. A linear
wileyonlinelibrary.com/journal/bmc
Figure 4. Plot of (k’nI)/(1 + k’) vs k’ when the injection mole amounts of caffeic acid were 20.0, 15.0, 10.0, 5.0, 2.5, 1.25, 0.63, 0.32 and 0.16 nM. The regression equation is y = 12.84x + 69.64.
Copyright © 2014 John Wiley & Sons, Ltd.
Biomed. Chromatogr. 2014; 28: 1881–1886
Binding of caffeic acid to human serum albumin
Figure 5. Frontal analysis of caffeic acid on the immobilized HSA column at pH 7.2 and 37 °C, where the concentrations of applied caffeic acid (from right to left) are 1.0, 2.0, 4.0, 6.0, 8.0 and 10.0 μM.
relationship was obtained, shown in Fig. 4, with a correlation coefficient of 0.9979 and a regression equation of y = 12.84x + 69.64. Using the slope and intercept of the curve, the association constant for the binding of caffeic acid to HSA was calculated to be (2.75 ± 0.14) × 104/M and the binding site was 69 nM. Another important result was that no deviation from the linear curve between k′nI/(1 + k′) and k′ occurred in the whole regression range. This result indicated that only one type of binding site was available on the column for caffeic acid targeting HSA. This deduction was reasonable because it agreed well with the report by Liu et al. (2010) in which the authors discovered that only site I on bovine serum albumin participates the binding of caffeic acid to the protein. Moreover, another report found that caffeic acid had increasing association constants during the binding to HSA when decreasing temperatures were tested (Zhang et al., 2008). For instance, the association constants at 303 and 310 K were determined to be 3.06 × 104 and 2.82 × 104/M, respectively. These data were in good agreement with the value of (2.75 ± 0.14) × 104/M determined in this work at the same temperature. Although different approaches were used in the references and this work, similar conclusions were obtained for the binding of caffeic acid to HSA. This discovery confirmed the feasibility of our model for the pursuit of drug–protein interaction. Validation of the current method for probing caffeic acid-HSA interactions To validate the application of our model in realizing drug– protein interaction, we further examined the binding of caffeic acid to immobilized HSA by frontal analysis. In this case, a widely known equation (Zhao et al., 2013) was utilized to calculate the association constant and the binding site of caffeic acid to immobilized HSA: 1 1 1 ¼ þ mLapp ðK A mL ½AÞ mL
(11)
Biomed. Chromatogr. 2014; 28: 1881–1886
Conclusion In the present work, we studied the binding of caffeic acid to HSA by HPAC technologies. A new mathematical model and frontal analysis were used to calculate the association constant and the number of binding sites of caffeic acid–HSA interaction. The two methods suggested that caffeic acid only has one type of binding site on HSA. Moreover, the association constant and the number of binding sites calculated from the two assays were in good agreement. In addition, the data obtain by the new model fitted previous observations on interaction between caffeic acid and HSA by spectrometric methods. All of these results indicated that the relationship between retention factors and the amounts of injection has potential for the pursuit of drug–protein interaction.
Acknowledgments We cordially thank the National Natural Sciences Foundation of China (nos J1210063; 21005060), the Program for Changjiang Scholars and Innovative Research Team in University (no. IRT1174), the project for Innovative Research Team of Research and Technology of Shaanxi Province (no. 2013KCT-24) and the key project from Ministry of Science and Technology of the China (no. 2013YQ17052509) for financial support.
References Bal W, Sokołowska M, Kurowska E and Faller P. Binding of transition metal ions to albumin: sites, affinities and rates. Biochimica et Biophysica Acta 2013; 1830: 5444–5455. Belgacem O, Stübiger G, Allmaier G, Buchacher A and Pock K. Isolation of esterified fatty acids bound to serum albumin purified from human plasma and characterized by MALDI mass spectrometry. Biologicals 2007; 35: 43–49. Chung MJ, Walker PA and Hogstrand C. Dietary phenolic antioxidants, caffeic acid and Trolox, protect rainbow trout gill cells from nitric oxide-induced apoptosis. Aquatic Toxicology 2006; 80: 321–328.
Copyright © 2014 John Wiley & Sons, Ltd.
wileyonlinelibrary.com/journal/bmc
1885
where KA is the association constant for binding of A to L, and [A] is the concentration of the solute applied to the column; mL is related to the true number of binding sites on the column; and mLapp denotes the apparent moles of solute required to reach the platform of the breakthrough curve. Typical breakthrough
curves obtained from the application of increasing concentration of caffeic acid on immobilized HSA column were shown in Fig. 5. As caffeic acid increased, it resulted in a saturation of HSA and produced a breakthrough curve which was used to calculate the apparent moles of caffeic acid at the mean point. The plot for 1/mLapp against 1/[caffeic acid] presented a linear relationship with a regression equation y = 0.5743x + 0.01524 and a correlation coefficient of 0.9977 (n = 6). This result suggested that only a single type of binding site was present for caffeic acid on the immobilized HSA. The association constant determined from the regression equation was 2.66 × 104/M, which agreed well with the value obtained by spectrometric assays (Liu et al., 2010). Compared with the data determined by spectrometric assays (Liu et al., 2010), the association constant calculated from frontal analysis was in good agreement with the value determined by our new model. This was expected since frontal analysis and our mathematical model were all carried out using the HPAC system. More importantly, frontal analysis is often accomplished by constantly flushing the column with a set of drug solutions at varied concentrations. This special requirement causes issues of long operation time and high drug consumption. Focusing on this point, our model is worthy of widespread application owing to the capacity to probe drug–protein interaction with the advantages of drugsaving and rapid performance.
Y. An et al. Damasceno SS, Santos NA, Santos IMG, Souza AL, Souza AG and Queiroz N. Caffeic and ferulic acids: an investigation of the effect of antioxidants on the stability of soybean biodiesel during storage. Fuel 2013; 107: 641–646. Enyedy ÉA, Horváth L, Hetényi A, Tuccinardi T, Hartinger CG, Keppler BK and Kiss T. Interactions of the carrier ligands of antidiabetic metal complexes with human serum albumin: a combined spectroscopic and separation approach with molecular modeling studies. Bioorganic and Medicinal Chemistry 2011; 19: 4202–4210. Gabriella F, Alessandra M, Viviana T, Maria M, Mauro F and Paolo A. Human serum albumin: from bench to bedside. Molecular Aspects of Medicine 2012; 33: 209–290. Kim HS and Wainer IW. Rapid analysis of the interactions between drugs and human serum albumin (HSA) using high-performance affinity chromatography (HPAC). Journal of Chromatography B 2008; 870: 22–26 Kim HS, Mallik R and Hage DS. Chromatographic analysis of carbamazepine binding to human serum albumin: II. Comparison of the Schiff base and N-hydroxysuccinimide immobilization methods. Journal of Chromatography B 2006; 837: 138–146. Liu QW, Xu H, Li GH, Zhang T and Qiao QA. Insight into interaction of caffeic acid with bovine serum albumin. Food Science 2010; 31: 24–28. Lu QH, Ba CD and Chen DY. Investigating noncovalent interactions of rutin – serum albumin by capillary electrophoresis – frontal analysis. Journal of Pharmaceutical and Biomedical Analysis 2008; 47: 888–891. Mallik R, Yoo MJ, Briscoe CJ and Hage DS. Analysis of drug–protein binding by ultrafast affinity chromatography using immobilized human serum albumin. Journal of Chromatography A 2010; 1217: 2796–2803. Matsud R, Anguizol J, Joseph KS and Hage DS. Analysis of drug interactions with modified proteins by high-performance affinity chromatography: binding of glibenclamide to normal and glycated human serum albumin. Journal of Chromatography A 2012; 1265: 114–122. Miron T and Wilchek M. A spectrophotometric assay for soluble and immobilized N-hydroxysuccinimide esters. Analytical Biochemistry 1982; 126: 433–435. Qian J, Tang QL, Cronin B, Markovich R and Rustum A. Development of a high performance size exclusion chromatography method to determine the stability of human serum albumin in a lyophilized formulation of Interferon alfa-2b. Journal of Chromatography A 2008; 1194: 48–56. Rajdev P, Mondol T, Makhal A and Pal SK. Simultaneous binding of antituberculosis and anti-thrombosis drugs to a human transporter protein: a FRET study. Journal of Photochemistry and Photobiology B: Biology 2011; 103: 153–158.
Ryan AJ, Ghuman J, Zunszain PA, Chung CW and Curry S. Structural basis of binding of fluorescent, site-specific dansylated amino acids to human serum albumin. Journal of Structural Biology 2011; 174: 84–91. Tong Z, Schiel JE, Papastavros E, Ohnmacht CM, Smith QR and Hage DS. Kinetic studies of drug–protein interactions by using peak profiling and high-performance affinity chromatography: Examination of multi-site interactions of drugs with human serum albumin columns. Journal of Chromatography A 2011; 1218: 2065–2071. Tsai SJ, Chao CY and Yin MC. Preventive and therapeutic effects of caffeic acid against inflammatory injury in striatum of MPTP-treated mice. European Journal of Pharmacology 2011; 670: 441–447. Tsuruda PR, Yung J, Martin WJ, Chang R, Mai N and Smith JAM. Influence of ligand binding kinetics on functional inhibition of human recombinant serotonin and norepinephrine transporters. Journal of Pharmacological and Toxicological Methods 2010; 61: 192–204. Wang YC, Zhang CH, Deng NY and Wang Y. Kernel-based data fusion improves the drug–protein interaction prediction. Computational Biology and Chemistry 2011; 35: 353–362. Wu H, Zhang CH, Liang YP, Shi JF, Wang XL and Jiang ZY. Catechol modification and covalent immobilization of catalase on titania submicrospheres. Journal of Molecular Catalysis B: Enzymatic 2013; 92: 44–50. Yang F, Ma ZY, Zhang Y, Li GQ, Li M, Qin JK, Lockridge O and Liang H. Human serum albumin-based design of a diflunisal prodrug. European Journal of Pharmaceutics and Biopharmaceutics 2013; 84: 549–554. Yoo MJ, Schiel JE and Hage DS. Evaluation of affinity microcolumns containing human serum albumin for rapid analysis of drug–protein binding. Journal of Chromatography B 2010; 878: 1707–1713. Yue YY, Liu JM, Fan J and Yao XJ. Binding studies of phloridzin with human serum albumin and its effect on the conformation of protein. Journal of Pharmaceutical and Biomedical Analysis 2011; 56: 336–342. Zhang L, Zhang WP, Chen KD, Qian XD, Fang SH and Wei EQ. Caffeic acid attenuates neuronal damage, astrogliosis and glial scar formation in mouse brain with cryoinjury. Life Sciences 2007; 80: 530–537. Zhang YH, Yue YY, Li JZ and Chen XG. Studies on the interaction of caffeic acid with human serum albumin in membrane mimetic environments. Journal of Photochemistry and Photobiology B: Biology 2008; 90: 141–151. Zhao XF, Huang JJ, Li Q, Wei LS, Zheng JB, Zheng XH, Li ZJ and Zhang YY. Revealing binding interaction between seven drugs and immobilized β2-adrenoceptor by high-performance affinity chromatography using frontal analysis. Journal of Molecular Recognition 2013; 26: 252–257. Zinn N, Hopf C, Drewes G and Bantscheff M. Mass spectrometry approaches to monitor protein–drug interactions. Methods 2012; 57: 430–440.
1886 wileyonlinelibrary.com/journal/bmc
Copyright © 2014 John Wiley & Sons, Ltd.
Biomed. Chromatogr. 2014; 28: 1881–1886
Revised: 26 March 2014,
Accepted: 9 April 2014
Published online in Wiley Online Library: 15 May 2014
(wileyonlinelibrary.com) DOI 10.1002/bmc.3238
Binding of caffeic acid to human serum albumin by the retention data and frontal analysis Yuxin Ana, Qian Lia, Jiejun Chenb, Xiaokang Gaoa, Hongwei Chena, Chaoni Xiaoa, Liujiao Biana, Jianbin Zhengc, Xinfeng Zhaoa* and Xiaohui Zhenga ABSTRACT: A new mathematical model and frontal analysis were used to characterize the binding behavior of caffeic acid to human serum albumin (HSA) based on high-performance affinity chromatography. The experiments were carried out by injecting various mole amounts of the drug onto an immobilized HSA column. They indicated that caffeic acid has only one type of binding site to HSA on which the association constant was 2.75 × 104/M. The number of the binding site involving the interaction between caffeic acid and HSA was 69 nM. The data obtained by the frontal analysis appeared to present the same results for both the association constant and the number of binding sites. This new model based on the relationship between the mole amounts of injection and capacity factors assists understanding of drug–protein interaction. The proposed model also has the advantages of ligand saving and rapid operation. Copyright © 2014 John Wiley & Sons, Ltd. Keywords: affinity chromatography; drug–protein interaction; human serum albumin; caffeic acid
Introduction
Biomed. Chromatogr. 2014; 28: 1881–1886
* Correspondence to: X. Zhao, Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi’an 710069, China. Email: [email protected] a
Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi’an 710069, China
b
China National Center for Biotechnology Development, Beijing 100036, China
c
Institute of Analytical Science, Northwest University, Xi’an 710069, China Abbreviations used: DSC, disuccinimidyl carbonate; HPAC, highperformance affinity chromatographyl; HSA, human serum albumin; NHS, N-hydroxysuccinimide; PBS, potassium phosphate buffer.
Copyright © 2014 John Wiley & Sons, Ltd.
1881
The binding of a drug to a protein in blood plays an important role in controlling the function (Tsuruda et al., 2010), therapeutic activity (Rajdev et al., 2011) and toxicity (Bal et al., 2013) of the drug in vivo. Recent work (Zinn et al., 2012; Tong et al., 2011; Wang et al., 2011) on drug–protein interaction has attracted increasing attention in several fields including biochemistry, pharmaceutical analysis and pharmacology. Among the widely studied bio-macromolecules, human serum albumin (HSA) is undoubted an outstanding protein for the pursuit of drug– protein interaction for several reasons: (1) it is the most abundant protein in human plasma and is particularly important in the binding and transport of many low-molecular-weight compounds in blood (Gabriella et al., 2012; Yue et al., 2011); (2) the protein is easy to prepare and has good stability after purification (Qian et al., 2008); and (3) the structure of the protein has been well identified (Yang et al., 2013). As a model protein, HSA has a molar mass of around 66,000 g/mol and consists of a single chain of 585 amino acids held together by 17 disulfide bonds (Belgacem et al., 2007). Many drugs with low molecular weight show reversible binding to HSA (Ryan et al., 2011). These drugs include long-chain fatty acids, steroids, warfarin, tryptophan, ketoprofen, propranolol and diazepam. Numerous assays, such as ultrafiltration, equilibrium dialysis, UV–vis spectroscopy, spectrofluorometry, crystallography, capillary electrophoresis and affinity capillary electrophoresis, have been reported for examining the binding of a drug to HSA (Enyedy et al., 2011). Another technique, highperformance affinity chromatography (HPAC) is also largely used for such work owing to its better speed, precision and good correlation vs reference methods (Matsud et al., 2012). This method is typically performed by frontal analysis and competitive displacement technologies. The two HPAC assays
require a constant flush of the immobilized protein with increasing known concentrations of a drug, which causes issues of drug and time consumption. Ongoing work has been focusing on the creation of new mathematical models and the construction of microcolumn to address these issues. Kim and Wainer (2008) combined frontal analysis and competitive displacement on an HPAC column containing immobilized HSA to examine the association constants of various compounds. They have obtained a linear relationship between retention factors of reference compounds collected by competitive displacement and association constants by frontal analysis. The linear relationship is further used for rapid determination of association constants of various drugs and has resulted in a high correlation with literature data obtained by equilibrium dialysis or ultra-filtration. Other works have confirmed that ultrafast affinity chromatography using a microcolumn packed with immobilized HSA has potential for rapid analysis of drug–protein binding (Mallik et al., 2010; Yoo et al., 2010). Although these studies have
Y. An et al. reinforced frontal analysis and competitive displacement for effect analysis of drug–protein interaction, further work is required to substantially decrease the run time and the amounts of ligands when frontal analysis and competitive displacement are used. Caffeic acid (Fig. 1) is abundantly distributed in plant-derived products such as fruits, vegetables tea, olive oil and wine (Zhang et al., 2007; Chung et al., 2006). It possesses a wide variety of biological functions including anti-oxidant (Damasceno et al., 2013) and anti-inflammatory (Tsai et al., 2011). This work is designed to explore the binding of caffeic acid to HSA by an improved HPAC method based on the relationship between the mole amounts of injection and the retention factors.
phase and the mobile phase, respectively; and Vm is the volume of the mobile phase in the column. We can obtain equation (7) by fusing equation (5) with equation (6): k′ ¼
K A Vnmt
(7)
1 þ K A ½L
When A is injected as a solute, the mole amount of A distributed between mobile phase and stationary phase is generally defined as: ½AV m þ ½ALfSg ¼ nI
V m þ fSg
nI ½AL ¼ ½ A A
(8)
where nI is the mole amount of the injected solute. Incorporating equation (5) into equation (8), we have:
Theory In general, if a solute (A) binds to a single type of ligand (L) immobilized on a solid matrix, the mass balance equation describing the binding of A to L is: A þ L ¼ AL
(1)
The association constant during the binding can be presented by equation (2): ½AL KA ¼ ½A½L
(3)
where [A] and [AL] are the concentrations of A and the ligand– protein complex (AL) at the equilibrium; {S} stands for the apparent surface area of the stationary phase; and nt is the total mole amount of binding sites on the immobilized protein. Rearranging equation (3), we have: ½A ¼
nt ½AL fSg
(4)
Combining equation (2) with equation (4), one can foresee: K A fnStg ½AL ¼ ½L 1 þ K A ½L
(5)
In chromatographic system, the capacity factor of a solute can be illustrated as: k′ ¼
ns ½AL fSg ¼ ½L V m nm
(6)
where k’ is the capacity factor of an injection solution; ns and nm represent the mole amounts of the solute in the stationary
(9)
When capacity factor of the solute is greater than zero, equation (9) can be translated to a new form through replacing [A] by the corresponding parameter in equation (7) and a desired arrangement: k′nI 1 ¼ nt k′V m KA 1 þ k′
(2)
Supposing an even distribution of the binding sites on stationary phase, a rapid absorption and desorption, and a neglect of longitudinal diffusion, we characterize the total binding sites on the protein using equation (3) when the number of sites remains constant: ½AfSg þ ½ALfSg ¼ nt
K A V m ½A2 þ ½K A ðnt nI Þ þ V m ½A nI ¼ 0
(10)
In equation (10), k’ is easy to determine by k’ = (tR t0)/t0, where tR and t0 denote the retention time of the solute and the void time of the chromatographic system. Plotting the curve of (k’nI)/(1 + k’) vs k’, one will observe a linear relationship between the two parameters. The association constant and the binding sites during the binding of a ligand to the immobilized protein can be calculated using the intercept and slope of the curve. When two types of binding site occur, deviation of a linear relationship will be viewed and equation (10) can be used to calculate the binding parameters by adding a second term to k’ expression.
Experimental Instruments and reagents The chromatographic system used in this work consisted of a Series of Agilent 1100 HPLC system including a binary pump, a column oven, a diode array detector (Waldbronn, Germany) and a Chemistation 5.2 software installation for data acquisition and processing. The ZZXT-A packing machine was supplied by Dalian Yilite Analytic Instruments Company Limited (Dalian, China). Standard of caffeic acid was purchased from the Institute of Drug and Biological Product Control of China (Beijing, China). L-tryptophan (>98% pure), S-warfarin (>99% pure), tamoxifen (>98% pure) and digitoxin (97% pure) were acquired from Sigma-Aldrich (St Louis, MO, USA). Fatty acid and globulin-free HSA was obtained as lyophilized powder from Sigma-Aldrich (St Louis, MO, USA). Macro-pore silica gel (SPS 300-7; pore size 300 Å, particle size 7.0 μm) was supplied by Fuji Silysia Chemical Company (Tokyo, Japan). All other reagents were of analytic grade unless stated specifically.
Immobilization of HSA
1882
Figure 1. Chemical structure of (E)-3-(3,4-dihydroxyphenyl)acrylic acid, also named caffeic acid.
wileyonlinelibrary.com/journal/bmc
A widely reported N-hydroxysuccinimide (NHS) method (Wu et al., 2013) was employed to covalently attach HSA on the surface of macro-porous silica gel (Fig. 2). Briefly, 2.0 g of the silica gel was pretreated with 16% (v/v) hydrochloric acid through refluxing at 110 °C overnight. Subsequently, the treated gel was rinsed six times with water and filtered using a 0.22 μm
Copyright © 2014 John Wiley & Sons, Ltd.
Biomed. Chromatogr. 2014; 28: 1881–1886
Binding of caffeic acid to human serum albumin
Figure 2. Preparation of N-hydroxysuccinimide (NHS)-activated silica for protein immobilization. Potassium phosphate buffer: 50 mM potassium phosphate buffer (pH 7.2).
nylon filter. The resulting gel was dried overnight under vacuum at 120 °C. The dried gel was further transferred to a 150 mL round-bottom flask and merged with 40 mg disuccinimidyl carbonate (DSC). The mixture was suspended in 30 mL dry acetone and gently agitated with a stirring bar. A solution containing 2.0 mL triethylamine and 20 mL dry pyridine was placed dropwise into the suspension under a nitrogen stream during the course of 30 min. Followed by an additional 60 min agitation, the mixture was washed with acetone to remove the remaining DSC. The final gel was filtered and then dried under vacuum overnight at room temperature. Potassium phosphate buffer (PBS, 50 mM, pH 7.2) was used as slurry solution and propulsive agent to pack stainless steel chromatographic 7 columns (50 × 4.6 mm.) under a pressure of 4.0 × 10 Pa. The immobilization of HSA on the NHS-coated silica gel was performed by cyclically flushing the column for 2.0 h with phosphate buffer (50 mM, pH 7.2) containing 20 mg/mL HSA.
Nonspecific adsorption of HSA column Nonspecific adsorption of the column containing immobilized HSA was examined by comparing the retention behaviors of L-tryptophan, S-warfarin, tamoxifen and digitoxin on immobilized HSA with that on control columns, viz. columns containing bare silica and NHS-activated gel. The mobile phase used for this aim was phosphate buffer (50 mM, pH 7.2). The detection wavelengths were 280 nm for L-tryptophan, 282 nm for S-warfarin, 240 nm for tamoxifen and 220 nm for digitoxin. Each drug was measured three times to achieve a mean capacity factor with a flow rate of 0.2 mL/min and an injection volume of 5.0 μL (1.0 mg/mL).
Results and discussion Immobilization of HSA The activated sites on the surface of NHS-coated gel were determined by measuring the NHS groups released into solution after hydrolysis (Miron and Wilchek, 1982). It presented a value of 12.6 (±0.4) μM activated groups per gram gel. Bicinchoninic acid assay was used to determine the amounts of HSA immobilized on the surface of the stationary phase by the analysis of total protein concentration pro- and post-immobilization. The final content of HSA on the stationary phase was calculated to be 10.3 mg/g silica. This value well corresponded to the coverage of a 0.11 monolayer for HSA on the silica’s surface (480 m2/g) based on the size of 140 × 40 Å for HSA (Lu et al., 2008). Kim et al. (2006) investigated the immobilization of HSA on the surface of the same kind of silica gel using an off-line NHS method and obtained a value of 125 nM HSA per gram silica during the immobilization. Compared with their work, the current on-line assay was believed to be more efficient owing to a higher amount of immobilized HSA on the gel. Nonspecific adsorption of HSA column
Interaction between caffeic acid and HSA The binding of caffeic acid to HSA was studied by the mathematical model we proposed above. In this case, the mole amounts of injected caffeic acid were 20.0, 15.0, 10.0, 5.0, 2.5, 1.25, 0.63, 0.32 and 0.16 nM. The mobile phase was phosphate buffer (50 mM, pH 7.2) with a flow rate of 0.2 mL/min. The detection wavelength was set at 323 nm. All the experiments were performed at 37 °C to imitate the temperature for a drug binding to HSA in vivo.
Validation of the proposed mathematical model
The next item studied in this work was to assess the nonspecific adsorption of immobilized HSA synthesized by the on-line NHSattaching method. In this case, the retention properties of caffeic acid on bare silica, NHS-coated gel and immobilized HSA columns were measured in triplicate. Caffeic acid gave approximate capacity factors on bare silica and NHS-coated gel (Table 1). This result indicated that the silica gel itself was the main source of weak nonspecific interaction during the binding of caffeic acid to immobilized HSA. This result was expected because NHS can only activate a small amount of silicanols on the silica and the rest of the surface was available as the adsorption sites for a drug. The reason for the similar capacity factors of caffeic acid on the two control columns may be partly behind the direct reaction between bare silica and DSC. During the reaction, DSC directly reacted with silianols on the surface of silica to form an active NHS ester, whereby we believe no spacers or any other active groups were present at the silica surface. The remaining active sites were removed by hydrolysis (Kim et al., 2006) after these NHS-activated sites were further used for HSA immobilization. It was also notable that caffeic acid illustrated a retention time of 4.0 min on the column containing immobilized HSA.
Copyright © 2014 John Wiley & Sons, Ltd.
wileyonlinelibrary.com/journal/bmc
1883
The next set of experiment was designed to confirm the validation of the mathematical model we proposed using frontal analysis, which is widely known to be a powerful and classic tool for revealing drug–protein interaction in affinity chromatography. Caffeic acid was dissolved in ethanol to prepare a stock solution of 10 mM, and further diluted with phosphate buffered solution (50 mM, pH 7.2) to obtain a series of chromatographic mobile phases containing 1.0, 2.0, 4.0, 6.0, 8.0 and 10.0 μM of the drug. All the mobile phases were totally degassed by ultrasonic wave in prior to be used. Frontal analysis was performed using the chromatographic mobile phase at a flow rate of 0.2 mL/min. A correction for the system void time was made by performing similar experiments using sodium nitrite (1.0 μM) as a nonretained solute. The column was
Biomed. Chromatogr. 2014; 28: 1881–1886
regenerated between each study by passing phosphate buffered solution (50 mM, pH 7.2) through the column. All experiments were performed in triplicate under each set of test conditions.
Y. An et al. Table 1. Nonspecific binding of caffeic acid and probe drugs to various silica-based stationary phases
Caffeic acid L-Tryptophan S-Warfarin Tamoxifen Digitoxin
Capacity factors Bare silica control column
NHS control column
0.23 ± 0.03 0.08 ± 0.01 0.28 ± 0.03 0.16 ± 0.02 0.43 ± 0.05
0.24 ± 0.02 0.07 ± 0.03 0.27 ± 0.05 0.18 ± 0.01 0.41 ± 0.06
HSA column 4.00 ± 0.10 3.83 ± 0.18 4.41 ± 0.16 2.16 ± 0.12 2.50 ± 0.07
All of these capacity factors were measured at 37 °C. The void time of the system was determined to be 1.2 min using sodium nitrite as a nonretention solute. NHS, N-hydroxysuccinimide; HSA, human serum albumin.
Taking all the results into account, nonspecific adsorption was believed to have little effect on the binding of caffeic acid to HSA for the reason that it was easily subtracted from the capacity factors of the drug on immobilized HSA. Nonspecific binding of the HSA column was tested by the retention behaviors of L-tryptophan, S-warfarin, tamoxifen and digitoxin. The four drugs are well known to have clear binding to HSA and are commonly used as site-selective ligands to probe drug–HSA interaction. For all four drugs, no substantial differences in the capacity factors were found between the values determined from the bare silica column and the NHS-coated gel column. This result is in good agreement with the data for the binding of caffeic acid to HSA immobilized by the same method. Therefore, we concluded that the nonspecific adsorption of the immobilized HSA can be mainly attributed to the silica gel itself. Since the nonspecific adsorption arose from the bare silica, the second comparison was only made between the capacity factors of the four drugs on the bare silica column and HSA column. Compared with the retention on bare silica, all the drugs presented good retentions on HSA column. Nonspecific bindings of L-tryptophan, S-warfarin, tamoxifen and digitoxin contributed 2.1, 6.3, 7.4 and 17.2% to their retention on immobilized HSA. Based on these results, the immobilized HSA using NHS-activated method was supposed to be capable of probing the drug–HSA interaction.
Absorbance 323 nm
Drugs
50 40 30 20 10 0 0
2
4
6
8
10
12
14
16
18
Time (min) Figure 3. Representative chromatograms of caffeic acid on the immobilized human serum albumin (HSA) column when varied mole amounts of the drug were injected. From left to right, the amounts of caffeic acid were 30.0, 20.0, 10.0, 15.0, 10.0, 5.0 and 2.5 nM.
Table 2. Capacity factors of caffeic acid on conlumn containing immobilized HSA when declining mole amounts of caffeic acid are injected as solutes Mole amounts of injection (nM) 30.0 25.0 20.0 15.0 10.0 7.50 5.00 2.50 1.25
Capacity factors
3.60 3.84 4.22 4.45 4.78 4.90 5.11 5.27 5.37
3.61 3.87 4.21 4.46 4.75 4.88 5.12 5.30 5.34
3.62 3.86 4.21 4.47 4.76 4.89 5.10 5.28 5.35
Mean capacity factors 3.61 3.86 4.21 4.46 4.76 4.89 5.11 5.28 5.35
k′nI 1þk′
23.48 19.84 16.17 12.25 8.27 6.23 4.18 2.10 1.05
Interaction between caffeic acid and immobilized HSA
1884
The representative chromatograms of caffeic acid on the column containing immobilized HSA are pictured in Fig. 3, when varied mole amounts of the drug were used as the injection solutes. They show that the retention times of caffeic acid negatively corresponded to the injection volumes in the range 0.16 20.0 nM. The capacity factors of the drug decreased with increasing injection amounts of the drug used. These results accord well with the prediction of our model, providing a proof of applying the current model in realizing drug–protein interaction. Capacity factors of caffeic acid on HSA column are listed in Table 2 when increasing injection amounts of the drug were performed. It was found that the capacity factors grew when shrinking amounts of the drugs were injected. Equation (10) was accordingly used to plot the curve of k′nI/(1 + k′) against k′. A linear
wileyonlinelibrary.com/journal/bmc
Figure 4. Plot of (k’nI)/(1 + k’) vs k’ when the injection mole amounts of caffeic acid were 20.0, 15.0, 10.0, 5.0, 2.5, 1.25, 0.63, 0.32 and 0.16 nM. The regression equation is y = 12.84x + 69.64.
Copyright © 2014 John Wiley & Sons, Ltd.
Biomed. Chromatogr. 2014; 28: 1881–1886
Binding of caffeic acid to human serum albumin
Figure 5. Frontal analysis of caffeic acid on the immobilized HSA column at pH 7.2 and 37 °C, where the concentrations of applied caffeic acid (from right to left) are 1.0, 2.0, 4.0, 6.0, 8.0 and 10.0 μM.
relationship was obtained, shown in Fig. 4, with a correlation coefficient of 0.9979 and a regression equation of y = 12.84x + 69.64. Using the slope and intercept of the curve, the association constant for the binding of caffeic acid to HSA was calculated to be (2.75 ± 0.14) × 104/M and the binding site was 69 nM. Another important result was that no deviation from the linear curve between k′nI/(1 + k′) and k′ occurred in the whole regression range. This result indicated that only one type of binding site was available on the column for caffeic acid targeting HSA. This deduction was reasonable because it agreed well with the report by Liu et al. (2010) in which the authors discovered that only site I on bovine serum albumin participates the binding of caffeic acid to the protein. Moreover, another report found that caffeic acid had increasing association constants during the binding to HSA when decreasing temperatures were tested (Zhang et al., 2008). For instance, the association constants at 303 and 310 K were determined to be 3.06 × 104 and 2.82 × 104/M, respectively. These data were in good agreement with the value of (2.75 ± 0.14) × 104/M determined in this work at the same temperature. Although different approaches were used in the references and this work, similar conclusions were obtained for the binding of caffeic acid to HSA. This discovery confirmed the feasibility of our model for the pursuit of drug–protein interaction. Validation of the current method for probing caffeic acid-HSA interactions To validate the application of our model in realizing drug– protein interaction, we further examined the binding of caffeic acid to immobilized HSA by frontal analysis. In this case, a widely known equation (Zhao et al., 2013) was utilized to calculate the association constant and the binding site of caffeic acid to immobilized HSA: 1 1 1 ¼ þ mLapp ðK A mL ½AÞ mL
(11)
Biomed. Chromatogr. 2014; 28: 1881–1886
Conclusion In the present work, we studied the binding of caffeic acid to HSA by HPAC technologies. A new mathematical model and frontal analysis were used to calculate the association constant and the number of binding sites of caffeic acid–HSA interaction. The two methods suggested that caffeic acid only has one type of binding site on HSA. Moreover, the association constant and the number of binding sites calculated from the two assays were in good agreement. In addition, the data obtain by the new model fitted previous observations on interaction between caffeic acid and HSA by spectrometric methods. All of these results indicated that the relationship between retention factors and the amounts of injection has potential for the pursuit of drug–protein interaction.
Acknowledgments We cordially thank the National Natural Sciences Foundation of China (nos J1210063; 21005060), the Program for Changjiang Scholars and Innovative Research Team in University (no. IRT1174), the project for Innovative Research Team of Research and Technology of Shaanxi Province (no. 2013KCT-24) and the key project from Ministry of Science and Technology of the China (no. 2013YQ17052509) for financial support.
References Bal W, Sokołowska M, Kurowska E and Faller P. Binding of transition metal ions to albumin: sites, affinities and rates. Biochimica et Biophysica Acta 2013; 1830: 5444–5455. Belgacem O, Stübiger G, Allmaier G, Buchacher A and Pock K. Isolation of esterified fatty acids bound to serum albumin purified from human plasma and characterized by MALDI mass spectrometry. Biologicals 2007; 35: 43–49. Chung MJ, Walker PA and Hogstrand C. Dietary phenolic antioxidants, caffeic acid and Trolox, protect rainbow trout gill cells from nitric oxide-induced apoptosis. Aquatic Toxicology 2006; 80: 321–328.
Copyright © 2014 John Wiley & Sons, Ltd.
wileyonlinelibrary.com/journal/bmc
1885
where KA is the association constant for binding of A to L, and [A] is the concentration of the solute applied to the column; mL is related to the true number of binding sites on the column; and mLapp denotes the apparent moles of solute required to reach the platform of the breakthrough curve. Typical breakthrough
curves obtained from the application of increasing concentration of caffeic acid on immobilized HSA column were shown in Fig. 5. As caffeic acid increased, it resulted in a saturation of HSA and produced a breakthrough curve which was used to calculate the apparent moles of caffeic acid at the mean point. The plot for 1/mLapp against 1/[caffeic acid] presented a linear relationship with a regression equation y = 0.5743x + 0.01524 and a correlation coefficient of 0.9977 (n = 6). This result suggested that only a single type of binding site was present for caffeic acid on the immobilized HSA. The association constant determined from the regression equation was 2.66 × 104/M, which agreed well with the value obtained by spectrometric assays (Liu et al., 2010). Compared with the data determined by spectrometric assays (Liu et al., 2010), the association constant calculated from frontal analysis was in good agreement with the value determined by our new model. This was expected since frontal analysis and our mathematical model were all carried out using the HPAC system. More importantly, frontal analysis is often accomplished by constantly flushing the column with a set of drug solutions at varied concentrations. This special requirement causes issues of long operation time and high drug consumption. Focusing on this point, our model is worthy of widespread application owing to the capacity to probe drug–protein interaction with the advantages of drugsaving and rapid performance.
Y. An et al. Damasceno SS, Santos NA, Santos IMG, Souza AL, Souza AG and Queiroz N. Caffeic and ferulic acids: an investigation of the effect of antioxidants on the stability of soybean biodiesel during storage. Fuel 2013; 107: 641–646. Enyedy ÉA, Horváth L, Hetényi A, Tuccinardi T, Hartinger CG, Keppler BK and Kiss T. Interactions of the carrier ligands of antidiabetic metal complexes with human serum albumin: a combined spectroscopic and separation approach with molecular modeling studies. Bioorganic and Medicinal Chemistry 2011; 19: 4202–4210. Gabriella F, Alessandra M, Viviana T, Maria M, Mauro F and Paolo A. Human serum albumin: from bench to bedside. Molecular Aspects of Medicine 2012; 33: 209–290. Kim HS and Wainer IW. Rapid analysis of the interactions between drugs and human serum albumin (HSA) using high-performance affinity chromatography (HPAC). Journal of Chromatography B 2008; 870: 22–26 Kim HS, Mallik R and Hage DS. Chromatographic analysis of carbamazepine binding to human serum albumin: II. Comparison of the Schiff base and N-hydroxysuccinimide immobilization methods. Journal of Chromatography B 2006; 837: 138–146. Liu QW, Xu H, Li GH, Zhang T and Qiao QA. Insight into interaction of caffeic acid with bovine serum albumin. Food Science 2010; 31: 24–28. Lu QH, Ba CD and Chen DY. Investigating noncovalent interactions of rutin – serum albumin by capillary electrophoresis – frontal analysis. Journal of Pharmaceutical and Biomedical Analysis 2008; 47: 888–891. Mallik R, Yoo MJ, Briscoe CJ and Hage DS. Analysis of drug–protein binding by ultrafast affinity chromatography using immobilized human serum albumin. Journal of Chromatography A 2010; 1217: 2796–2803. Matsud R, Anguizol J, Joseph KS and Hage DS. Analysis of drug interactions with modified proteins by high-performance affinity chromatography: binding of glibenclamide to normal and glycated human serum albumin. Journal of Chromatography A 2012; 1265: 114–122. Miron T and Wilchek M. A spectrophotometric assay for soluble and immobilized N-hydroxysuccinimide esters. Analytical Biochemistry 1982; 126: 433–435. Qian J, Tang QL, Cronin B, Markovich R and Rustum A. Development of a high performance size exclusion chromatography method to determine the stability of human serum albumin in a lyophilized formulation of Interferon alfa-2b. Journal of Chromatography A 2008; 1194: 48–56. Rajdev P, Mondol T, Makhal A and Pal SK. Simultaneous binding of antituberculosis and anti-thrombosis drugs to a human transporter protein: a FRET study. Journal of Photochemistry and Photobiology B: Biology 2011; 103: 153–158.
Ryan AJ, Ghuman J, Zunszain PA, Chung CW and Curry S. Structural basis of binding of fluorescent, site-specific dansylated amino acids to human serum albumin. Journal of Structural Biology 2011; 174: 84–91. Tong Z, Schiel JE, Papastavros E, Ohnmacht CM, Smith QR and Hage DS. Kinetic studies of drug–protein interactions by using peak profiling and high-performance affinity chromatography: Examination of multi-site interactions of drugs with human serum albumin columns. Journal of Chromatography A 2011; 1218: 2065–2071. Tsai SJ, Chao CY and Yin MC. Preventive and therapeutic effects of caffeic acid against inflammatory injury in striatum of MPTP-treated mice. European Journal of Pharmacology 2011; 670: 441–447. Tsuruda PR, Yung J, Martin WJ, Chang R, Mai N and Smith JAM. Influence of ligand binding kinetics on functional inhibition of human recombinant serotonin and norepinephrine transporters. Journal of Pharmacological and Toxicological Methods 2010; 61: 192–204. Wang YC, Zhang CH, Deng NY and Wang Y. Kernel-based data fusion improves the drug–protein interaction prediction. Computational Biology and Chemistry 2011; 35: 353–362. Wu H, Zhang CH, Liang YP, Shi JF, Wang XL and Jiang ZY. Catechol modification and covalent immobilization of catalase on titania submicrospheres. Journal of Molecular Catalysis B: Enzymatic 2013; 92: 44–50. Yang F, Ma ZY, Zhang Y, Li GQ, Li M, Qin JK, Lockridge O and Liang H. Human serum albumin-based design of a diflunisal prodrug. European Journal of Pharmaceutics and Biopharmaceutics 2013; 84: 549–554. Yoo MJ, Schiel JE and Hage DS. Evaluation of affinity microcolumns containing human serum albumin for rapid analysis of drug–protein binding. Journal of Chromatography B 2010; 878: 1707–1713. Yue YY, Liu JM, Fan J and Yao XJ. Binding studies of phloridzin with human serum albumin and its effect on the conformation of protein. Journal of Pharmaceutical and Biomedical Analysis 2011; 56: 336–342. Zhang L, Zhang WP, Chen KD, Qian XD, Fang SH and Wei EQ. Caffeic acid attenuates neuronal damage, astrogliosis and glial scar formation in mouse brain with cryoinjury. Life Sciences 2007; 80: 530–537. Zhang YH, Yue YY, Li JZ and Chen XG. Studies on the interaction of caffeic acid with human serum albumin in membrane mimetic environments. Journal of Photochemistry and Photobiology B: Biology 2008; 90: 141–151. Zhao XF, Huang JJ, Li Q, Wei LS, Zheng JB, Zheng XH, Li ZJ and Zhang YY. Revealing binding interaction between seven drugs and immobilized β2-adrenoceptor by high-performance affinity chromatography using frontal analysis. Journal of Molecular Recognition 2013; 26: 252–257. Zinn N, Hopf C, Drewes G and Bantscheff M. Mass spectrometry approaches to monitor protein–drug interactions. Methods 2012; 57: 430–440.
1886 wileyonlinelibrary.com/journal/bmc
Copyright © 2014 John Wiley & Sons, Ltd.
Biomed. Chromatogr. 2014; 28: 1881–1886
