Spectrometric study of the interaction between Alpinetin and bovine serum albumin using chemometrics approaches

Analytica Chimica Acta 663 (2010) 139–146

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Spectrometric study of the interaction between Alpinetin and bovine serum albumin using chemometrics approaches Yongnian Ni a,b,∗ , Shuangshuang Wang b , Serge Kokot c a b c

State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China Department of Chemistry, Nanchang University, Nanchang 330047, China School of Physical and Chemical Sciences, Queensland University of Technology, Brisbane 4001, Australia

a r t i c l e

i n f o

Article history: Received 30 October 2009 Received in revised form 26 January 2010 Accepted 27 January 2010 Available online 6 February 2010 Keywords: Alpinetin Bovine serum albumin Fluorescence and UV–visible spectroscopy Chemometrics Ligand comparison

a b s t r a c t The binding interaction of Alpinetin (APT) with bovine serum albumin (BSA) was studied by fluorescence, UV–visible and synchronous fluorescence spectroscopy (SFS) under simulated physiological conditions. The measured complex spectra were resolved by multivariate curve resolution-alternating least squares (MCR-ALS), yielding a host of data and information, which otherwise would have been impossible to obtain. The extracted profiles corresponded to the spectra of the single species in the APT/BSA mixture. In addition, the presence of the APT–BSA complex was demonstrated, and it was shown that the associated quenching of the fluorescence from the BSA protein resulted from the formation of APT–BSA complex via a static mechanism. The binding constant (Ka(ave) = 2.34 × 106 L mol−1 ) and the number of sites (n = 1) were obtained by fluorescence methods as were the thermodynamic parameters (H0 , S0 and G0 ). This work suggested that the principal binding between APT to BSA was facilitated by hydrophobic interactions. The thermodynamic parameters for APT were compared to those from the structurally similar Chrysin and Wogonin molecules. It appeared that the entropy parameters were relatively more affected by the small structural changes. SFS from the interaction of BSA and APT showed that the ligand affected the conformation of BSA. The competitive interaction of APT and site makers with BSA indicated site I as the binding area of APT in BSA. © 2010 Elsevier B.V. All rights reserved.

1. Introduction The interaction between small drug molecules and biomacromolecules is an important phenomenon [1–3]. Among biomacromolecules, serum albumin (SA) is one of the major soluble proteins of the circulatory system. For example, it plays an important role in the transport and deposition of a variety of ligands in blood [4] and contributes in many other ways, which have been described elsewhere [4,5]. Thus, the binding of small molecules, particularly drugs, with bovine serum albumin (BSA) is a typical example of such interactions and is appropriate for investigation, especially, since the structure of BSA is analogous to that of the human serum albumin (HSA) [6,7]. As an example of such processes, natural and synthetic flavonoids have often been found to ‘target’ such proteins [8]. These compounds are derived from a large family of polyphenolic secondary metabolites, and are, generally, natural substances with variable phenolic structures, which have

∗ Corresponding author at: Department of Chemistry, Nanchang University, East Nanjing Road 235, Nanchang 330047, Jiangxi, China. Tel.: +86 791 3969500; fax: +86 791 3969500. E-mail address: [email protected] (Y. Ni). 0003-2670/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.aca.2010.01.053

been grouped according to their molecular structures [9]. They are present as anti-oxidants in many fruits, vegetables and beverages such as tea, red wine, and beer [9,10], and they also have antiviral, antibacterial, antiprotozoal and antifungal properties [11]. One such flavonoid, Alpinetin (APT, 7-hydroxy-5-methoxyflavanone, Table 1), is a traditional Chinese medicine (TCM), which is widely distributed in higher plants and may be extracted from the roots or seeds of such varieties as, e.g., Alpinia katsumadai Hayata, and Amomum alnus. The TCM has many therapeutic applications and has low systemic toxicity [12]. This study set out to examine the effect of APT on the structure of BSA in solution under physiological conditions with the use of UV–visible, fluorescence and synchronous fluorescence spectroscopic (SFS) methods. The binding mechanism of APT to BSA was investigated by studying the binding constants and sites, the thermodynamic properties and the effect of APT on the protein secondary structure. Multiple curve resolution based on alternating least squares (MCR-ALS)—a soft-modeling method, was applied for elucidating the contributions of all species involved in such interactions, their concentration profiles and spectra. This was carried out without the need to postulate a chemical model [13] and the MCR-ALS, is an appropriate approach for the analysis of such multidimensional data matrices because it does not follow a

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Table 1 Structural formulae of Alpinetin, Phenylbutazone, Ibuprofen and other related small drug molecules. Name

Molecular formula

Alpinetin (APT)

C16 H14 O4

Phenylbutazone (PB)

C19 H20 N2 O2

Ibuprofen (IB)

C13 H18 O2

Chrysin

C15 H10 O4

Wogonin

C16 H10 O4

rigorous multilinear model. It uses factor analysis, which has been applied for analyses of spectroscopic and electrochemical data from biomolecular equilibria in solution [14]. When this approach is applied to the analysis of individual data matrices, unresolved, underlying factor analysis ambiguities may arise [15]. However, the MCR-ALS method is able to analyze more than one data matrix simultaneously, especially in the case of mixtures. This significantly reduces the number of possible solutions and hence, ambiguities inherent in the factor analysis. Ni et al. [13] have applied such methods for studying the interactions between berberine chloride and BSA with the use of fluorescence and UV–visible spectroscopy. Two sample series were measured by both techniques: (1) [BSA] was kept constant and [BC] was varied, and (2) [BC] was kept constant and [BSA] was varied, and thus, four spectral data matrices were obtained. They were combined into one expanded spectral matrix, which was processed by the MCR-ALS with satisfactory results. Vives et al. [16] investigated the interaction of ethidium bromide and poly(inosinic)–poly(cytidylic) acids with the use of UV–visible absorption, fluorescence and circular dichroism (CD) spectroscopic techniques. Spectra from all of these techniques were recorded from samples with different polynucleotides: dye concentration ratios, and the whole set of spectroscopic data matrices were simultaneously analyzed by MCR-ALS. This procedure allowed the detection of the polynucleotide/dye intercalation complex, the recovery of the concentration profiles and of the pure spectra for each species as well as the calculation of the polynucleotide: dye ratio in the complex and the apparent equilibrium constant. Kumar et al. [17] studied the folding processes of DNA as monitored by fluorescence resonance energy transfer (FRET). In particular, the folding of a 31-mercytosine-rich DNA segment from the promoter region of the human c-myc oncogene was investigated, and the FRET data from experiment, carried out under different conditions, were individually and simultaneously analyzed by MCR-ALS. Again most of the ambiguities related to factor analysis were removed and

Structural formula

this method of data interpretation indicated the formation of two ordered molecular conformations in acidic and neutral pH media in addition to the disordered structure found at high temperatures. It was suggested that the ordered conformations were related to the cytosine-tetraplex structures showing different degrees of protonation on the cytosine bases. It is clear that the application of chemometrics to extract information from complex measurements of small molecule–SA systems has been relatively infrequent, and thus, the aims of this study were to apply the above noted MCR-ALS method: (i) to resolve the complex, overlapping UV–visible and fluorescence spectra of the APT–BSA system, (ii) to use the extracted spectra to obtain thermodynamic parameters and to compare them with those in the literature for similar small molecular systems, (iii) to use Phenylbutazone (PB) and Ibuprofen (IB) as site makers to identify the binding site of APT on the BSA and (iv) to investigate any effects of APT on conformational changes in the BSA with the use of SFS. 2. Experimental 2.1. Reagents BSA (Mr = 66,000; fatty acid free and electrophoresis grade reagents) was purchased from Shinegene Molecular Biotechnology Co. Ltd. (Shanghai). Stock solution of BSA (1.1 × 10−3 mol L−1 ) was prepared by dissolving 1.668 g BSA in 25 mL sodium chloride solution (50 mmol L−1 ) and stored at 4 ◦ C. Its purity was estimated to be 99% based on the measured absorbance value at 279 nm and compared to the reference value of 0.667 for 1.0 g L−1 pure BSA [18]. All experimental solutions were adjusted with the Tris–HCl buffer ((hydroxy methyl) amino methane-hydrogen chloride), pH 7.4. A stock solution of Alpinetin ((1.7 × 10−3 mol L−1 ) APT; A.R. grade, Research Central of Criterion for Chinese Medicine, Shang-

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hai) was prepared by dissolving the crystals in an appropriate volume of ethanol, followed by further dilution to 25 mL with distilled water. Phenylbutazone (PB, 3.0 × 10−3 mol L−1 , Table 1) and Ibuprofen (IB, 2.0 × 10−4 mol L−1 , Table 1) stock solutions were prepared by dissolving their crystals in distilled water, and diluting to the desired concentration. 2.2. Apparatus All fluorescence spectra were recorded on a Perkin-Elmer LS55 luminescence spectrometer equipped with 1.0 cm quartz cell and a thermostated bath (Model ZC-10, Ningbo Tianheng Instruments Factory, China). Both slit widths for excitation and emission were set at 1.0 cm while the scanning rate was 1500 nm min−1 . The UV–visible spectrum was recorded at room temperature on an Agilent UV-8453 spectrometer equipped with 1.0 cm quartz cell. 2.3. Experimental procedure 2.3.1. Mole-ratio methods with fluorescence and UV–visible detection Fluorescence and UV–visible spectroscopic titrations were carried out at room temperature (25 ± 0.2 ◦ C) in the Tris–HCl buffer. Two separate experiments were carried out with the use of the mole-ratio method: (1) the concentration of BSA was kept constant (1.52 × 10−7 mol L−1 ), and different amounts of APT (range: 0–3.42 × 10−7 mol L−1 ) were added to the solution (21 different solutions made); (2) the concentration of APT was kept constant (2.85 × 10−7 mol L−1 ) and different amounts of BSA were added (range: 0–1.52 × 10−7 mol L−1 , 21 different solutions made). Each solution was allowed to stand for 10 min, and then its UV–visible (250–400 nm) and fluorescence (300–540 nm) spectra (with an excitation wavelength of 280 nm) were collected at every 1 and 0.5 nm, respectively. Thus, four data matrices DBSA (21 × 480), DAPT (21 × 480), DBSA F F UV (21 × 150) APT and DUV (21 × 150) were obtained from these measurements, and column- and row-wise expanded data matrix with two different measurements for the two different experiments was constructed. 2.3.2. Fluorescence quenching experiments The concentration of BSA was kept constant (1.52 × 10−7 mol L−1 ), and different amounts of APT with the concentration range of 0–1.71 × 10−7 mol L−1 were added to the solution; 11 different solutions were prepared. Each sample solution was scanned on the fluorophotometer in the range of 300–540 nm with an excitation wavelength of 280 nm and the fluorescence intensity at 350 nm was detected. The experiments were carried out at four constant temperatures (298, 301, 304 and 307 K). In addition, SFS of BSA in the presence of APT were measured ( = 60 and 15 nm) with the same experimental conditions.

Fig. 1. Arrangement of the data matrices for simultaneous analysis of the UV–visible and fluorescence spectra. These corresponded to different spectroscopic techniques and different experiments. D, C, S and E represent the measured spectra, concentration, spectroscopic species and iterative error data matrices, respectively. Superscripts represent BSA and APT (at constant concentration) and subscripts F and UV indicate the techniques.

data matrix D (NR × NC ) based on the multivariate extension of the Beer’s law: D = CS T + E

(1)

where the columns in the C (NR × NX ) and the rows in ST (NX × NC ) are, respectively, data matrices containing concentration profiles and pure component spectra present in the experiment. E (NR × NC ) contains the matrix of residual noise not explained by the proposed components or conformations in C and ST . NR and NC are the total number of time points studied and wavelengths used of the data set, respectively, and NX is the number of components to be resolved. The four collected data matrices can be combined into an expanded data matrix and resolved into two matrices of pure spectra ST and concentration, C, by ALS-based algorithm (Eq. (1), Fig. 1). This general description can fit a wide range of applications including processes, mixtures, elutions, images and environmental data monitored by multivariate instrumentation [21]. 2.4.2. Initial estimate of the concentration profiles and pure spectra with the use of MCR-ALS Before collecting any spectra, the number of contributions, N, to the experimental response, has to be determined by, e.g., singular value decomposition (SVD) [22], evolving factor analysis (EFA) [23] or SIMPLISMA [24]. Such methods extract the rank of a matrix. With EFA, the computing process is effectively that of the ALS optimization procedure, and is performed in two directions: forwards (in the same direction as the experiment), starting with the two first spectra, and backwards (in the opposite direction of the experiment), i.e. starting with the last two spectra. Thus, the forward process allows the detection of new, emerging contributions, while the backward computation indicates the locations of the disappearing species. The first estimate of the changes in concentrations of the significant components, i.e. their concentration profiles in the interaction, is obtained from the EFA plots. Once the number of species, N, has been extracted, then, the initial concentration profiles and pure spectra of all the contributing species can be established by the MCR-ALS method. Thus, the concentration profiles from EFA were used as the initial estimate for the concentration matrix input in the constrained ALS optimization. The ALS iterative process can be expressed by the two following equations: ST = C +D

2.4. Chemometrics C = D(S T ) 2.4.1. Multivariate curve resolution-alternating least squares (MCR-ALS) MCR-ALS is a commonly used technique to resolve the multi-component mixtures into a simple model consisting of a composition-weighted sum of the signals of the pure compounds [19,20]. Multi-way UV–visible and fluorescence data were analyzed with MCR-ALS to evaluate concentration profiles and pure spectra of chemical components simultaneously present in the system from decomposition of a multivariate multi-component experimental

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(2) +

(3)

The matrix C+ (=(CT C)−1 CT ) and (ST )+ (=S(ST S)−1 ) are the pseudoinverse matrices of C and ST , and are restricted by ST or C greater than or equal to zero, respectively [25]. The spectral matrix, ST , and concentration matrix, C, may be obtained by continuous iteration. Convergence is reached when the relative differences in the standard deviations of the residuals between the experimental and the MCR-ALS reproduced data for two consecutive iterations are less than a preset threshold value, e.g., 0.1%.

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Fig. 2. Fluorescence emission (A) and absorption (C) spectra of BSA (1.52 × 10−7 mol L−1 ) in the presence of different concentrations of APT (1–21): [APT] = 0–3.42 × 10−7 mol L−1 at intervals of 1.71 × 10−8 mol L−1 ; ex = 280 nm; fluorescence emission (B) and absorption (D) spectra of APT (2.85 × 10−7 mol L−1 ) in the presence of different concentrations of APT (1–21); [APT] = 0–1.52 × 10−7 mol L−1 at intervals of 7.6 × 10−9 mol L−1 ; ex = 280 nm.

The quality of the MCR-ALS results is assessed by the lack of fit estimate:



lack of fit (%) = 100 ×

(dij∗ − dij )



2

dij2

(4)

where dij is an element of the experimental matrix, D, and dij∗ is

an element of the reproduced data matrix D* = CST , obtained by the MCR-ALS decomposition. 3. Results and discussion 3.1. Mole-ratio method: analysis of fluorescence and UV–visible spectra BSA fluoresces naturally at 350 nm after excitation at 280 nm, and this fluorescence is due to a tryptophan residue [26]. When small molecules bind with BSA, this fluorescence can be quenched. APT is one such molecule, and thus, its interaction with BSA was studied by monitoring the intrinsic fluorescence intensity changes of BSA after the addition of APT. This kind of spectral quenching is illustrated as a function of concentration of APT in Fig. 2A. In the presence of APT, the BSA fluorescence intensity decreased, and a new APT fluorescence peak developed at about 430 nm as a function of increasing APT concentration. An isoactinic point

formed at 380 nm, which indicated an equilibrium between the free APT and the formed APT–BSA complex (345 nm). Fluorescence spectra of APT in the presence of various concentrations of BSA (Fig. 2B) showed that the APT fluorescence intensity increased slightly, and simultaneously, a new BSA fluorescence peak developed at 350 nm. The shape and position of the two fluorescence peaks did not change to any extent. The UV–visible absorption spectrum of BSA (Fig. 2C) has a peak at about 278 nm whose intensity increased gradually as a function of increasing APT concentration. A new peak developed at about 325 nm, which is the wavelength corresponding to the absorption peak of APT on its addition. A similar situation was observed for APT on addition of BSA (Fig. 2D). The obtained spectral profiles were complex and difficult to interpret, and thus, the MCR-ALS method was applied to extract further information. The number of significant factors, N, which indicated the number of chemical constituents involved in the interaction, was extracted by EFA (Section 2.4.2). Both the UV–visible and fluorescence data showed clearly the presence of only three such factors. The initial estimates of the pure fluorescence and UV–visible spectra (Fig. 3A and B) corresponded to SF and SUV , while the concentration profiles of the analytes extracted by MCR-ALS are shown in Fig. 3C and D. Note that from the results in these two figures, the binding ratio can be estimated for this system at equilibrium ([BSA]:[APT] = 0.5). The cases with

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Fig. 3. Results of the simultaneous analysis of the UV–visible and fluorescence data of the two experiments. Recovered UV–visible (A) and fluorescence (B) spectra (solid line: measured; dashed line: recovered), corresponding to SUV and SF , respectively, from Eq. (2). Recovered concentration profiles for experiment 1(C) and 2(D) in Section 2.3.1, corresponding to CBSA and CBC , respectively, from Eq. (3).

constant cBSA and cAPT (Section 2.3.1) correspond to data matrices CBSA and CAPT , respectively, and it was quite evident that the experimental spectra were very similar to the resolved ones. This supports the EFA results above that there were three chemical components in the system—namely, the free BSA, free APT and the BSA–APT complex. Consequently, the apparent binding constant Kapp [27] may be calculated from the extracted spectral profiles: Kapp =

[BSA − APT] [APT][BSA]

(5)

where [BSA–APT], [APT] and [BSA] are the estimateed concentrations of the free BSA–APT, APT and BSA, respectively. The values of equilibrium constants, Kapp , were obtained at the points where the three species coexisted (Fig. 3C and D), i.e. 2.68 × 105 and 1.63 × 105 L mol−1 , and, the mean values of log Kapp were 5.43 and 5.21, respectively. The estimates of Kapp derived from the two different spectroscopic measurements were very similar both being of the same order magnitude, i.e. 105 . 3.2. Fluorescence quenching study 3.2.1. Binding constant and binding sites As indicated by the results in Section 3.1 above, APT can interact with BSA to form a binary complex, APT–BSA. To obtain the binding constant for the formation of this complex, this reaction was carried out at different temperatures (Section 2.3.2), and the results

were interpreted according to the Stern–Volmer and the associated linear plots (Fig. 4A): F0 = 1 + KSV [Q ] = 1 + Kq 0 [Q ] F

(6)

where Kq , KSV ,  0 and [Q] are the quenching rate constant of the biomolecule, the dynamic quenching constant, the average lifetime of the molecule without the quencher, and the concentration of the quencher, respectively. Generally, Kq = KSV / 0 , and  0 (biopolymer) is taken as 10−8 s [28]. When this is combined with the value of KSV (∼105 ), Kq is found to be in the order of 1013 L mol−1 s−1 . According to the literature [29], for dynamic quenching, the maximum scatter collision-quenching constant of various quenchers with biopolymers is 2.0 × 1010 L mol−1 s−1 and KSV increases with temperature. Thus, the rate constant for BSA quenching procedure initiated by APT was larger than the maximum value of Kq above for the scatter procedure. This observation further indicated that the BSA–APT binding could not be associated with the dynamic fluorescence quenching mechanism but rather with the static one, which originated from the formation of the BSA–APT complex. Therefore, for the static quenching interaction, if it is assumed that there are similar sites in the bio-molecule, the binding constant (Ka ) and the number of sites (n) can be determined according to the following equation [30]: log

F − F  0 F

= log Ka + n log[Q ]

(7)

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Fig. 4. Stern–Volmer plots (A) and linear fitting plots (B) of log[(F0 − F)/F] versus log[APT] for the reaction of BSA and APT at different temperatures. Table 2 Binding constants and thermodynamic parameters for the APT–BSA system at different temperatures. T (K)

n

Ka (106 L mol−1 )

G0 (kJ mol−1 )

H0 (kJ mol−1 )

S0 (J mol−1 K−1 )

298 301 304 307

1.06 1.00 0.92 0.82

2.23 2.32 2.39 2.43

−36.30 −36.84 −37.37 −37.91

16.74

126.0

where Ka is the binding constant of APT with BSA, and n is the number of binding sites per BSA molecule. Thus, Ka and n can be determined from the slope and the intercept of the regression curve (Fig. 4B and Table 2). The correlation coefficients R were satisfactory and the values of n at the experimental temperatures were approximately equal to 1, which indicated that there was one kind of binding site for an APT molecule in BSA. 3.2.2. Binding sites of APT on BSA Similar to HSA, BSA consists of amino acids chains forming a single polypeptide, which contains three homologous ␣-helices in domains (I–III). Each domain is divided into anti-parallel six helix and four sub-domains (A and B). A cluster of two sub-domains with their grooves towards each other forms a domain, and three of such domains make up an albumin molecule [31]. There are two major specific drug-binding sites in serum albumin, sites I and site II, which are located within specialized cavities in sub-domains IIA and IIIA, respectively [32]. Most of the small molecules, which are known to combine with BSA form a complex at site I, and only a few at site II. However, it is difficult to establish the actual site involved from the structure of the small molecule involved. Thus, in this work, two common site markers were used to determine the binding site of APT on BSA. It has been suggested [33] that site I of serum albumin showed affinity for Warfarin (WF) and Phenylbutazone (PB), and site II for Ibuprofen (IB), Fluofenamic acid (FA), among others. In this work, PB and IB were used as the site I and site II markers, respectively. The interaction of PB with the APT–BSA complex was investigated at the excitation wavelength 278 nm (Fig. 5). In the absence of the site marker, PB, the value of the binding constant, Ka , was 2.23 × 106 L mol−1 at 298 K (Table 2, average for four temperatures was 2.34 × 106 L mol−1 ), but when PB was present in the BSA solution, the value of the apparent Ka decreased markedly with the increase in concentration of the site marker. With the increase of the PB concentration, the intrinsic fluorescence of BSA and APT was quenched in both cases. However, the BSA fluorescence intensity decreased marginally while that of APT decreased moderately. This suggests that the binding sites of PB and APT on BSA were sim-

ilar, because in the presence of the three analytes, BSA, APT and PB together, competition for the binding could well be expected. This observation was supported by the estimation of the percent displacement of the site marker [33]: Displacement =

F  2

F1

× 100%

(8)

where F1 and F2 represent the fluorescence intensity of the drug plus BSA at 352 nm in the presence and absence of the site marker, respectively [34]. The result showed that the percent displacement could reach 50% (relative values for F1 and F2 were 443.6 and 229.5, respectively, Fig. 5) when the concentration ratio of PB versus BSA was ∼7.2 (curve 12). This indicated that the binding site of APT on BSA was site I. PB displaced APT from site I on BSA leading to the reduction of the APT fluorescence intensity.

Fig. 5. Fluorescence emission spectra of BSA–APT complex titrated with Phenylbutazone (PB); excitation wavelength: 278 nm. Concentration of BSA and APT were 1:1 (1.52 × 10−7 mol L−1 ) while concentrations of PB were 0, 1.0, 2.0, . . . , 11.0 × 10−7 mol L−1 .

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A fluorescence titration was also carried out in the presence of a site II marker, i.e. IB. No obvious effect on the binding of APT to BSA was observed. The displacement percentage only reached about 10% when the concentration ratio of PB versus BSA was 7.9, which indicated that the two molecules did not readily share a common binding site on the BSA protein. It should be noted that although similar binding constants (∼105 ) were observed for APT and IB with BSA, competition for the site by the ligands was still present, because apart from the binding constant value, the competitive reaction was affected by additional factors, such as the ligand’s affinity and specificity for BSA [35]. 3.2.3. Thermodynamic parameters and nature of the binding forces Generally, small molecules are bound to macromolecules by a combination of forces which may include: hydrogen bonds, van der Waals forces, electrostatic forces, and hydrophobic interactions [36]. The binding studies were carried out at 298, 301, 304 and 307 K and at these temperatures, BSA does not undergo any structural degradation. Assuming that there was no significant change in the enthalpy (H0 ) value over the temperature range, the entropy change (S0 ) and the free energy change (G0 ) of binding can be estimated from the following equations: log Ka =

−H 0 S 0 + 2.303RT 2.303R

G0 = H 0 − TS 0

(9) (10)

where Ka is the binding constant at temperature T and R is gas constant. H0 , S0 and G0 are the standard enthalpy, entropy, and free energy changes, respectively (Table 2). The negative values of G0 (−36.3 to −37.9 kJ mol−1 ) indicated that the binding process was spontaneous and positive enthalpy (H0 = 16.74 kJ mol−1 ) and entropy (S0 = 126.0 J mol−1 K−1 ) values for the interaction of APT with BSA were typical of those associated with hydrophobic interactions [37]. Differences in the structures of small molecules facilitate various modes of binding with BSA by different inter-molecular forces. Recently, Olsson et al. [35] studied the general thermodynamic properties of protein interactions with small molecules, and investigated correlations involving changes in solvation. The database used was the Structure/Calorimetry of Reported Protein Interactions Online, which contained published isothermal titration calorimetry studies and structural information on the interactions between proteins and small ligands. It was shown that most of the interactions were enthalpy driven. Synthetic inhibitors and biolog-

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ical ligands formed two distinct sub-populations in the data, with the former having greater average affinity for BSA due to more favourable entropy changes on binding. This difference between the two groups of ligands apparently resulted from the differences in the burial of polar or apolar surface areas. This finding is supported by previous studies of drug molecules such as the flavonoids, Chrysin [38] and Wogonin [39], which have similar molecular structures to APT (Table 1). The small structural differences occur in positions 5 and 8 of ring A where for APT the substituent is CH3 O– at 5-A; Chrysin has an –OH in this position, and Wogonin has –OH and CH3 O– in 5- and 8-A, respectively. Hydrophobic binding was proposed for the Chrysin–HSA interaction (H0 = 39.19 kJ mol−1 , S0 = 211.91 J mol−1 K−1 ) while for the Wogonin–BSA binding, the thermodynamic parameters (H0 = −12.02 kJ mol−1 , S0 = 58.72 J mol−1 K−1 ) also suggested strong hydrophobic interactions but weak electrostatic forces could not be ruled out. Chrysin–HSA and APT–BSA complexes have thermodynamic values with the same sign, and thus, the same binding forces have been invoked. This suggested that both ligands had similar apolar surface area burials. In the case of the Wogonin–BSA complex, the presence of the two groups on the A ring resulted in a negative H0 value, i.e. the binding reaction is spontaneous. The S0 for Chrysin is positive and relatively high, perhaps because of the presence of only the most polar substituent, OH, in position 5-A; S0 is least favourable when both positions 5- and 8-A are blocked on the Wogonin molecule. Presumably, this contrast in S0 arises because of the differences in the dehydration of the apolar groups upon burial in site I pocket of the BSA. 3.2.4. Study of BSA conformation SFS is a spectroscopic technique [40], which facilitates investigations involving conformational changes in proteins [41]. These may occur during the measurement of fluorescence quenching and may be reflected in the shift of the maximum emission wavelength, max , as a result of the changes in polarity around the microenvironment of a chromophore [36]. It is well-known that the fluorescence of BSA arises from the tyrosine (Tyr), tryptophan (Trp) and phenylalanine (Phen) side-chain residues [42] but the Tyr and Trp are the main chromophores. The difference between excitation and emission wavelengths, , is an important experimental parameter to probe conformational changes. When  is 15 nm, SFS detects characteristics of Tyr residues, but when  is 60 nm, characteristic information from Trp residues is highlighted. Irrespective of the  selected, if there is an accompanying shift in the max , then the fluorescence quenching of BSA implies a change in polarity of

Fig. 6. SF spectra of the interaction between BSA and APT at  = 60 nm (A) and at  = 15 nm (B). Concentration of BSA was 1.52 × 10−7 mol L−1 while concentrations of APT were 0–1.71 × 10−7 mol L−1 .

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the microenvironment around the Tyr or Trp residue as well as a change in the nature of binding of APT to BSA [43]. The SF spectra (Fig. 6) of the interaction between APT and BSA at  = 60 nm (A) and 15 nm (B) showed that the max had red shifted when  = 60 nm (Fig. 6A). Such a red shift effect indicated that the conformation of BSA had changed on addition of APT. It also indicated that the polarity around the Trp residues increased and the hydrophobicity decreased [42]. However, when  was fixed at 15 nm (Fig. 6B), no shift of max was apparent. This suggested that the interaction of BSA with APT did not have a distinct effect on the conformation of the microenvironment around Tyr. Conformational changes were also observed with the Chrysin–BSA interaction with the use of SFS [38]. And when the Wogonin interaction with BSA was studied with the use of the FT-IR technique, it was found that the protein’s secondary structure was similarly affected [39]. 4. Conclusions Interactions between small molecules and proteins are very important but are not easy to study because of the complexity of the host biomacromolecule and the possibility of competitive interactions. In this work: (1) The multivariate curve resolution-alternating least squares (MCR-ALS) chemometrics method of data analysis was demonstrated to be particularly useful for investigating small molecule–biomacromolecule interactions such as the APT–BSA one. It successfully resolved the complex mixture of fluorescence and UV–visible spectral responses, which contained the profiles of APT, BSA and the APT–BSA complex. The pure spectra of the system of APT and BSA were extracted and the presence of the three reactive species was confirmed. These experiments also suggested that the quenching of the fluorescence by the APT inhibitor followed the static quenching mechanism. (2) The study of the competitive reactions of APT with the site I marker, Phenylbutazone, and the site II marker, Ibuprofen, strongly suggested that site I was the interaction site. In site I, APT seemed to compete with the Phenylbutazone marker mainly in subdomain IIA for the Trp side-chain residue, particularly since conformation change studies suggested that the alternative, Tyr residue mainly in subdomain IIIA, was found to be unaffected. (3) Extracted thermodynamic parameters suggested that the principal mode of binding of APT involved hydrophobic interaction forces. (4) Importantly, the effects of minor structural differences of the small molecules on the thermodynamics of the binding with BSA suggested that the entropy parameters were relatively more affected. Acknowledgements The authors are grateful to the research program of the State Key Laboratory of Food Science and Technology of Nanchang University (SKLF-MB-200807 and SKLF-TS-200919) for financial support.

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