NMR provides information about analyte–modifier interactions, which, in turn, helps researchers understand MEKC separations.
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© 2005 AMERICAN CHEMICAL SOCIETY
Using NMR to Develop Insights into Electrokinetic Chromatography Kevin F. Morris and Angela L. Froberg Carthage College Bridget A. Becker and Valentino K. Almeida University of Kansas Jepkoech Tarus Louisiana State University Cynthia K. Larive University of California, Riverside
N
MR is a powerful method for studying the interactions between molecules because it provides information about both binding affinities and dynamics. Changes in NMR chemical shift indicate that intermolecular interactions have occurred. These changes reflect the local chemical environment of the nucleus and are, therefore, influenced by factors such as hydrogen bonding, shielding, hydrophobic interactions, and electrostatic (dipole–dipole) effects. Direct evidence for intermolecular interactions can be obtained from the nu-
© 2005 AMERICAN CHEMICAL SOCIETY
clear Overhauser effect (NOE), which provides information about interactions between nuclei that are within ~5 Å but not necessarily connected through chemical bonds. More recently, NMR diffusion measurements have offered an alternative approach for probing intermolecular interactions. In this article, we explain how NMR spectroscopy can give unique insights into the intermolecular interactions important in separations conducted with electrokinetic chromatography (EKC), a modified form of CE first reported in 1984 by Terabe (1). J U LY 1 , 2 0 0 5 / A N A LY T I C A L C H E M I S T R Y
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(a)
S Solute
Covalent bonds
–
Electrophoresis of polymeric sur factant
– S
–
+
–
EOF
– –
S –
–
–
S In CE, analytes are transported through the capillary by electroosmotic flow (EOF), which is a pluglike bulk S S migration of the run buffer generated at the capillary wall–solution interface when an electric field is applied (2). (b) Analytes are separated in CE because O O – Na+ they have different migration velocities poly (SULV) H through the capillary, determined by H2 N * C CH the magnitude of the EOF and their N * O H respective electrophoretic mobilities, O x which depend on the charge-to-size ratio of the ion. Neutral analytes miH5 H4 grate with the EOF and cannot be sepH3 H6 arated by CE because they have no 40 electrophoretic mobility. 30 O In EKC, the run buffer contains a O H7 R H8´ BNP modifier that interacts with the analyte P H8 20 H7´ (Figure 1a). In micellar EKC (MEKC), O OH S the modifier is a surfactant that forms 10 micelles, which act as a pseudostationH6´ H3´ ary phase (3). Analytes are separated in 0 MEKC mainly on the basis of their difH5´ H4´ fering affinities for the micelle. Sodi–10 um dodecyl sulfate, Brij-35, Tween –20 20, and cetyltrimethylammonium bromide are among the most commonly used surfactants for MEKC separa22 24 26 28 30 tions, either singly or as mixtures. A Time (min) limitation of these surfactants is that they provide only a transient hy- FIGURE 1. (a) A schematic of the process of an EKC separation by means of a polymeric surfacdrophobic environment into which tant. Although the electrophoretic mobility of the negatively charged micelles is toward the analytes can partition. In addition, to anode, the strong EOF causes a net flow of the solution toward the cathode. (b) A typical electrooptimize MEKC conditions, experi- pherogram for the EKC separation of the BNP enantiomers, with poly(SULV) used as a buffer mental parameters such as tempera- modifier. Molecular structures of BNP and poly(SULV) are given above the electropherogram; ture, pH, organic modifier content, * indicates chiral centers, and x is the degree of polymerization. buffer ionic strength, and surfactant concentration must be varied. However, these changes can often micellar solutions. Consequently, unlike conventional micelles, disrupt the dynamic equilibrium between the micelles and the changes in the concentration of the polymeric surfactant or the free surfactant monomers (4). The need to overcome these lim- presence of organic modifiers cannot break the micellar bonds, itations paved the way for the development of conformationally although the structure may vary with solvent conditions. Reflexible polymeric surfactants for use as EKC modifiers (5). searchers have manipulated the separation ability of polymeric Polymeric surfactants, such as polysodium N-undecanoyl-L- surfactants by changing the sequence and configurations of the leucylvalinate [poly(SULV)], are high-molecular-weight macro- surfactant’s head group (6), the length of the hydrocarbon molecules resulting from the polymerization of conventional chain (7 ), or the counterion at the surfactant head group (8), or surfactants at micelle-forming concentrations (Figure 1b). Poly- by adding organic modifiers (9). Unique and complex intermeric surfactants are popular EKC additives in part because molecular interactions between the analytes and various polytheir structural rigidity, due to covalent linkage among the meric surfactants often lead to remarkable EKC separations monomeric units, eliminates the dynamic equilibrium present in (Figure 1b). mAU
–
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practical strategy to minimize undesirable anaCyclodextrins (CDs) or other compounds calyte–modifier interactions (19). The concentrapable of forming host–guest complexes can be tions used in NMR experiments can mimic those used to achieve chiral EKC separations. The selectivfor the separation. However, unless miniaturized ity of CDs has been manipulated by varying the size of NMR detection probes are used, the typical NMR sample the cavity or by chemically modifying the outer-rim hydroxyl groups with neutral or charged functional groups (10). volumes (600–750 µL) greatly exceed those utilized in CE. Mixtures of neutral and charged CDs or of CDs and surfactants Therefore, NMR experiments will generally require more of can enhance separations of chiral analytes because of the differ- the analyte and additive. ences in complexation mechanisms and affinities of each selector with the analyte enantiomers (10). An alternative approach uses Chemical shift analysis chiral surfactants, such as those containing amino acid or dipep- An analysis of complexation-induced chemical shifts (CICS) can tide head groups. In addition, polymerized chiral surfactants can often be used to gain insight into the interactions between anaenhance separations while overcoming many of the limitations of lytes and CE buffer modifiers. The chemical shift of an NMR-acmonomeric surfactants (11). The chiral selectivity of polymeric tive nucleus is sensitive to its local electronic environment. When surfactants can be altered by varying the amino acid head group changes in this environment occur—for example, by the gain or or by reversing the order of the amino acids in dipeptide poly- loss of an acidic proton, noncovalent interactions with other meric surfactants (12, 13). molecules, or the formation of a host–guest complex—changes Researchers are challenged by an inadequate understanding of in the chemical shift are often observed. the mechanisms that govern these separations, even as they seek Analysis of CICS can be used to gain insight into analyte– to optimize the experimental conditions. Because of the lack of modifier intermolecular interactions if a significant change in analytical techniques that provide specific information about an- the chemical shift of either an analyte or a modifier resonance alyte–modifier interactions, researchers have relied on trial and can be observed upon complex formation. Although in princierror and mathematical optimization schemes (14, 15). Howev- ple the chemical shift of any NMR-active nucleus can be monier, trial and error is time-consuming because the analyst must tored, in most applications, either 1H or 13C spectrometry is logically and sequentially vary separation parameters such as pH, used. In a typical CICS experiment, a series of solutions is pretemperature, voltage, injection pressure, modifier concentration, pared in which either the analyte or modifier concentration is and capillary length (16, 17). Mathematical optimization uses varied. NMR spectra are then collected, and the chemical shifts statistical models, such as linear solvation energy relationships, of selected analyte and modifier resonances are monitored. Figwhich describe experimental variables better than the 5 (a) CH2OH CH2OH trial-and-error method but CH3 1 3 H2 H2 may not give specific inforCH 4 C 2 C H4 H4 mation on the nature of anO CH3 6 CH N H8´ H HO H5 H5 alyte–modifier interactions. H7´ H2´ H1 NMR can provide valuH1 able information about anH3 H3 H6´ H2 H2 H3´ alyte–modifier interactions that can help elucidate the H5´ H4´ fundamental nature of the Propranolol thermodynamics, orienta-CD tion, and dynamics of binding (18). With NMR, (b) the behavior of each chemFIGURE 2. (a) The structures ically distinct component of propranolol and -CD. 25.0 mM in the separation phase can (b) NMR spectra measured be monitored in a single for the titration of a 10-mM 20.0 mM measurement. This infor-CD solution with (R)-promation can guide the sepranolol. The propranolol con10.0 mM lection of the appropriate centrations are listed on the modifier or even the deright. Complexation-induced sign of new and improved changes in the chemical shift 5.0 mM buffer modifiers. In addiof the -CD resonances are H2 H5 H6 H4 H3 tion, interactions that inobserved as the propranolol 0.80 mM crease migration time and concentration is increased. decrease separation selecThe largest shift is observed 3.5 3.6 3.9 3.8 3.7 tivity and peak efficiency for the -CD proton H5 on the ppm have created the need for a inside of the host cavity. J U LY 1 , 2 0 0 5 / A N A LY T I C A L C H E M I S T R Y
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obs = ffreefree + fboundbound
(1)
in which ffree and fbound are the mole fraction of free and bound analyte. If we assume a 1:1 binding stoichiometry, then ffree + fbound = 1 and Ka becomes
Ka =
[A bound]
(2)
[A free][Modif ier]
in which [A bound] is the concentration of the analyte bound to the modifier, [A free] is the concentration of the analyte free in solution, and [Modifier] is the concentration of the free buffer modifier. In cases where the modifier is present in large excess, as in binding to micelles or polymerized surfactants, the total modifier concentration can be used for [Modifier]. Combining Equations 1 and 2 yields Ka =
obs – free (bound – obs) [Modifier]
(3)
The observed chemical shift is recorded directly from the NMR spectra of solutions that contain both the analyte and modifier; the chemical shift of the free analyte is obtained from an NMR spectrum collected for an analyte solution under the same experimental conditions. However, bound cannot usually be obtained directly from a single NMR measurement. Instead, it is determined by a least-squares fit of the data at several analyte-to-modifier concentration ratios or by extrapolation of the CICS titration results to infinite modifier concentration. Finally, the total modifier concentration is measured by comparing the relative intensities of the modifier resonances to an external chemical shift 258 A
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Mole fraction (obs – free )
ure 2 shows molecular structures of (R)-propranolol and -CD and a CICS data set for this analyte–modifier mixture. The atom labels in Figure 2b correspond to the -CD hydrogens. As the analyte concentration is increased, changes in chemical shift are observed for all of the CD resonances. However, the most pronounced shift occurs for -CD hydrogen H5 on the inside of the host cavity. This result shows that the analyte inserts itself into the -CD cavity to form an inclusion complex. Although it is assumed that these nuclei are involved in the analyte–modifier interactions, it must be stressed that this type of information is not always conclusive. The observations must be confirmed by complementary techniques such as NOE spectroscopy (NOESY) and rotational-frame NOE spectroscopy (ROESY) experiments. The association constant Ka of the analyte–modifier complex can also be calculated from CICS data sets. In these analyses, we assume that the free and bound forms of the analyte undergo fast exchange on the NMR chemical-shift time scale. Under these conditions, the observed chemical shift is the weighted average of the free (free) and bound (bound) values or
0.012
0.008
0.004 H2 N 0.000 0.0
0.2
O
H2 C C H2 0.4
C C H2
OH
0.6
0.8
1.0
Mole fraction
FIGURE 3. The Job’s plot obtained from NMR spectra as the concentrations of -aminobutyric acid and -CD are varied. The maximum at a mole fraction of 0.5 indicates a 1:1 stoichiometry for the analyte–-CD complex. The structure of -aminobutyric acid is shown under the plot.
reagent, such as trimethylsilylpropionic acid, or calculated from serial dilution. Alternatively, Ka can be calculated by a graphical approach that relies on the Benesi–Hildebrand equation as modified by Scott for a complex with 1:1 stoichiometry (20, 21). [Modifier]
[Modifier]
1
(4) K a bound in which obs is (free – obs) and bound is (free – bound). According to Equation 4, plotting [Modifier]/obs versus [Modifier] yields a line with a slope of 1/bound and a y intercept of 1/(boundKa). Ka is calculated by simply taking the ratio of the slope and the y intercept. When this analysis is applied to the (R)propranolol–-CD data set shown in Figure 2b, Ka = 212 M–1 is calculated. Along with the association constant, the stoichiometry of the analyte–modifier complex can be established from an analysis of CICS. NMR spectra are again recorded for a series of solutions that contain both the analyte and modifier. Typically, the mole fraction of the analyte is varied from 0 to 1, but the total concentration of analyte plus modifier is kept constant in each solution. A resonance that undergoes a significant complexation-induced shift is then identified, and this resonance’s obs is recorded. A graph is prepared with the analyte mole fraction plotted on the x axis and the product of the analyte mole fraction and the quantity (obs – free) plotted on the y axis. If the resulting graph, often referred to as a Job’s plot (22), shows a maximum at an analyte mole fraction of 0.5, then the stoichiometry of the analyte–modifier complex is 1:1. Similarly, a maximum at 0.4 indicates a 2:1 complex. A sample Job’s plot is shown in Figure 3 for the complexation of the neurotransmitter -aminobutyric acid by -CD. This approach has been utilized to investigate the binding of many analytes with diverse structures. Kitae and co-workers highlighted the use of separation techniques to confirm the strength of modifier–analyte interactions determined by CICS analysis (23). However, Wenzel’s group has reported that experiments with calixarenes, another type of common CE mobile-phase modifier, indicate that results from CE separations and CICS analysis may not always correlate (24). Therefore, CICS analyses provide information about the nature of the analyte–modifier complex as well as the complex’s asKa =
obs
=
bound
+
V H
(a)
L H (S)-BNP
18 23
48 8.2
8.0
7.8
4.5 4.4 4.3 4.2 4.1
4.0
3.9
ppm (b)
1.6
ad ien t(
NMR diffusion experiments An alternative method for investigating analyte–modifier interactions is pulsed field gradient (PFG)-NMR diffusion experiments (26, 27 ). Gao and Wong used diffusion coefficients to investigate analyte partitioning between a micellar pseudophase and bulk solvent, as well as to determine the thermodynamic parameters G, S, and H (28). In NMR diffusion experiments, the diffusion coefficient D of both the analyte and modifier are measured using pulse sequences that incorporate magnetic field gradient pulses to encode the spatial positions of the nuclei. These experiments also include a delay during which both the analyte and modifier molecules undergo free diffusion. The diffusion delay is followed by decoding gradient pulses and detection of the NMR signal. In a typical diffusion experiment, a series of spectra are measured with increasing values of the magnetic field gradient strength g (Figure 4a). The intensity I of each resonance in the resulting NMR spectrum decays exponentially with increasing g according to
1.2 0.8 Ln (peak area)
Gr
43 45
G/
33 38
cm )
28
plexes with small Ka values often fall into this category. Another problem is resonance overlap. When analyte resonances overlap each other or the modifier, it is often impossible to quantify the change in analyte chemical shift. Finally, Ka calculated by the methods described earlier for a particular analyte–modifier system can sometimes depend on the resonance used for the calculation (24, 25).
0.4 0.0 – 0.4 – 0.8 0.0
2.0 105
6.0 105
1.0 106
(g )2 ( – 3)
FIGURE 4. (a) PFG-NMR spectra measured for a solution containing (S )-BNP and poly(SULV) as a function of the amplitude of the gradient pulses. The diffusion experiment was performed with the bipolar pulse pair stimulated echo pulse sequence. The diffusion time and gradient pulse width were 75.0 and 4.0 ms, respectively. Note that the spectra in this figure are offset; if they were not, the resonances would lie on top of each other, because no change in chemical shift occurs when gradient amplitude increases. (b) The linearized form of Equation 5 is used to plot a graph of the results from (a). The different slopes of the resulting lines reflect the diffusion coefficients of (S)-BNP and poly(SULV). Data plotted with open squares correspond to poly(SULV); data plotted with closed squares correspond to (S)-BNP.
sociation constant and stoichiometry. In addition, because virtually all analytes and modifiers have one or more NMR-active nucleus, this method is widely applicable. However, several drawbacks exist. In some applications, complex formation results in very modest changes in the analyte or modifier chemical shift (i.e.,
