Binding site identification of metformin to human serum albumin and glycated human serum albumin by spectroscopic and molecular modeling techniques: a comparison study.

This article was downloaded by: [Nipissing University] On: 18 October 2014, At: 19:40 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Biomolecular Structure and Dynamics Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tbsd20

Binding site identification of metformin to human serum albumin and glycated human serum albumin by spectroscopic and molecular modeling techniques: a comparison study a

a

a

Elaheh Rahnama , Maryam Mahmoodian-Moghaddam , Sabra Khorsand-Ahmadi , Mohammad b

Reza Saberi & Jamshidkhan Chamani

a

a

Faculty of Sciences, Department of Biochemistry and Biophysics, Islamic Azad University, Mashhad Branch, Mashhad, Iran b

Medical Chemistry Department, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran Published online: 10 Apr 2014.

To cite this article: Elaheh Rahnama, Maryam Mahmoodian-Moghaddam, Sabra Khorsand-Ahmadi, Mohammad Reza Saberi & Jamshidkhan Chamani (2014): Binding site identification of metformin to human serum albumin and glycated human serum albumin by spectroscopic and molecular modeling techniques: a comparison study, Journal of Biomolecular Structure and Dynamics, DOI: 10.1080/07391102.2014.893540 To link to this article: http://dx.doi.org/10.1080/07391102.2014.893540

PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions

Journal of Biomolecular Structure and Dynamics, 2014 http://dx.doi.org/10.1080/07391102.2014.893540

Binding site identification of metformin to human serum albumin and glycated human serum albumin by spectroscopic and molecular modeling techniques: a comparison study Elaheh Rahnamaa, Maryam Mahmoodian-Moghaddama, Sabra Khorsand-Ahmadia, Mohammad Reza Saberib and Jamshidkhan Chamania* a

Faculty of Sciences, Department of Biochemistry and Biophysics, Islamic Azad University, Mashhad Branch, Mashhad, Iran; Medical Chemistry Department, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran

b

Communicated by Ramaswamy H. Sarma

Downloaded by [Nipissing University] at 19:40 18 October 2014

(Received 27 September 2013; accepted 8 February 2014) The interaction between metformin and human serum albumin (HSA), as well as its glycated form (gHSA) was investigated by multiple spectroscopic techniques, zeta potential, and molecular modeling under physiological conditions. The steady state and time-resolved fluorescence data displayed the quenching mechanism of HSA–metformin and gHSA–metformin was static. The binding information, including the binding constants, number of binding sites, effective quenching constant showed that the binding affinity of metformin to HSA was greater than to gHSA which also confirmed by anisotropy measurements. It was determined that metformin had two and one set of binding sites on HSA and gHSA, respectively. Far-UV CD spectra of proteins demonstrated that the α-helical content decreased with increasing metformin concentration. The zeta potential and resonance light scattering (RLS) diagrams provided that lower drug concentration induced metformin aggregation on gHSA surface as compare to HSA. The increase in polarizability was one of the important factors for the enhancement of RLS and the formation of drug/protein complexes. The zeta potential results suggested that both hydrophobic and electrostatic interactions played important roles in the protein–metformin complex formation. Site marker experiments and molecular modeling showed that the metformin bound to subdomain IIIA (Sudlow’s site II) on HSA and gHSA. Keywords: HSA; gHSA; metformin; spectroscopy; zeta potential; molecular modeling

1. Introduction Human serum albumin (HSA) is the most abundant carrier protein and plays an important role in the transport and disposition of many endogenous and exogenous substances such as metabolites, drugs, and other biologically active compounds present in blood (Bourassa et al., 2011). The concentration of HSA in blood plasma is ~40 mg mL−1; it constitutes up to 60% of the total plasma proteins and contributes to 80% of the colloid osmotic blood pressure (Równicka-Zubik et al., 2009). HSA is a globular protein composed of 585 amino acid residues in three homologous α helical domains (I, II, III). Each domain contains 10 helices that are divided into six antiparallel helices and two subdomains (A and B). There is only one tryptophan located at position 214 along the chain, in subdomain II A of HSA (N’soukpoé-Kossi, Sedaghat-Herati, Ragi, Hotchandani, & Tajmir-Riahi, 2007). This protein has two major binding sites for drugs: Sudlow’s sites I and II. Sudlow’s site I, which is found in subdomain IIA of HSA, binds bulky heterocyclic compounds such as coumarins, sulfonamides, and salicylate. Sudlow’s site II, found in

*Corresponding author. Email: [email protected] © 2014 Taylor & Francis

subdomain IIIA, binds aromatic carboxylic acids and profens (Joseph, Anguizola, & Hage, 2011). Diabetes mellitus, characterized by defective blood sugar regulation, exists in two forms: type I and type II. Type I occurs when the production of insulin is compromised due to pancreatic beta cell destruction. Type II accounts for 90% of all cases of diabetes and occurs when insulin receptors become resistant to insulin, demanding a higher insulin secretion level, which overburdens the pancreas until it fails (Mendez, Jensen, McElroy, Pena, & Esquerra, 2005). HSA has several important physiological and pharmacological functions. It transports metals, fatty acids, cholesterol, bile pigments, and drugs. In normal conditions, its half-life is about 20 days. A large proportion of total serum antioxidant properties can be attributed to albumin (Roche, Rondeau, Singh, Tarnus, & Bourdon, 2008). One process that is believed to affect the binding of drugs to HSA is glycation, which refers to the modification of a protein by a process that begins with the reaction between a reducing sugar and a free amine group on a protein. This process can occur for HSA and


2

E. Rahnama et al.

becomes more pronounced in diabetes when an elevated amount of glucose is present in the blood stream. While an average individual has 6–13% of HSA in glycated form, a person with diabetes may have 20–30% or more glycated HSA in the circulation (Chiou, Tomer, & Smith, 1999; Mendez et al., 2005; Nakajou, Watanabe, Kragh-Hansen, Maruyama, & Otagiri, 2003; Garlick & Mazer, 1983). This process, involves the addition of reducing sugars and/or their degradation products to free primary and secondary amine groups on proteins (Barnaby, Cerny, Clarke, & Hage, 2011). Therefore, for diabetic patients in addition of HSA, glycated human serum albumin (gHSA) also is able to bind and deliver some drugs such as metformin that is the most frequently used anti diabetic drug worldwide. Metformin improves peripheral glucose uptake and reduces hepatic glucose in patients with type 2 diabetes mellitus (T2DM) (Grisouard et al., 2010). Metformin (1,1-dimethylbiguanide; Scheme 1) is used as monotherapy or in combination with other antidiabetic agents including insulin (Lai & Feng, 2006). It is extensively accepted in pharmaceutical industry that the overall distribution, metabolism, and efficacy of many drugs can be changed based on their affinity to plasma proteins, especially HSA; on the other hand, the interaction between drugs and HSA can change variants of HSA that their binding properties can be different with respect to native protein (Yue, Chen, Qin, & Yao, 2009). Hence, in recent years several spectroscopic methods have been used to investigate the interaction of drugs and HSA and clarify the conformational change of protein (Bourassa et al., 2011; Chiou et al., 1999; Joseph et al., 2011; Mendez et al., 2005; N’soukpoé-Kossi et al., 2007; Roche, Rondeau, Singh, Tarnus, & Bourdon, 2008; Równicka-Zubik et al., 2009) but there is no report about interaction between HSA and gHSA with metformin. In this work, the interaction between metformin with HSA and gHSA was investigated by biophysical methods such as multi-spectroscopic methods and molecular modeling. The aim of the present study was to investigate the interaction mechanism between metformin with HSA and gHSA in order to compare the two forms with regard to the specific binding site, binding affinity and the effect of metformin on the conformation of HSA and gHSA. Because there are different binding properties in the interaction between drugs with HSA as compare to

Scheme 1.

The chemical structure of metformin.

gHSA, thus each of them interact with the special concentration of drugs and determining the drug dosage should be different. Therefore, our work will provide some important information for drug usage doses (Li, Li et al., 2008). 2. Materials and methods 2.1. Material and solutions HSA and metformin were obtained from Sigma-Aldrich Company (St. Louis, MO, USA) and used without further purification. A stock solution of HSA was prepared by dissolving an appropriate amount of solid HSA into potassium phosphate buffer (pH 7.4) with a concentration of 4.5 × 10−3 mM. The metformin solution (1 mM) was also prepared by dissolution in the phosphate buffer (pH 7.4). gHSA sample preparation was performed in 50 mM phosphate buffer, pH 7.4, by addition of 1 ml D-glucose (100 mM) to 1 ml of HSA (80 mg ml−1). This solution was incubated under sterilization for six days at 37 °C, and then centrifuged for 1 h, at 4 °C, rotation 8000 rps. Subsequently, the solution was dialyzed three times, each time during 8 h. All solutions were prepared at room temperature and were stored in a refrigerator at 4 °C in the dark. The extinction coefficients were used to calculate the concentration of protein. If the initial concentration and volume of the protein solution are [P]0 and V0, respectively, and the stock ligand concentration is [L]0, then the total concentration of protein ([P]t) and ligand ([L]t) can be obtained by accounting for the total volume of the aliquot (Vc) added during the titration experiment (Wang, Zhao, Wei, Zhang, & Ji, 2010): ½Pt ¼ ½P0 V0 =ðV0 þ Vc Þ;

½Lt ¼ ½L0 V0 =ðV0 þ Vc Þ

The extent of glycation was assessed by the thiobarbituric acid reaction to be 0.32 mM 5-hydroxymethylfurfural (5HMF) equivalents (approx. 1 mol 5-HMF/mol HSA). The extinction coefficient values of HSA and gHSA are 12.3 × 104 and 13.5 × 104 M−1 cm−1 respectively.

2.2. Method 2.2.1. Fluorescence measurements Fluorescence spectra were recorded on an F-2500 spectrofluorometer (Hitachi, Tokyo, Japan) linked to a personal computer and equipped with a 150-W xenon arc lamp, with grating excitation and emission monochromators, and a Hitachi recorder. Slit widths for both monochromators were set at 10 nm. A 1.0 cm quartz cell was used. Moreover, the fluorescence intensities were corrected for absorption of excitation light and reabsorption of emitted light to decrease the inner filter and dilution effects using the formula:

Interaction between Metformin with HSA and gHSA Fcor ¼ Fobs eðAex þAem Þ=2

(1)


where Fcor and Fobs are the fluorescence intensities corrected and observed, Aex and Aem are the absorption of the system at excitation and emission wavelength, respectively (Równicka-Zubik et al., 2009). A 2.0 ml solution containing an appropriate concentration of HSA was titrated manually by successive addition of a 1 mM stock solution of metformin with trace syringes. The excitation wavelength was 280 and 295 nm, and the emission wavelength was 300–500 nm. The HSA fluorescence intensity was measured using an excitation wavelength of 305 nm for red edge excitation shift (REES) investigation. 2.2.2. Resonance light scattering and synchronous fluorescence For the resonance light scattering (RLS) measurements, the excitation and emission monochromators were scanned simultaneously with Δλ = 0 nm from 220 to 600 nm with the same instrument used for fluorescence measurements. A 2-ml solution containing 4.5 × 10−3 mM protein was injected by successive additions of metformin to a maximum concentration of 0.17 mM. 2.2.3. Synchronous fluorescence spectroscopy Synchronous fluorescence spectra were obtained by simultaneously scanning the excitation and emission monochromators. They are characteristic of the tyrosine and tryptophan residues of HSA when the wavelength interval Δλ is 15 and 60 nm, respectively. The concentration of HSA and gHSA was 4. 5 × 10−3 mM and the concentration of metformin was 0.17 mM. 2.2.4. Fluorescence anisotropy F-2500 spectrofluorometer (Hitachi, Japan) in “L-format” was used for the steady-state fluorescence anisotropy measurements, for which the excitation and emission slit widths were both 5 nm. The excitation wavelengths were set at 280 nm, and the emission wavelengths were registered between 300 and 600 nm. A long-pass absorption filter was used on the emission channel in order to ensure the separation of fluorescence from scattered light. The experimental solutions were prepared with the following concentrations: [HSA] = 0.45 × 10−3 mM, −3 [gHSA] = 0.45 × 10 mM and [metformin] = 0.17 mM. 2.2.5. Zeta potential measurements The zeta potential was determined by laser Doppler electrophoresis, performed on a Zetasizer Non series-ZS (Malvern Instrument, UK) at 298 K using the drug and proteins. For this, HSA and metformin were dissolved in

3

a phosphate buffer (pH 7.4). The experimental solutions were prepared with the following concentrations: [HSA] = 4.5 × 10−3 mM, [gHSA] = 4.5 × 10−3 mM and [metformin] = 0.17 mM. 2.2.6. Time-resolved fluorescence spectra Time-resolved fluorescence spectra were executed in a time-correlated single photon counting system on an FL920P spectrometer (Edinburgh Instruments, UK) with λex = 295 nm. The data were fitted to biexponential functions after deconvolution of the instrumental response function by an iterative reconvolution approach. This was performed with the DAS6 decay analysis software utilizing reduced χ and weighted residuals as parameters for goodness of fit. The average fluorescence lifetime (τ) for biexponential iterative fitting was calculated from the decay times and the relative amplitudes (A) using the following equation: s ¼ s1 A 1 þ s2 A 2

(2)

2.2.7. Circular dichroism measurements Circular dichroism (CD) spectra were obtained on a J-815 automatic recording spectropolarimeter (Jasco, Tokyo, Japan) with a quartz cell with a 2 mm path length at room temperature. Dry nitrogen gas was used to purge the machine before and during the measurements. The band width was 1 nm. The rotatory contributions of a protein can be determined by X = fH XH + fβ Xβ + fT XT + fR XR, where X is either the ellipticity or the rotation at any wavelength, and f is the fractions of the helix (fH), beta form (fβ), turn (fT) and unordered form (fR); the sum of f is equal to unity and each f is greater than or equal to zero. The secondary structure contents of the proteins were analyzed by SELCON3, CONTIN, and CDSSTR to estimate the relative proportions of α-helices, β-sheets, turns, and random coils (Chen, Yang, & Martinez, 1972; Sreerama & Woody, 2000). The samples for CD were prepared with a fixed concentration of HSA (4.5 × 10−3 mM), gHSA (4.5 × 10−3 mM) and 0.17 mM metformin. 2.2.8. UV–vis spectroscopy UV–vis spectroscopy absorption spectra were obtained with a Jasco V-630 spectrophotometer. Measurement information included the cell length (10 mm), data pitch (1 nm), band width (1.5 nm), response (fast), and scanning speed (400 nm/min). 2.2.9. Molecular modeling The crystal structure of HSA was obtained from the Protein Data Bank (PDB entry code 1AO6). A

4

E. Rahnama et al.


three-dimensional form of gHSA and metformin were modeled by the MOE software 2008. Molecular modeling of HSA–metformin and gHSA–metformin was performed with the Autodock4 program and MOE software 2008. For the docking calculations, polar hydrogens were added to the protein and all water molecules were removed from the protein by the AutoDock tool. The Lamarckian genetic algorithm was used to calculate the interaction between the drug and the protein. The maximum number of energy evaluations for each run was set to medium. To determine the interaction of proteins with a ligand, the grid box was set to include whole protein domains for HSA and gHSA, as well as the ligand. The conformation with the lowest energy was used for the final analysis with the Swiss–PDB viewer, Molegro and Viewer Light software.

2.2.10. Protein modeling The three-dimensional structure of gHSA has been designed by homology modeling. The HSA sequence was obtained from Uniprot, after which a similarity search was performed using Psi-Blast. A structure with a similar identity was selected as a candidate template. Modeller 9v7 was employed to simulate the target protein. The protein models were refined and the energy was minimized (by Hyper Chem 7) according to evaluation scores until the best structure was obtained. The results were analyzed by Viewer Lite and SPDV and tests, such as Ramachandran plots and the ERRAT algorithm from the UCLA server. The ERRAT test and Ramachandran plot and according to the results, the number of residues in the favored region was 646 (95.8%)(~98.0% expected), and number of residues in the allowed region was 22 (3.3%)(~2.0% expected) and the number of residues in the outlying region was 6 (0.9%). All of these results proved that the model was correct.

3. Results and discussion 3.1. Fluorescence quenching of HSA and gHSA by metformin The proteins containing Trp residues (such as HSA) have intrinsic fluorescence. Information about these proteins can be obtained by measuring the intrinsic fluorescence intensity of the Trp residues before and after the addition of the drug (Bourassa et al., 2011). Figure 1(A) and its inset show the fluorescence spectra of HSA at various concentrations of metformin at the excitation wavelengths of 280 and 295 nm, respectively. The maximum emission wavelength of HSA was about 340 nm, and this value decreased regularly with an increasing amount of metformin, indicating

that interaction between metformin and HSA occurred (Wang, Liu et al., 2010). Since, both tryptophan and tyrosine residue of HSA fluorescence emission when the excitation is 280 nm (although Tyr contributes more than Trp) (Sakurai & Tsuchiya, 1988), so the observed fluorescence quenching caused by the interaction between metformin with both Trp and Tyr residues of HSA. On the other hand, Figure 1(A) shows a blue shift of the maximum wavelength of HSA, and this was seen as an indication of the chromophore of the protein being transferred to a more hydrophobic environment (a decreased polarity of the microenvironment), as well as conformation of the protein becoming altered (Matei & Hillebrand, 2010; Sulkowska, Bojka, Rownicka, & Sulkowski, 2006). The same results are observed in the inset of Figure 1(A). Considering that the intrinsic fluorescence of HSA at 295 nm excitation wavelength is related to the presence of only Trp214 residue (Chamani et al., 2010), thus, the interaction between metformin and HSA leading to fluorescence quenching and increasing the hydrophobicity around of the Trp214 residue in HSA. Figure 1(B) and its inset show the fluorescence spectra of gHSA at various concentrations of metformin at the excitation wavelengths of 280 and 295 nm, respectively. As can be seen in Figure 1(B), the maximum emission wavelength of gHSA was about 340 nm. When increasing the metformin concentration, the intensity of the fluorescence spectra of gHSA decreased regularly and a blue shift of the maximum wavelength of gHSA could be noticed. Such a strong quenching clearly indicated the binding of metformin to gHSA and also addition of metformin can decrease the polarity of the region surrounding the Trp and Tyr residue of gHSA (Yue et al., 2009). The inset of Figure 1(B) recorded similar results for interaction between metformin and gHSA when the excitation wavelength was 295 nm and indicated that drug gHSA interactions leading to change in protein structure and increase in the hydrophobicity around Trp214. The fluorescence quenching of HSA and gHSA by metformin is almost similar. 3.2. Binding parameters and mechanism Fluorescence quenching refers to any process where there is a decrease of the fluorescence intensity from a fluorophore due to a variety of molecular interactions. Examples include excited state reactions, molecular rearrangements, energy transfer, ground state complex formation, and collisional quenching (Wang et al., 2010). It is known that there are two quenching mechanisms involved in a quenching process, which are usually classified as dynamic and static quenching. Dynamic quenching is attributed to the collisional encounters between the quencher and the fluorophore in the excited

Interaction between Metformin with HSA and gHSA

5

Fluorecence Intensity

4000

(A) 10000 0 mM

1000

0 300

0.17 mM

0.17 mM

2000

350

400

450

Wavelength / nm

6000

4000

2000

0 300

350

400 Wavelength / nm

450

(B)

FluorescenceIntensity

2500

5000 0 mM 4000

Fluorescence Intensity



8000

0 mM

3000

2000 0 mM 1500

500 0 300

0.17 mM

0.17 mM

1000

350

400

450

Wavelength / nm

3000

2000

1000

0 300

350

400

450

Wavelength / nm

Figure 1. (A) Fluorescence spectra of the HSA–metformin complex at λex = 280 nm. The inset gives the fluorescence spectra of HSA–metformin complex at λex = 295 nm. (B) Fluorescence spectra of the gHSA–metformin complex at λex = 280 nm. The inset gives the fluorescence spectra of the gHSA–metformin complex at λex = 295 nm. The concentration of HSA and gHSA was 4.5 × 10−3 mM and that of metformin was increased from 0 to 1.7 × 10−1 mM, T = 298 K and pH = 7.4.

state, whereas static quenching is due to the formation of a nonluminescent ground state complex between the fluorophore and quencher (Pan, Liu, Qin, Wang, & Zhao, 2010). The possible quenching mechanism can be interpreted by the Stern–Volmer equation:

F0 =F ¼ 1 þ kq s0 ½Q ¼ 1 þ Ksv ½Q

(3)

Ksv ¼ kq s0

(4)

where F0 and F are the fluorescence intensities before and after the addition of the quencher, respectively, kq is

E. Rahnama et al. (ƒa Ka)−1. The value ƒa−1 is fixed on the ordinate. The binding constant (Ka) is a quotient of the ordinate ƒa−1 and the slope (ƒa Ka)−1 (Tian et al., 2004). Figure 2 and its inset show the modified Stern–Volmer plots for the HSA and gHSA fluorescence quenching by metformin at the excitation wavelength of 280 and 295 nm, respectively. Analysis of the modified Stern–Volmer equation enabled us to determine the Ka and ƒ values for HSA– metformin and gHSA–metformin and these are listed in Table 1. Based on the modified Stern–Volmer method, Figure 2 and its inset indicated the similar results and also there was a linear dependence between F0/(F0 − F) and 1/[Q]. As can be seen, for HSA–metformin complex the slope of curves increased with increasing metformin concentration but when [Q−1] ~ 0.5 × 10−2 mM the modified Stern–Volmer plot had two regression curves, which suggested that the metformin occupied more than one binding site at high drug concentration at both excitation wavelengths. Whereas, for the gHSA–metformin complex there are one linear curve that display the drug occupied only a single binding site on gHSA at the excitation wavelengths of 280 and 295 nm (Tang, Luan, & Chen, 2006). Table 1 show that the Ka value for the HSA–metformin complex was higher than for its gHSA– metformin counterpart and this indicates that affinity of metformin to HSA was much greater than to gHSA. Glycation thus has an effect on the drug affinity to HSA and its affinity to metformin was lowered. Moreover, for HSA–metformin complex the value of Ka1 was greater than Ka2, this suggests that drug binding to HSA gave rise to an enhanced drug/protein affinity

the biomolecular quenching constant, τ0 is the average lifetime of the biomolecule (10−8 s) and [Q] is the concentration of the quencher (Pan et al., 2010). However, the Stern–Volmer equation describes dynamic quenching (Pan et al., 2010). For dynamic quenching, maximum scattering collision quenching constant (kdif) of various quenchers with biomolecules is 2.0 × 1010 L mol−1 s−1, so, if the rate constant of the protein quenching by ligands be much larger than the limiting diffusion coefficient (kdif) of the biomolecule, the quenching mechanism is static (Lakowicz & Weber, 1973; Yuan, Shen, Liu, Wei, & Gao, 2011). The calculated value of kq for HSA–metformin was kq1 = 4.32 × 1012 and kq2 = 3.03 × 1012 L mol−1 s−1 and the calculated kq value for gHSA–metformin was 1.77 × 1012 L mol−1 s−1. It can be seen that the kq values for interaction between both proteins with metformin is greater than 2.0 × 1010 L mol−1 s−1, therefore, the drug–protein complexes are formed and the quenching mechanism is static. In static quenching, in order to determine the binding constant, the experimental data from the fluorescence titration was analyzed according to the modified Stern– Volmer equation: F0 =ðF0 FÞ ¼ 1=fa þ 1=Ka fa ½Q

(5)

F0, F, and Q are here the same as in Equation (3), ƒa is the fraction of the initial fluorescence that is accessible for the quencher, and Ka represents the modified Stern– Volmer quenching constant. The dependence of F0/ΔF on the reciprocal value of the quencher concentration [Q]−1 is linear with the slope equaling the value of

F0 / F0-F

30

12 10

20

10

0 0

1

2

3

(1 / [metformin]) X 102 mM

8

F0 / F0-F


6

6 4 2 0

0

0.5

1

1.5

2

2.5

2

(1 / [metformin]) x 10 mM

Figure 2. Modified Stern–Volmer curves of fluorescence quenching of HSA and gHSA at an excitation wavelength of 280 nm, (△) HSA–metformin, (□) gHSA–metformin. The inset gives the modified Stern–Volmer curves of fluorescence quenching of HSA and gHSA at an excitation wavelength of 295 nm, (▲) HSA–metformin, (■) gHSA–metformin.


7

Table 1. Modified Stern–Volmer quenching constants, the number of binding sites, fractions of accessible protein and correlation coefficients in the HSA– and gHSA–metformin systems at pH = 7.4, λex = 280 nm. System


HSA–metformin gHSA–metformin

Ka1 (M−1)

Ka2 (M−1)

n1

n2

fa1

fa2

R1

R2

(4.32 ± 0.02) × 104 (1.77 ± 0.03) × 104

(3.03 ± 0.02) × 104

0.52 0.89

0.84

0.91 0.98

0.49

0.9983 0.9862

0.9356

and some binding sites with low affinities can become active (Sakurai & Tsuchiya, 1988). This is evidence of a cooperative behavior of metformin bound to HSA. When ƒa was equal to 1, all the fluorophores were accessible to the quencher. Consequently, a change in the value of ƒa signified that the fraction of fluorescent components accessible to the ligand became altered (Tang et al., 2006). Table 1 shows the ƒ values for the HSA–metformin and gHSA–metformin complexes. It can be seen that ƒa1 was greater than ƒa2. This implies that the interaction of the drug to HSA gave rise to a change of the protein and that the fluorophore was less available to the quencher. When small molecules bind independently to a set of equivalent sites on a macromolecule, the binding constant (Kb) and the number of binding sites (n) can be determined by the following equation: Log ½ðF0 FÞ=F ¼ log Kb þ n log ½Q

(6)

In the present case, Kb is the binding constant and n is the number of the binding sites per HSA, which can be determined by the ordinate and slope of double logarithm regression curve of log (F0 − F)/F vs. log [Q] based on the Equation (6) (Qian et al., 2010). The numbers of binding site, evaluated from the slope of these plots, are listed in Table 1. It can be seen that the number of binding sites (n) was about 1 for the gHSA–metformin system, which indicates that metformin occupied only a single binding site of gHSA, whereas for the HSA–metformin system there were two sets of binding sites for metformin. When the excitation wavelength is 295 nm, only the tryptophan residue has a fluorescence emission but at the excitation wavelength of 280 nm, both Trp and Tyr residues have fluorescence emission. Comparison of fluorescence quenching of protein excited at 280 and 295 nm allows estimating the participation of tryptophan and tyrosine groups in the complex (Chamani et al., 2010). Figure 3(A) and its inset display the quenching curves representing the 280 and 295 nm excitation wavelengths for HSA–metformin and gHSA–metformin complexes, respectively. As can be seen, the F/F0 values excited at two wavelengths decreased also the curves did not overlap. This observation indicates that both Trp and Tyr groups took part in the interaction between metformin with HSA and gHSA and also displays the slope quenching curves of HSA and gHSA by metformin at λex = 280 nm are higher than at λex = 295 nm, this is due

to the simultaneously fluorescence quenching of Trp and Tyr residues at λex = 280 nm. Figure 3(B) and its inset present the quenching curves for HSA–metformin and gHSA–metformin complexes at an excitation wavelength of 280 and 295 nm, respectively, which display that there is more binding affinity between both Trp and Tyr residues of HSA with metformin as compare to gHSA, as the results of Ka values in Table 1 confirm these observation. 3.3. Time-resolved fluorescence To establish the type of quenching that took place, timeresolved fluorescence measurements were carried out on HSA and gHSA, and then on the HSA–metformin and gHSA–metformin complexes. Average fluorescence lifetime (τ) for biexponential iterative fittings was calculated from the decay times and the relative amplitude (α) using the following equation (Mandal, Bardhan, & Ganguly, 2010): s ¼ s1 a1 þ s 2 a2

(7)

The obtained values of relative fluorescence lifetime for the proteins in the absence and presence of metformin are listed in Table 2. The average fluorescence lifetime (τ) of HSA reduces from 3.70 to 3.29 ns, in the absence and presence of metformin, respectively, implying that the fluorescence quenching is essentially a static mechanism. The similar results are observed for gHSA that represent the value of (τ) decrease from 3.52 to 3.28 ns, before and after metformin addition, respectively. Thus, both steady-state and time-resolved measurements mention to the existence the static fluorescence quenching mechanism for protein–metformin complex that caused by specific interaction, mainly by ground state complex formations (Mandal et al., 2010). By comparing recorded value of the (τ) for HSA with gHSA in the presence of metformin we find that likely both proteins are able to form complex. In other words, changes in the HSA structure will not lead to a lake of its capacity to drug delivery. 3.4. Synchronous fluorescence Synchronous fluorescence spectroscopy can separate the overlapped excitation peaks of aromatic residues in conventional fluorescence spectra. When the D-value (Δλ) between the excitation and emission wavelength is set at

8

E. Rahnama et al. 1 0.8

1

F / F0

(A)

0.6 0.4 0.2

0.8

0 0

0.05

0.1 [Q] / mM

0.15

0.2

F/F0

0.6

0.4

0

0

0.05

0.1

0.15

0.2

[Q] / mM 1 0.8

1

F / F0

(B)

0.6 0.4 0.2

0.8

0 0

0.05

0.1

0.15

0.2

[Q] / mM

0.6

F/F0


0.2

0.4

0.2

0 0

0.05

0.1

0.15

0.2

[Q] / mM Figure 3. (A) A comparison of curves of F/F0 vs. [Q] for the HSA–metformin system at λex = 280 nm (△) and λex = 295 nm (▲). The inset shows curves of F/F0 vs. [Q] for gHSA–metformin at λex = 280 nm (○) and λex = 295 nm (●). (B) Quenching curves of HSA–metformin (△) and gHSA–metformin (○) at an excitation wavelength of 280 nm. The inset shows curves of HSA–metformin (▲) and gHSA–metformin (○) at λex = 295 nm. [HSA] = 4.5 × 10−3 mM, [gHSA] = 4.5 × 10−3 mM, [metformin] = 0.17 mM, pH = 7.4 and T = 298 K.

15 or 60 nm, a spectrum characteristic of, respectively, Tyr or Trp residues is obtained (Wang, Liu et al., 2010). For aromatic Tyr and Trp residues, change in position of maximum fluorescence emission peak (λem max) reflects change in polarity around the fluorophore environment.

A red shift indicates that the fluorescing aromatic residues buried in nonpolar hydrophobic cavities are moved to a more hydrophilic environment, while a blue shift signifies an enhancement of hydrophobicity (Zhang, Ni, & Kokot, 2010).



Table 2.

9

Time resolved fluorescence data of HSA and gHSA in the presence of metformin at pH = 7.4, λex = 295 nm.

System

τ1/ns

α1

τ2/ns

α2

τ/ns

χ2

HSA HSA–metformin gHSA gHSA–metformin

1.941 1.922 1.909 1.894

0.6865 0.7512 0.6935 0.7543

6.125 6.033 5.772 6.086

0.4964 0.3741 0.4937 0.3733

3.6968 3.2887 3.5154 3.2818

0.9621 0.9638 0.9533 0.9517

Figure 4(A) and its inset show synchronous fluorescence spectra of the interaction between HSA and metformin in Δλ = 60 and 15 nm, respectively. It can be seen in both figures that fluorescence quenching was occurred and the maximum emission wavelength of Tyr (Δλ = 15 nm) had a weak blue shift, whereas a significant blue shift for Trp (Δλ = 60 nm) was observed. The blue shift of the maximum emission wavelength indicates that with an increasing metformin concentration, the conformation of HSA was changed and the polarity around the Trp and Tyr residues became decreased (more hydrophobic); on the other hand, the microenvironment surrounding the Trp residue changed more than Tyr residue. Figure 4(B) and its inset demonstrate synchronous fluorescence spectra of the interaction between gHSA and metformin in Δλ = 60 and 15 nm, respectively According to Figure 4(B) and its inset, the maximum emission wavelength of Tyr of gHSA was slightly blue shifted, whereas that of Trp demonstrated a significant blue shift. This was another indication that the polarity around the Trp and Tyr residues had been lowered. It can furthermore be seen in the inset of Figure 4(A) and (B) that the Tyr fluorescence emission decreased. However, no significant change in its emission maximum wavelength was observed, which indicates that the interaction of the drug with HSA vs. gHSA did not affect the microenvironment of the Tyr residues. Therefore, the formation of the HSA–metformin and gHSA–metformin complexes caused conformational changes of HSA of varying grades. To explore these structural change of proteins induced by the addition of the drug, measurements were made of curves of F/F0 vs. [Q] with various amounts of drug at Δλ = 60 and Δλ = 15 nm for HSA– and gHSA–metformin (Figure 4(C) and its inset, respectively). As can be seen in Figure 4(C) and its inset that the pitch of quenching at Δλ = 60 nm is higher than that Δλ = 15 nm, which suggests that the main contribution to the fluorescence quenching in the interaction between metformin with HSA and gHSA was related to the Trp residue. During the binding process of metformin to HSA and gHSA, the drug affected the microenvironment of the Trp residue (Wang, Liu et al., 2010; Zhang et al., 2010). 3.5. REES REES is a shift in the wavelength of maximum fluorescence emission toward higher wavelengths, caused by a

movement of the excitation wavelength toward the red edge of the absorption band (Demchenko, 2002). REES relies on slow solvent reorientation in the excited state of a fluorophore that can be used to monitor the environment and dynamics around a fluorophore in a host assembly. Thus, REES is particularly useful in monitoring motions around the Trp residues in protein studies and also compare the environment and mobility features of Trp residue in different species (Zhang, Wang, & Jiang, 2009). In our studies, we excited Trp at both 295 and 305 nm to investigate the REES effect, and the results are listed in Tables 3 and 4. The value of Δλem, max was defined as the difference of the emission maximum between that excited at 295 and 305 nm (Rao & Rao, 1994). As can be seen, native HSA and gHSA presented a 9 nm REES, which indicates that the Trp residue in HSA and gHSA was in an environment where its movement was slightly restricted. According to the amount of equal Δλem, max HSA and gHSA, the REES values were investigated in three molar ratios (1:1, 1:5, 1:10) in the presence of metformin. A constant value of Δλem, max was clearly indicates that metformin had no obvious effect on the mobility of the Trp microenvironment, in other word; the Trp environment in both cases appeared to be less polar. Also, the restricted mobility around the Trp residue in HSA– and gHSA–metformin systems can be compared by the magnitude of REES, so it was suggested that Trp microenvironment has the same condition in both systems. 3.6. RLS spectra RLS spectra were obtained by simultaneously scanning the excitation and emission wavelengths through a monochromator of a common spectrofluorometer with Δλ = 0 nm (Chen, Zhu, Song, Chen, & Guo, 2009; Gao et al., 2007). Due to the simplicity, sensitivity, and rapidity of the RLS technique, it is also extensively applied for the studies of proteins, in which case the RLS technique is mostly based on the enhancement of the RLS intensity, which attributes to the new complex formation between RLS probes and proteins (Wu et al., 2009). As a new spectral analysis technique, light-scattering measurements with a common spectrofluorometer are very simple, and sensitive. The technique is generally coupled to other spectral analysis methods such as

10

E. Rahnama et al. 2000 Fluorescence Intensity

(A) 12000 10000 Fluorescence Intensity

0 mM 1600 0.17 mM 1200 800 400 0 220

0mM

250

280

310

Wavelength / nm

8000

0.17mM

6000 4000 2000 0 220

250

280 Wavelength / nm

310

(B)


0 mM

6000


0.17 mM

800

400

0 mM

0 220

250

4000

280

310

Wavelength / nm

0.17 mM

2000

0 220

250

280 Wavelength / nm

310 1.2 1

F / F0

0.8 0.6 0.4

(C)

0.2

1.2

0 0

0.04

1

0.08

0.12

0.16

0.2

[Q] / mM

0.8

F / F0


1200

0.6 0.4 0.2 0

0

0.04

0.08 0.12 [Q] / mM

0.16

0.2

Figure 4. (A) Original synchronous fluorescence spectra of HSA in the presence of metformin at Δλ = 60 nm. The inset indicates synchronous fluorescence spectra of HSA–metformin at Δλ = 15 nm. (B) Synchronous fluorescence spectra of the gHSA–metformin system at Δλ = 60 nm. The inset shows synchronous fluorescence spectra of gHSA–metformin at Δλ = 15 nm. (C) The quenching of the synchronous fluorescence of HSA by the drug at Δλ = 60 (●) and Δλ = 15 (○) nm. The inset shows the quenching of the synchronous fluorescence of gHSA–metformin at Δλ = 60 (■) and Δλ = 15 (◊) nm. [HSA] = 4.5 × 10−3 mM, [gHSA] = 4.5 × 10−3 mM, [metformin] = 0.17 mM, pH = 7.4, and T = 298 K.

Interaction between Metformin with HSA and gHSA Table 3.

Red edge excitation effects for the HSA and HSA–metformin systems.

Sample

Ratio

λex: 295 nm λem max (nm)


Δλem max (nm)

HSA HSA–metformin HSA–metformin HSA–metformin

1:1 1:5 1:10

300 300 300 300

309 309 309 308

9 9 9 8

Table 4.


11

Red edge excitation effects for the gHSA and gHSA–metformin systems.

Sample

Ratio


λex : 305 nm λem max (nm)

Δλem max (nm)

gHSA gHSA–metformin gHSA–metformin gHSA–metformin

1:1 1:5 1:10

300 300 300 300

309 309 309 309

9 9 9 9

absorption, fluorescence, and CD, and can compensate for the drawbacks of spectrophotometric and fluorometric measurements (Li, Ren et al., 2008). The results are shown in Figure 5. It can be seen that, under the experimental conditions, the RLS intensities for the pure protein were very weak, on the other hand, the RLS intensity of protein become remarkably enhanced with the addition of amount of metformin to the HSA solution. As we can see in Figure 5 there were two maximum scattering peaks at about 260 and 310 nm in the HSA–metformin. Since the enhancement of RLS is consistently associated with aggregation and is sensitive to the electronic mechanism of the drugs over the HSA surface can be reasonably established (Cui, Wang, & Cui, 2007). Moreover, as we know, when other factors are held constant, the increase of molecular volume and hydrophobicity, resonance energy transfer between absorption and scattering, as well as drug binding conformational changes contribute to the RLS enhancement. It was thus concluded that an interaction had occurred between HSA and metformin, and formation complex between HSA and metformin and increase in particle size in the protein solution (Yang et al., 2008). Consequently, the increase in the concentration of the drug– protein complex leads to the intensity enhancement of the RLS spectra. Another possible reason for the RLS enhancement was an effect of polarizability on the scattering intensity. A large increase in polarizability is thus one of the important factors for the enhancement of RLS and the formation of complexes (Sarzehi & Chamani, 2010). Polarizability values for metformin, HSA, gHSA, and complexes of HSA– and gHSA–metformin can be found in Table 5. Results showed that the polarizability of the complexes was higher than metformin, HSA, and gHSA. Thus, the remarkable increase of the mean polarizability

after the reaction was a significant reason for the enhancement of RLS. The effect of the metformin concentration on the RLS intensity was studied for the HSA–metformin and gHSA–metformin systems and the results are shown in inset Figure 5. According to inset Figure 5, the ΔIRLS values, represented as ΔIRLS = IRLS − I0RLS (which IRLS and I0RLS are the RLS intensities of the systems in the presence and absence of ligand, respectively) were enhanced when increasing the metformin concentration (Long, Zhang, Cheng, & Bi, 2008). It can be seen that there existed a nonliner relationship between the RLS intensity and the metformin concentration. The ΔIRLS of both systems increased with the metformin concentration, which is indicative of complex formation. In addition, when the metformin concentration reached to 1.74 × 10−2 mM, the RLS intensity increase because of the complex formation and also due to metformin aggregating on the HSA was occurred. This value thus corresponded to the critical induced aggregation concentration (CCIAC) of the drug (indicated by an arrow in the figures) and also the value of CCIAC for gHSA was about 1.24 × 10−2 mM and was a main reason for the increase in RLS intensity (Abdollahpour, Asoodeh, Saberi, & Chamani, 2011). Our results reveal that the estimated CCIAC for the HSA–metformin system was greater than for the gHSA–metformin system, which is evidence of the gHSA aggregation being induced at lower concentrations of metformin. 3.7. Zeta potential measurement The zeta potential is a function of the surface charge that is generated when any material is placed in a liquid. It is a very good index of the magnitude of the electrostatic repulsive interaction between particles. The zeta potential

12

E. Rahnama et al.

ΔI RLS

600

2400

400

200

0.17 mM 0

1800

0

0.04

I RLS Downloaded by [Nipissing University] at 19:40 18 October 2014

0.08

0.12

[Q] / mM

0 mM 1200

600

0 220

320

420 Wavelength / nm

520

Figure 5. RLS spectra of HSA and gHSA in the presence of a variety of concentrations of metformin. The inset shows curves of ΔIRLS vs. [Q] for the HSA–metformin (○) and gHSA–metformin (●) systems. Conditions: T = 298 K, pH = 7.4, [HSA] = 4.5 × 10−3 mM, [gHSA] = 4.5 × 10−3 mM, [metformin] = 0.17 mM. Table 5. Calculated polarizability effects of metformin and protein on the scattering intensity. System HSA gHSA Metformin HSA–metformin gHSA–metformin

Polarizability/a.u. 281.23 309.42 66.07 313.3 341.49

is commonly used to predict and control dispersion stability; it is determined by measuring the electrophoretic particle velocity in an electrical field (Prieto, Sabin, Ruso, González-Pérez, & Sarmiento, 2004). In solution, the presence of a net charge on a particle affects the distribution of the ions surrounding it, resulting in an increase of the concentration of counterions. The region over which this influence extends is called the electrical double layer. Conventionally, this layer is thought of as existing as two separate regions: an inner region of strongly bound ions known as the Stern layer, and an outer layer of loosely associated ions called the diffuse layer. As the particle moves through the solution, the ions move with it due to gravity or an applied voltage. At a certain distance from the particle, there exists a “boundary” beyond which the ions do not move with the

particle. This is known as the surface of hydrodynamic shear, or the slipping plane, and exists somewhere within the diffuse layer. The potential at the slipping plane is defined as the zeta potential (Cai et al., 2006). The zeta potential, unlike the particle size or molecular weight, is a property involving not only the particles but also their environments, e.g. pH, ionic strength, and even the type of ions in the suspension. Binding is determined by measuring the partition coefficients and the changes in drug-induced zeta potential of HSA. Negative surface charges facilitate drug binding and drug protonation in the protein surface, whereas positive surface charges prevent protonation of the drugs (Malhotra & Coupland, 2004). In order to confirm the existence of drug binding and drug aggregation on proteins, zeta potential measurements were carried out at physiological pH. Figure 6 illustrates a plot of the zeta potential for the HSA–metformin and gHSA–metformin complexes as function of drug concentration. It can be seen that pure HSA and gHSA molecules in the absence of the drug showed zeta potential values of about 5.5 and −7.87 mV, respectively. These negative values of zeta potential represent that hydrophobic force is predominant in the initial interaction between metformin with HSA and gHSA, also protein–metformin complexes are made up (Malhotra &

Interaction between Metformin with HSA and gHSA 0 -2.5

Zeta Potential

-5 -7.5 -10 -12.5 -15 -17.5


-20

0

0.04

0.08 0.12 [Q] / mM

0.16

0.2

Figure 6. Dependence of the zeta potential of HSA on the drug concentration. HSA–metformin (□), gHSA–metformin (■). [HSA] = 4.5 × 10−3 mM, [gHSA] = 4.5 × 10−3 mM, [metformin] = 0.17 mM, T = 298 K and pH = 7.4. The zeta potential values reported are based on mV.

Coupland, 2004). Figure 6 displays that there is an initial decrease in the zeta potential, which tends to a final plateau, this point is related to the critical induced aggregation concentration (CCIAC) of metformin (show by an arrow in the figure) (Prieto et al., 2004). The CCIAC point demonstrates that the surface of HSA and gHSA are full and metformin aggregation is occurred. As can be seen in Figure 6 the CCIAC point for gHSA–metformin complex took place at low drug concentration as compare to HSA–metformin complex, which imply that glycation leads to reduce HSA resistance against the drug aggregation on the protein surface. This information can be useful in determining drug dosage. In addition, in the presence of high metformin concentration, there is a reversal in the zeta potential curves, corresponding values increased, which express that after the CCIAC point electrostatic force plays a main role in formation of the metformin–protein complex (Malhotra & Coupland, 2004; Prieto et al., 2004). Consequently, interaction between metformin with HSA and gHSA occurred due to the presence of both electrostatic and hydrophobic interactions. These results confirm obtained results from RLS technique. 3.8. Fluorescence anisotropy Fluorescence polarization is a powerful and sensitive technique for the study of molecular interactions in solution. It is based on the observation of the molecular movement of the fluorescent molecules in solution and does not require physical separation of the excess ligand or acceptor. Anisotropy is directly related to the polarization, and is the ratio of the polarized light component to the total light intensity (Li, He, Dong, Sheng, & Hu,

13

2006). A series of study methods concerning the interaction between drugs and protein are often monitored using optical techniques as these approaches are sensitive and relatively easy to use. Among them, the fluorescence anisotropy is found to be intrinsically high and sensitive to relevant environmental changes (Anderson, Niesen, Blanch, & Prausnitz, 2000). Changes in the association state of molecules are reflected by modifications in molecular motion, and fluorescence anisotropy measurements are useful for investigating these changes. Fluorescence anisotropy is measured by first exciting a molecule with vertically polarized light, then observing the fluorescence intensity of emitted light passing through a polarizer held alternately parallel and perpendicular to the direction of polarization of the incident light (Barbero et al., 2009). Anisotropy measurements are based on the molecular motion of fluorescent molecules in solution in the time frame occurring between absorption and emission of light. According to Equation (8), the most common way to determine fluorescence anisotropy (r) values is according to: r ¼ ðIVV G IVHÞ =ðIVV þ 2 G IVHÞ

(8)

IVV is obtained when the excitation and emission polarizers are mounted vertically, and IVH requires a vertical excitation polarizer and a horizontal emission polarizer. G is a correction factor that detects the instrumental sensitivity of the polarization direction of emission. G is defined as: G ¼ IHV =IHH

(9)

where IHV and IHH represent, respectively, the vertically and horizontally polarized emission intensities obtained by excitation with horizontally polarized light (Sanz-Vicente, Castillo, & Galban, 2005). Molecules in solution rotate and tumble. In the case of small molecules, the movement is very rapid, but the movement of larger molecules becomes slower. When fluorescent-labeled small molecules in solution are excited with plane-polarized light, the emitted light is depolarized due to a fast movement of the molecule. However, when the fast-moving small fluorescent-labeled molecule is bound to a receptor having a large molecular mass, the movement of the conjugate is restricted and becomes slow. When such a conjugate is irradiated with polarized light, the emitted light obviously remains polarized (Sanz-Vicente et al., 2005). The interaction between metformin with HSA and gHSA was studied by fluorescence anisotropy and is shown in Figure 7. The concentration of metformin was kept constant, whereas the concentrations of HSA and gHSA were varied. In the absence of proteins, the fluorescence emission is not observed for the metformin, just after the addition of proteins into the drug solution

14

E. Rahnama et al. metformin with native HSA as compare to glycated HSA (Li et al., 2006). In other words, changes in protein structure lead to different interaction behavior and decrease binding affinity between drugs and proteins (Yue et al., 2009). In order to support recent results the dissociation constant values (Kd), which is inversely related to the binding constant (Ka) (Sanz-Vicente et al., 2005), calculated from the slope of anisotropy curves and were 0.05 and 0.9 for HSA–metformin and gHSA– metformin complex, respectively. This confirmed the obtained results of Figure 7.

1 0.9 0.8 0.7

r

0.6 0.5 0.4 0.3 0.2 0.1

0

0.002

0.004

0.006 0.008 [protein]/mM

0.01

0.012

0.014

3.9. CD and conformational analysis CD spectroscopy plays an important role in the study of protein folding as it allows the characterization of secondary and tertiary structures of proteins in native, unfolded, and partially folded states (Katrahalli, Jaldappagari, & Kalanur, 2010). It is known that ligand binding to a globular protein can alter the secondary structure, resulting in changes in the protein conformation, which are reflected by the CD spectrum (Bourassa et al., 2011). In order to better understand the conformational changes of HSA and gHSA upon the addition of metformin, the CD technique was applied to HSA and gHSA in the presence and absence of metformin. Figure 8

Figure 7. Fluorescence anisotropy (r) of the HSA–metformin (△) and gHSA–metformin (□) systems. [HSA] = 0.45 × 10−3 mM, [gHSA] = 0.45 × 10−3 mM, [metformin] = 0.001 mM, T = 298 K, and pH = 7.4.

exhibits anisotropy fluorescence. The plot shows that the anisotropy of metformin increased with larger concentrations of HSA and gHSA, which demonstrates that protein–metformin complexes are formed. The value of anisotropy for HSA–metformin is greater than gHSA– metformin complex, thus there is more affinity between

10

CD / mdeg

0

50

0.17 mM

-10 0 mM

-20 -30

100 0.17 mM

-40 200

210

220

230

240

Wavelength / nm 0

CD / mdeg


0

-50

0 mM

-100 -150 -200

200

210

220 Wavelength / nm

230

240

Figure 8. Far-UV CD spectra of native HSA and gHSA in the presence of various concentrations of metformin. [HSA] = 0.45 × 10−3 mM, [gHSA] = 0.45 × 10−3 mM, [metformin] = 0.17 mM, T = 298 K and pH = 7.4.



Table 6.

15

Secondary structural analysis of the HSA–metformin and gHSA–metformin systems from CD data.

System

α-helix (%)

β-sheet (%)

Turn (%)

Unordered coil (%)

HSA HSA–metformin gHSA gHSA–metformin

53.84 ± 0.12 50.25 ± 0.10 48.19 ± 0.14 45.47 ± 0.12

18.36 ± 0.12 19.33 ± 0.10 18.27 ± 0.14 17.08 ± 0.12

13.55 ± 0.12 13.47 ± 0.10 12.62 ± 0.14 11.59 ± 0.12

14.25 ± 0.12 16.95 ± 0.10 20.92 ± 0.14 25.86 ± 0.12

displays the CD spectra of HSA, HSA–metformin, gHSA, and gHSA–metformin. The secondary structure contents for both systems are presented in Table 6. According to Figure 8, the CD spectra of HSA and gHSA exhibit two negative bands at 208 and 222 nm, characteristic of the α-helical structure. A reasonable explanation is that the negative peaks at 208 and 222 nm were both contributed to by n→π transition for the peptide bond of α-helix (Tang et al., 2006). As can be seen from Table 6, the calculated results showed a decrease in the α-helix content that both systems with enhancement of metformin concentration, whereas the α-helical content of gHSA in the absence of drug was lower than for HSA. This is explained as the glycation causing the secondary structural change of HSA. However, the increase in unordered coil content indicated a decreased in secondary structure of the protein in addition to a decrease in protein function. Table 6 lists the fractions of α-helix, β-sheet, turn and unordered coil, and as can be seen, the native HSA comprised 53.84% α-helix, 18.36% β-sheet, 13.55% turn, and 14.25% unordered coil. The results in Table 6 and Figure 8 show that the percentage of α-helix decreased, upon metformin binding, indicating a certain degree of destabilization. Similar results were observed for the gHSA–metformin complex. When it comes to the βsheet content in the HSA–metformin system, it was found to increase whereas it decreased in the gHSA–metformin complex. In both systems, the content of unordered coil increased. From the above results, it was apparent that the binding of metformin to HSA and gHSA caused a conformational change of the protein, with a loss of helicity. Combined decrease of helicity and increase of unordered coil regions, may signify the decrease in protein stability. Therefore, the interaction between metformin with HSA and gHSA caused changes of the secondary structure content.

3.10. Energy transfer from HSA and gHSA to the drug The efficiency of energy transfer in biochemistry can be used to evaluate the distance between the ligands and the fluorophores in the protein (Naveenraj, Anandan, Kathiravan, Renganathan, & Ashokkumar, 2010). According to FRET, the transfer of energy that occurs through direct electrodynamic interaction between the

primarily excited molecules and their neighbors is controlled by the following three aspects: (1) the donor should have a strong fluorescence quantum yield, (2) there should be more spectral overlap between the donor emission and the acceptor absorption, and (3) the distance (r) between the acceptor and the donor should be within 7 nm (Ge et al., 2010). The efficiency of energy transfer (E) is related to the distance (R) between the donor and acceptor. E could be calculated using the equation: E ¼ 1 ðF0 =FÞ ¼ R60 =ðR60 þ r6 Þ

(10)

where F0 and F are the fluorescence intensities without and with drug, respectively, r is the distance between acceptor and donor, and R0 is the critical distance when the transfer efficiency is 50%, R60 ¼ 8:79 1025 K 2 n4 UJ

(11)

2

Here, (K ) is the spatial orientation factor between the emission dipole of the donor and the absorption dipole of the acceptor, n is the average refractive index of the medium, Φ is the fluorescence quantum yield of the donor, and J is the overlap integral of the fluorescence emission spectrum of the donor and the absorption spectrum of the receptor (J can be calculated by the equation). J ¼ ðFðkÞeðkÞk4 DkÞ=ðFðkÞDkÞ

(12)

where F(λ) is the fluorescence intensity of the donor in the wavelength range λ to λ + dλ, and ɛ(λ) is the molar absorption coefficient of the acceptor at λ (Yu et al., 2010). The overlap of the fluorescence emission spectra of HSA and gHSA with the UV absorption spectra of metformin are shown in Figure 9(A) and (B), respectively. In this study, r values were obtained for HSA– metformin and gHSA–metformin according to Equations (8)–(10). When determining the energy transfer between HSA and metformin, r = 2.38 nm was obtained. This value also was calculated for the gHSA–metformin system and was 1.91 nm. The distance between metformin and both HSA and gHSA was less than 7 nm which this proved that the energy transfer from HSA and gHSA to metformin could occur with a high probability (Ge et al., 2010). Nevertheless, the smaller distance between gHSA and metformin as compared with HSA implies that a more stable complex was formed between gHSA and

E. Rahnama et al.

(A) 0.2

2500

2000

a

1500 0.1 1000 b

0.05

0 320

500

340

360

380

400

0 420

Wavelength / nm 2500

1500 a

0.1

1000 b 0.05

0 320

Fluorescence intensity

2000

0.15

Absorbance

(A) 1.2 1

500

340

360 380 Wavelength / nm

400

0.8

0 420

Figure 9. (A) The spectral overlap of the fluorescence emission spectrum of HSA (curve a) with the absorption spectrum of metformin (curve b) Cdrug/CHSA = 1:1. (B) The spectral overlap of the fluorescence emission spectrum of gHSA (curve a) with the absorption spectrum of metformin (curve b) Cdrug/CgHSA = 1:1.

0.6 0.4 0.2 0

0

0.05

0.1

0.15

0.2

[Q] / mM

metformin. In agreement with Förster’s theory, these results confirmed the existence of static quenching between drug and the protein.

(B) 1.2 1

0.8

3.11. Binding site allocation of metformin on HSA and gHSA It is accepted that drugs preferentially bind to separate and specific binding domains on albumin. The first binding region is known as the warfarin binding site, also called Site I, and is believed to involve the amino acid residues Trp214 and Lys199. A second region is the ibuprofen binding site, also called Site II, which is believed to be made up of the following amino acids: Tyr411, Phe403, Lys414, and Arg410. Drugs known to bind to the above-mentioned sites can be used as displacers for competitive binding studies (Ding, Liu, Zhang, Yin, & Sun, 2010; Ghuman et al., 2005; Saquib et al., 2010). Thus, to obtain more information on the binding of metformin to HSA and gHSA, binding studies were carried out in

F / F0


(B) 0.2

the presence of warfarin and ibuprofen under otherwise identical conditions. Figure 10(A) shows plots of the relative fluorescence intensity against the ligand concentration plots for HSA–metformin and HSA–warfarin complexes. Both metformin and warfarin quenched the HSA fluorescence, but the extent of quenching by warfarin was much more significant as compared to that by metformin. On the other hand, Figure 10(A) presents the enhancement of metformin in a solution of HSA and warfarin of equimolar concentration. By comparing the curves in Figure 10(A), we find that the quenching curve of HSA–metformin in the absence and presence of warfarin almost are similar, therefore probably metformin and warfarin will not occupy the same binding sites on HSA and there is no competitive relationship between drugs. In other words, warfarin and metformin bound independently to HSA and metformin probably not bound within the subdomain IIA (Sudlow’s site I) (Ding et al., 2010).

F / F0

Absorption

0.15


16

0.6

0.4

0.2

0

0

0.04

0.08

0.12

0.16

0.2

[Q] / mM

Figure 10. Fluorescence quenching profiles of (A) HSA–metformin (ο); HSA–warfarin (⋄); and HSA–warfarin mixture in the presence of metformin (•); (B) HSA–metformin (ο); HSA– Ibuprofen (▲), and HSA–Ibuprofen complex in the presence of metformin (Δ). T = 298 K, pH = 7.4 and λex = 280 nm.

17



Figure 11. (A) Docking interaction of metformin with HSA. The distance between the Trp 214 of HSA with metformin is portrayed with a dashed line. (B) Computational model of the docking: the distance between Trp of gHSA with metformin is represented by solid line.


18

E. Rahnama et al.

Figure 10(B) shows a comparison of the relative fluorescence intensity (F/F0) vs. the ligand concentration of the HSA–metformin system in the absence and presence of ibuprofen. In this work, in the presence of ibuprofen, the fluorescence property of the HSA–metformin system differed as opposed to in the absence of ibuprofen, which indicated that ibuprofen prevented the binding of metformin in its usual binding location and also drugs located in same binding sites (site II) on HSA (Saquib et al., 2010). In order to facilitate the comparison of the influence of warfarin and ibuprofen on the binding of metformin to HSA, the binding constants with the presence of site markers were evaluated from the fluorescence data (Ghuman et al., 2005). The Ka value for HSA–metformin complex in the presence of site markers found to be 4.02 × 104 M−1 for warfarin and 9.8 × 103 M−1 for ibuprofen (for HSA–metformin Ka = 4.32 × 104 M−1). Apparently, the binding constant was remarkably decreased after the addition of ibuprofen, while the addition of warfarin caused only a small difference. These results demonstrated that metformin bound with a high affinity to subdomain IIIA on HSA. The same experiments with sites markers were also carried out for the gHSA–metformin complex (curves are not shown). The binding constants in the presence of site markers were found to be 1.68 × 104 M−1 for warfarin and 1.12 × 104 M−1 for ibuprofen (for gHSA–metformin Ka = 1.77 × 104 M−1). These results demonstrated that metformin bound with a high affinity to Site II (subdomain IIIA) of gHSA. Therefore, glycation does not lead to alter the binding site of metformin on HSA.

3.12. Molecular modeling Molecular modeling is a method that has been employed to promote the understanding of the interaction of drugs and HSA (Jiaxin et al., 2011). Crystal structure analysis has revealed that has consists of a single polypeptide chain of 585 amino acid residues and comprises three structurally homologous domains (I–III): I (residues 1–195), II (196–383), and III (384–585). These domains assemble to form a heart-shaped molecule (Tang, Lian, He, & Zhang, 2008; Wang et al., 2008). The best docking results of the interaction between metformin with proteins are shown in Figure 11(A) and (B). According to Figure 11(A) and (B) metformin was located in subdomain IIIA (Sudlow’s site II) on HSA and gHSA, respectively. We should mention that despite the presence of two binding sites in HSA vs. only one in gHSA (possibly because glycosylation disables the second site), we investigated only one of them in IIIA subdomain, present in both proteins. Molecular modeling results obviously confirm the obtained result from site marker experiments. In order to corroborate the FRET

result, the distances between Trp214 (in subdomain IIA) and metformin (r) on HSA and gHSA were calculated and are shown in Figure 11(A) and (B). The reordered distances (r) were 2.4 and 1.6 nm for HSA–metformin and gHSA–metformin complex, respectively. These results are in good agreement with results from FRET which reported that the corresponding distances were 2.38 and 1.91 nm for HSA–metformin and gHSA–metformin complex, respectively. The distance between Trp214 and metformin in gHSA–metformin was shorter than in the HSA–metformin complex. Therefore, glycation affected the protein causing a change in the site where the drug bound. Molecular modeling thus confirmed the results of the fluorescence spectroscopy. 4. Conclusions In this work, binding interaction of metformin with HSA and gHSA has been studied and compared in vitro under a simulated physiological condition (T = 298 K and pH = 7.4) by different spectroscopic methods and molecular modeling. The steady state, time-resolved fluorescence spectroscopy, and also polarizability data indicated the creation of a complex between metformin with HSA and gHSA through a static mechanism. The CD results revealed the occurrence of secondary structural changes in HSA and gHSA in the presence of metformin and result in a slight decrease in α-helical content. The microenvironment around both proteins also became more hydrophobic according to synchronous fluorescence data. The value of binding constant, number of binding site from fluorescence analysis, and also anisotropy spectroscopy displayed that there was more affinity between metformin with HSA than gHSA. The RLS and zeta potential measurements represented the structural changes in HSA reduced its resistance against the drug aggregation (CCIAC of HSA–metformin >CCIAC of gHSA–metformin). Moreover, it was found that both hydrophobic and electrostatic interactions played important role in inducing aggregation of the drug on the protein, as determined by the zeta potential technique. The distances (r) between the drug and the Trp214 residue of proteins were evaluated according to Förster’s theory of energy transfer and molecular modeling and both methods confirmed drug–protein complex formation. By using site marker competitive experiments and molecular modeling, it was possible to locate the exact binding site of the drug to the proteins, which clarified metformin was located at subdomain IIIA on HSA and gHSA, respectively. This binding study of metformin with HSA and gHSA is of great importance in pharmacy, pharmacology, and biochemistry, as the obtained results will help us to determine drug dosages.

Interaction between Metformin with HSA and gHSA Acknowledgments The financial support of the Research Council of the Islamic Azad University-Mashhad Branch is gratefully acknowledged. The authors thank Dr Ljungberg for the English editing.


References Abdollahpour, N., Asoodeh, A., Saberi, M. R., & Chamani, J. (2011). Separate and simultaneous binding effects of aspirin and amlodipine to human serum albumin based on fluorescence spectroscopic and molecular modeling characterizations: A mechanistic insight for determining usage drugs doses. Journal of Luminescence, 131, 1885– 1899. Anderson, C. O., Niesen, J. F. M., Blanch, H. W., & Prausnitz, J. M. (2000). Interactions of proteins in aqueous electrolyte solutions from fluorescence anisotropy and circulardichroism measurements. Biophysical Chemistry, 84, 177–188. Barbero, N., Napione, L., Quagliotto, P., Pavan, S., Barolo, C., Barni, E., … Viscardi, G. (2009). Fluorescence anisotropy analysis of protein–antibody interaction. Dyes and Pigments, 83, 225–229. Barnaby, O. S., Cerny, R. L., Clarke, W., & Hage, D. S. (2011). Comparison of modification sites formed on human serum albumin at various stages of glycation. Clinica Chimica Acta, 412, 277–285. Bourassa, P., Dubeau, S., Maharvi, G. M., Fauq, A. H., Thomas, T. J., & Tajmir-Riahi, H. A. (2011). Binding of antitumor tamoxifen and its metabolites 4-hydroxytamoxifen and endoxifen to human serum albumin. Biochimie, 93, 1089–1101. Cai, K., Frant, M., Bossert, J., Hildebrand, G., Liefeith, K., & Jandt, K. D. (2006). Surface functionalized titanium thin films: Zeta-potential, protein adsorption and cell proliferation. Colloids and Surfaces B: Biointerfaces, 50, 1–8. Chamani, J., Asoodeh, A., Homayoni-Tabrizi, M., Amiri Tehranizadeh, Z., Baratian, A., Saberi, M. R., & Gharanfoli, M. (2010). Spectroscopic and nano-molecular modeling investigation on the binary and ternary bindings of colchicine and lomefloxacin to human serum albumin with the viewpoint of multi-drug therapy. Journal of Luminescence, 130, 2476–2486. Chen, Y. H., Yang, J. T., & Martinez, H. M. (1972). Determination of the secondary structures of proteins by circular dichroism and optical rotatory dispersion. Biochemistry, 11, 4120–4131. Chen, Z., Zhu, L., Song, T., Chen, J., & Guo, Z. (2009). A novel curcumin assay with the metal ion Cu (II) as a simple probe by resonance light scattering technique. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 72, 518–522. Chiou, Y., Tomer, K. B., & Smith, P. C. (1999). Effect of nonenzymatic glycation of albumin and superoxide dismutase by glucuronic acid and suprofen acyl glucuronide on their functions in vitro. Chemico-Biological Interactions, 121, 141–159. Cui, F., Wang, L., & Cui, Y. (2007). Determination of bismuth in pharmaceutical products using methyltriphenylphosphonium bromide as a molecular probe by resonance light scattering technique. Journal of Pharmaceutical and Biomedical Analysis, 43, 1033–1038. Demchenko, A. P. (2002). The red-edge effects: 30 years of exploration. Luminescence, 17, 19–42.

19

Ding, F., Liu, W., Zhang, L., Yin, B., & Sun, Y. (2010). Sulfometuron-methyl binding to human serum albumin: Evidence that sulfometuron-methyl binds at the Sudlow’s site I. Journal of Molecular Structure, 968, 59–66. Gao, D., He, N., Tian, Y., Chen, Y., Zhang, H., & Yu, A. (2007). Determination of bovine serum albumin using resonance light scattering technique with sodium dodecylbenzene sulphonate–cetyltrimethylammonium bromide probe. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 68, 573–577. Garlick, R. L., & Mazer, J. S. (1983). The principal site of nonenzymatic glycosylation of human serum albumin in vivo. The Journal of Biological Chemistry, 258, 6142–6146. Ge, F., Chen, C., Liu, D., Han, B., Xiong, X., & Zhao, S. (2010). Study on the interaction between theasinesin and human serum albumin by fluorescence spectroscopy. Journal of Luminescence, 130, 168–173. Ghuman, J., Zunszain, P. A., Petitpas, I., Bhattacharya, A. A., Otagiri, M., & Curry, S. (2005). Structural basis of the drug-binding specificity of human serum albumin. Journal of Molecular Biology, 353, 38–52. Grisouard, J., Timper, K., Radimerski, T. M., Frey, D. M., Peterli, R., Kola, B., … Herrmann, M. (2010). Mechanisms of metformin action on glucose transport and metabolism in human adipocytes. Biochemical Pharmacology, 80, 1736–1745. Jiaxin, F., Kaiwei, W., Yushu, G., Fenglei, J., Xiaohong, S., Yang, L., & Yi, L. (2011). Biophysical studies of the interaction between a triazole derivative and bovine serum albumin by multi-spectroscopic and molecular modeling methods. Science China Chemistry, 54, 788–796. Joseph, K. S., Anguizola, J., & Hage, D. S. J. (2011). Binding of tolbutamide to glycated human serum albumin. Journal of Pharmaceutical and Biomedical Analysis, 54, 426–432. Katrahalli, U., Jaldappagari, S., & Kalanur, S. S. (2010). Study of the interaction between fluoxetine hydrochloride and bovine serum albumin in the imitated physiological conditions by multi-spectroscopic methods. Journal of Luminescence, 130, 211–216. Lai, E. P. C., & Feng, S. Y. (2006). Solid phase extraction— Non-aqueous capillary electrophoresis for determination of metformin, phenformin and glyburide in human plasma. Journal of Chromatography B, 843, 94–99. Lakowicz, J. R., & Weber, G. (1973). Quenching of fluorescence by oxygen. Probe for structural fluctuations in macromolecules. Biochemistry, 12, 4161–4170. Li, Y., He, W. Y., Dong, Y. M., Sheng, F., & Hu, Z. (2006). Human serum albumin interaction with formononetin studied using fluorescence anisotropy, FT-IR spectroscopy, and molecular modeling methods. Bioorganic & Medicinal Chemistry, 14, 1431–1436. Li, J., Li, M., Li, X., Tang, J., Kang, J., Zhang, H., & Zhang, Y. (2008). Study on the resonance light-scattering spectrum of lysozyme–DNA/CdTe nanoparticles system. Colloids and Surfaces B: Biointerfaces, 67, 79–84. Li, J., Ren, C., Zhang, Y., Liu, X., Yao, X., & Hu, Z. (2008). Human serum albumin interaction with honokiol studied using optical spectroscopy and molecular modeling methods. Journal of Molecular Structure, 881, 90–96. Long, X., Zhang, C., Cheng, J., & Bi, S. (2008). A novel method for study of the aggregation of protein induced by metal ion aluminum(III) using resonance Rayleigh scattering technique. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 69, 71–77.


20

E. Rahnama et al.

Malhotra, A., & Coupland, J. N. (2004). The effect of surfactants on the solubility, zeta potential, and viscosity of soy protein isolates. Food Hydrocolloids, 18, 101–108. Mandal, P., Bardhan, M., & Ganguly, T. (2010). A detailed spectroscopic study on the interaction of rhodamine 6G with human hemoglobin. Journal of Photochemistry and Photobiology B: Biology, 99, 78–86. Matei, I., & Hillebrand, M. (2010). Interaction of kaempferol with human serum albumin: A fluorescence and circular dichroism study. Journal of Pharmaceutical and Biomedical Analysis, 51, 768–773. Mendez, D. L., Jensen, R. A., McElroy, L. A., Pena, J. M., & Esquerra, R. M. (2005). The effect of non-enzymatic glycation on the unfolding of human serum albumin. Archives of Biochemistry and Biophysics, 444, 92–99. Nakajou, K., Watanabe, H., Kragh-Hansen, U., Maruyama, T., & Otagiri, M. (2003). The effect of glycation on the structure, function and biological fate of human serum albumin as revealed by recombinant mutants. Biochimica et Biophysica Acta (BBA) – General Subjects, 1623, 88–97. Naveenraj, S., Anandan, S., Kathiravan, A., Renganathan, R., & Ashokkumar, M. (2010). The interaction of sonochemically synthesized gold nanoparticles with serum albumins. Journal of Pharmaceutical and Biomedical Analysis, 53, 804–810. N’soukpoé-Kossi, C. N., Sedaghat-Herati, R., Ragi, C., Hotchandani, S., & Tajmir-Riahi, H. A. (2007). Retinol and retinoic acid bind human serum albumin: Stability and structural features. International Journal of Biological Macromolecules, 40, 484–490. Pan, X., Liu, R., Qin, P., Wang, L., & Zhao, X. (2010). Spectroscopic studies on the interaction of acid yellow with bovine serum albumin. Journal of Luminescence, 130, 611–617. Prieto, G., Sabin, J., Ruso, J. M., González-Pérez, A., & Sarmiento, F. (2004). A study of the interaction between proteins and fully-fluorinated and fully-hydrogenated surfactants by ζ-potential measurements. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 249, 51–55. Qian, X., Dan-Dan, D., Zhi-Juan, C., Qiong, X., Jian-Ying, L., & Jian-Zhong, L. (2010). Interaction between serum albumin and four flavones by fluorescence spectroscopy and molecular docking. Chinese Journal of Analytical Chemistry, 38, 483–487. Rao, S. C., & Rao, C. M. (1994). Red edge excitation shifts of crystallins and intact lenses. FEBS Letters, 337, 269–273. Roche, M., Rondeau, P., Singh, N. R., Tarnus, E., & Bourdon, E. (2008). The antioxidant properties of serum albumin. FEBS Letters, 582, 1783–1787. Równicka-Zubik, J., Sulkowska, A., Pozycka, J., Gazdzicka, K., Bojko, B., Maciazek-Jurczyk, M., & Sulkowski, W. W. (2009). Fluorescence analysis of sulfasalazine bound to defatted serum albumin in the presence of denaturating factors. Journal of Molecular Structure, 371, 924–926. Sakurai, T., & Tsuchiya, S. (1988). Superoxide production from nonenzymatically glycated protein. FEBS Letters, 236, 406–410. Sanz-Vicente, I., Castillo, J. R., & Galban, J. (2005). Fluorescence anisotropy: Application in quantitative enzymatic determinations. Talanta, 65, 946–953. Saquib, Q., Al-Khedhairy, A. A., Alarifi, S. A., Dwivedi, S., Mustafa, J., & Musarrat, J. (2010). Fungicide methyl thiophanate binding at sub-domain IIA of human serum albumin triggers conformational change and protein damage.

International Journal of Biological Macromolecules, 47, 60–67. Sarzehi, S., & Chamani, J. (2010). Investigation on the interaction between tamoxifen and human holo-transferrin: Determination of the binding mechanism by fluorescence quenching, resonance light scattering and circular dichroism methods. International Journal of Biological Macromolecules, 47, 558–569. Sreerama, N., & Woody, R. W. (2000). Estimation of protein secondary structure from circular dichroism spectra: Comparison of CONTIN, SELCON, and CDSSTR methods with an expanded reference set. Analytical Biochemistry, 287, 252–260. Sulkowska, A., Bojka, B., Rownicka, J., & Sulkowski, W. W. (2006). Competition of drugs to serum albumin in combination therapy. Journal of Molecular Structure, 249, 792– 793. Tang, J., Lian, N., He, X., & Zhang, G. (2008). Investigation of the interaction between sophoricoside and human serum albumin by optical spectroscopy and molecular modeling methods. Journal of Molecular Structure, 889, 408–414. Tang, J., Luan, F., & Chen, X. (2006). Binding analysis of glycyrrhetinic acid to human serum albumin: Fluorescence spectroscopy, FTIR, and molecular modeling. Bioorganic & Medicinal Chemistry, 14, 3210–3217. Tian, J., Liu, J., He, W., Hu, Z., Yao, X., & Chen, X. (2004). Probing the binding of scutellarin to human serum albumin by circular dichroism, fluorescence spectroscopy, FTIR, and molecular modeling method. Biomacromolecules, 5, 1956–1961. Wang, L., Liu, R., Chi, Z., Yang, B., Zhang, P., & Wang, M. (2010). Spectroscopic investigation on the toxic interactions of Ni2+ with bovine hemoglobin. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 76, 155– 160. Wang, T., Xiang, B., Wang, Y., Chen, C., Dong, Y., Fang, H., & Wang, M. (2008). Spectroscopic investigation on the binding of bioactive pyridazinone derivative to human serum albumin and molecular modeling. Colloids and Surfaces B: Biointerfaces, 65, 113–119. Wang, T., Zhao, Z., Wei, B., Zhang, L., & Ji, L. (2010). Spectroscopic investigations on the binding of dibazol to bovine serum albumin. Journal of Molecular Structure, 970, 128– 133. Wu, L., Mu, D., Gao, D., Deng, X., Tian, Y., Zhang, H., & Yu, A. (2009). Determination of protein by resonance light scattering technique using dithiothreitol–sodium dodecylbenzene sulphonate as probe. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 72, 178–181. Yang, H., Wang, Y., Wang, Y., Li, J., Xiao, X., & Tan, X. (2008). Study on the interaction among pyronine Y, potassium bromate and naphthols by absorption, three-dimension fluorescence and resonance light scattering spectra and their application. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 71, 1290–1295. Yu, X., Liu, R., Ji, D., Xie, J., Yang, F., Li, X., … Yi, P. (2010). Spectroscopic studies on the interactions between 3,4-dihydropyrimidin-2(1H)-ones and bovine serum albumin. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 77, 213–218. Yuan, D., Shen, Z. L., Liu, R. T., Wei, P. H., & Gao, C. Z. (2011). Study on the interaction of Nd3+ with human serum albumin at molecular level. Journal of the Chinese Chemical Society, 58, 568–574.



Yue, Y., Chen, X., Qin, J., & Yao, X. (2009). Characterization of the mangiferin-human serum albumin complex by spectroscopic and molecular modeling approaches. Journal of Pharmaceutical and Biomedical Analysis, 49, 753–759. Zhang, Q., Ni, Y., & Kokot, S. J. (2010). Molecular spectroscopic studies on the interaction between ractopamine and

21

bovine serum albumin. Journal of Pharmaceutical and Biomedical Analysis, 52, 280–288. Zhang, H. M., Wang, Y. Q., & Jiang, M. L. (2009). A fluorimetric study of the interaction of C.I. Solvent Red 24 with haemoglobin. Dyes and Pigments, 82, 156–163.

Analysis of binding interaction between antibacterial ciprofloxacin and human serum albumin by spectroscopic techniques.

Binding of helicid to human serum albumin: a hybrid spectroscopic approach and conformational study.

Analysis of glipizide binding to normal and glycated human serum albumin by high-performance affinity chromatography.

Probing the interaction of cefodizime with human serum albumin using multi-spectroscopic and molecular docking techniques.

Detection of interaction between lysionotin and bovine serum albumin using spectroscopic techniques combined with molecular modeling.

Insight into the binding mechanism of imipenem to human serum albumin by spectroscopic and computational approaches.

Interaction of oridonin with human serum albumin by isothermal titration calorimetry and spectroscopic techniques.

Molecular interaction of PCB180 to human serum albumin: insights from spectroscopic and molecular modelling studies.

Chlorpheniramine binding to human serum albumin by fluorescence quenching measurements.

Investigations on the interactions between naphthalimide-based anti-tumor drugs and human serum albumin by spectroscopic and molecular modeling methods.

Investigation of interaction of antibacterial drug sulfamethoxazole with human serum albumin by molecular modeling and multi-spectroscopic method.

Interaction of prometryn to human serum albumin: insights from spectroscopic and molecular docking studies.

Identification of Lys190 as the primary binding site for pyridoxal 5'-phosphate in human serum albumin.

Site-specific cleavage of glycated human serum albumin in the presence of iron.

Analysis of the Interaction of Dp44mT with Human Serum Albumin and Calf Thymus DNA Using Molecular Docking and Spectroscopic Techniques.

Binding modes of environmental endocrine disruptors to human serum albumin: insights from STD-NMR, ITC, spectroscopic and molecular docking studies.

Interactive association of drugs binding to human serum albumin.

Thermodynamic analysis of thymoquinone binding to human serum albumin.

Stereoselective binding of etodolac to human serum albumin.

Photoactivated covalent binding of [3H]bilirubin to human serum albumin.

Binding of porphyrin to human serum albumin. Structure-activity relationships.

The binding of pyridoxal 5'-phosphate to human serum albumin.

Spectrofluorometric and molecular docking studies on the binding of curcumenol and curcumenone to human serum albumin.

Review: modifications of human serum albumin and their binding effect.