Chiral carbohydrate adducts are effective for enantiomeric ion mobility separations

Abstract

Enantiomers play important roles in biology and the pharmaceutical industry but remain notoriously difficult to separate and characterize. Gold-standard chromatography and nuclear magnetic resonance-based methods are slow, laborious, and expensive, motivating the development of rapid methodologies for enantiomer characterization. While ion mobility spectrometry-mass spectrometry (IMS-MS) has emerged as a rapid technique for chiral analysis, current approaches often rely on derivatization, complicated chiral complexes, or large host molecules that can produce complex spectra. Herein, we investigate small carbohydrates as chiral adducts for the ion mobility separation of amino acid and drug enantiomers. Six commercially available nonreducing or reduced carbohydrates were evaluated as chiral adduct molecules using cyclic IMS-MS. All carbohydrate adducts readily formed simple 1:1 complexes in the MS dimension that produced two discrete IMS peaks for each enantiomeric pair and remained sufficiently stable for extended pathlength separations. The carbohydrate panel enabled chiral separation of all 15 amino acid and drug enantiomer pairs at pathlengths as low as 1 meter. Relative arrival time measurements further enabled unbiased comparison of separation performance across analyte-adduct pairs. The developed carbohydrate-based method was used to quantify enantiomeric excess down to a 99:1 molar ratio with estimated limits of detection down to 5 nM. These results demonstrate that small carbohydrates are effective chiral adducts for IMS-MS-based enantiomer separations and that simple analyte-adduct complexes can provide rapid and broadly applicable enantiomer differentiation without derivatization or the use of multi-molecule complexes.

Graphical Abstract

Introduction

Enantiomers are non-superimposable mirror image isomers and have implications in the pharmaceutical industry and in biology because of their distinct roles. Enantiomers may be naturally occurring (e.g., l/d-amino acids)¹ or produced synthetically during production of new pharmaceuticals (e.g., R/S-drugs)². In many instances, one enantiomer may have desirable effects while the other is inactive or may even have detrimental effects, thus underscoring the need for methods to separate and characterize enantiopure species.² Unfortunately, enantiomers present one of the greatest challenges in separation science, because they cannot be directly separated without either covalent, or non-covalent, interactions/modifications.

In the context of methods for separating enantiomers, it is desirable to keep the molecules unlabeled and create a chiral environment enabling their separations rather than relying on covalent labeling to create diastereomers. Covalent labeling requires functional group-specific chemistry, which may not be practical, or may introduce unnecessary complexities when there are multiple functional groups present. However, for targeted applications, covalent labeling has seen widespread use for enantiomeric separations.^3–6 Liquid chromatography (LC)-based methods for separating enantiomers require chiral stationary phases to provide unique interactions with each enantiomer but require long timescales on the order of tens of minutes to hours.^{7, 8} Chiral capillary electrophoresis (CE)^{8, 9} and nuclear magnetic resonance (NMR)^{10, 11} spectroscopy use chiral shift reagents or chiral solvating agents to resolve enantiomers, but require long acquisition times and large sample amounts, respectively. Mass spectrometry, by definition, cannot resolve enantiomers based on their identical m/z values and tandem mass spectrometry (MS/MS) spectra. However, methods to overcome these limitations, such as the kinetic method relying on for the formation of trimeric noncovalent complexes resulting in unique fragmentation patterns (i.e., branching ratios) have been developed.^12–14 Unfortunately, the kinetic method requires unique metals, references, and fixed ligands for each pair of enantiomers thus making method development more time consuming. Thus, this calls for other gas-phase methods to be developed that are broader in their utility for enantiomeric separations.

Ion mobility spectrometry-mass spectrometry (IMS-MS) separates ions in the gas phase in the presence of a neutral buffer gas and electric fields based on their size, shape, and charge (i.e., their mobilities). IMS-MS has shown promise as a rapid (milliseconds) and highly sensitive alternative to condensed-phased methods for analytical separations.¹⁵ Enantiomers, by definition, have the same mobilities owing to their identical collision cross sections (CCS).¹⁶ However, many successful strategies for distinguishing enantiomers in IMS-MS have been developed. Examples of this include the use of host-guest chemistry and kinetic method-based complexes to form the chiral environment required for enantiomeric IMS-MS separations.^17–22 For enantiomer IMS-MS separations with host-guest chemistry, cyclodextrins, which are comprised of a ring of covalently linked d-glucose molecules, have predominantly been used.^23–27 However, in several cases multiple peaks were observed for individual pure enantiomers with these cyclodextrin-based host-guest inclusion complexes. Furthermore, optimizing which cyclodextrin should be chosen is done empirically based on ring size (i.e., alpha, beta, or gamma) as well as possible OH-group modifications and thus can make experiments laborious in nature. For the kinetic method-based complexes in the IMS-MS separations of enantiomers, choosing the metal and reference (usually amino acids) molecules is again done empirically and the corresponding mass spectra are convoluted in nature and thus selecting which complex to subject to IMS-MS separations can be challenging. It is also important to mention that the breakthrough in high-resolution IMS-MS (i.e., trapped; TIMS, cyclic; cIMS, and structures for lossless ion manipulations; SLIM) have made chiral separations via adduction possible given the extended pathlengths in cIMS and SLIM and the high-resolution of TIMS at slow scan speeds.^28–31 In this work we were interested in developing a broader, and easier to use, method for enantiomer separations in high-resolution IMS-MS.

To achieve this goal, we proposed to use various carbohydrates, which are inherently chiral/enantiopure, as adducts for the IMS-MS separations of various small molecule enantiomers. While other studies have also used carbohydrate adducts to enable enantiomeric IMS-MS separations³², there seemed to be no practical reasoning for the chosen carbohydrates. Specifically, carbohydrates themselves contain alpha/beta anomers at the reducing end that interconvert between each other through an open ring intermediate in the solution phase. Thus, in the gas phase, this can result in up to three unique IMS-MS peaks for an individually pure carbohydrate molecule.^{33, 34} In the context of carbohydrate adducts for enantiomeric separations, this would be highly undesirable. Thus, to overcome the aforementioned issues in using carbohydrates as chiral adducts for enantiomeric separations, we selected a set of criteria that they must follow. Specifically, they must: 1) either have no reducing end or have been reduced themselves to eliminate the anomer issue, 2) be cost affordable in 10s to 100s of milligram scale from commercial vendors, and 3) be available in a range of adduct sizes by varying the degree of polymerization in the carbohydrates. While there are many potential suitable carbohydrates that fit these criteria, the six that we selected in this work as potential adducts for enantiomeric IMS-MS separations are shown in Figure 1. All of these carbohydrates have been previously run individually with high-resolution IMS-MS to confirm they indeed retain a single peak as their singly sodiated adducts as is expected from their chemical structure.^35–37 Herein, we present the use of carbohydrate adducts as a broad and effective strategy for resolving various small molecule enantiomers with high-resolution cyclic IMS-MS separations.

Figure 1.

Structures of the chiral carbohydrate adducts used in this work.

Experimental

Reagents and Sample Preparation

Maltitol, maltotriitol, raffinose, l-serine, l-tyrosine, l-arginine, d-arginine, l-aspartic acid, and d-aspartic acid were obtained from Sigma-Aldrich (St. Louis, MO USA). Sucrose, maltotetraitol, stachyose, and d-serine were obtained from Santa Cruz Biotechnology (Dallas, TX USA). d-tyrosine was obtained from Tokyo Chemical Industry (Portland, OR USA). (±)-Methamphetamine hydrochloride, (+)-methamphetamine hydrochloride, (±)-epinephrine hydrochloride, (–)-epinephrine, omeprazole, (R)-omeprazole (sodium salt), (S)-ketamine hydrochloride, (R)-ketamine hydrochloride, (±)-atenolol, (+)-atenolol, cetirizine hydrochloride, (R)-cetirizine hydrochloride, (±)-baclofen, (+)-baclofen hydrochloride, l-DOPA, d-DOPA, (S)-ibuprofen, (R)-ibuprofen, (+)-warfarin, and (–)-warfarin were obtained from Cayman Chemical (Ann Arbor, MI USA). l-Penicillamine and d-penicillamine were obtained from Sigma-Aldrich (St. Louis, MO USA). Structures of all amino acid and drug compounds are shown in Figure 2. Solutions were prepared by diluting drug compounds and carbohydrate hosts to ~10 μM each in 49.75/49.75/0.5 v/v/v H₂O/methanol/acetic acid for direct infusion electrospray analysis. Unless a racemic mixture was provided, enantiomer pairs were mixed in an equimolar ratio.

Figure 2.

Structures of the amino acid and drug compounds analyzed in this work. Chiral centers are designated by a red dashed circle; exact chiral configurations are shown in Figure S1.

Instrument Settings and Data Processing

The commercially available cIMS-MS platform from Waters Corporation (Wilmslow, UK) was used and data were acquired with MassLynx and Quartz.²⁸ Each solution was subjected to direct infusion electrospray ionization at 5 μL/min and ions of interest were filtered by the quadrupole prior to ion mobility analysis to encompass the mass-to-charge (m/z) of the desired complex. Ions were separated through the cyclic mobility region (1.73 mbar N₂) and traveling wave conditions were optimized for resolution. Traveling wave conditions were optimized individually for each experiment and are shown in Table S1. Finally, ions were routed to the time-of-flight (TOF) mass spectrometer operating in V mode for detection.

Results and Discussion

Complex Formation and Stability

Initially, we needed to test various factors to determine if the carbohydrate adducts we selected would be suitable to enable enantiomeric IMS-MS separations. Specifically, we must: 1) form the desired noncovalent complexes as observed with MS, 2) transmit the complexes through the cIMS separation region without unwanted losses (i.e., fragmentation), and 3) extend the separation pathlengths to enable sufficient resolution of the enantiomers as their carbohydrate adducts. To test this, we first acquired a mass spectrum of serine in the presence of an equimolar mixture of all six chiral carbohydrate adducts (Figure 3). In order to simplify data analysis and forgo adding any extra metal ions, we searched mainly for 1:1 complexes between the chiral analytes and carbohydrate adducts with either a proton or sodium ion as the charge carrier. We observed the [Ser + Carb + H]⁺ complex for all six adducts in analytically relevant formation efficiencies. For this analyte, the complexes involving reduced sugars (i.e., maltitol, maltotriitol, and maltotetraitol) seemed to be higher in intensity overall compared to the non-reducing sugars (i.e., sucrose, raffinose, and stachyose). Other complexes involving sodiated adducts as well as multimers were observed but were too low in signal intensity and defeated the purpose of simplifying chiral analysis, respectively. Furthermore, any complexes involving multiple chiral analytes were not investigated due to the increasing number of enantiomers and diastereomers that result when run in a racemic mixture (e.g., ll, dl, dd, and ld). All other chiral analytes in this study showed varying yields with each carbohydrate adduct, but this experiment with serine as the analyte is representative in nature. We do note that other instrument platforms may display different mass spectra given the differing electrospray conditions, source designs, and ion optics.

Figure 3.

Mass spectrum (TOF only, mobility off) of serine in an equimolar mixture of all carbohydrate adducts. Values in bold are the desired noncovalent complexes to be subjected to cIMS-MS separations.

After determining that the desired complexes did form, we were interested in assessing their stability during transmission through the cIMS separation region as a function of traveling wave conditions and pathlength (i.e., number of cycles). Specifically, at longer pathlengths there is a greater chance of space charge-based fragmentation in the trapping region³⁸ as well as from using activating traveling wave conditions (i.e., higher amplitudes)³⁹. Figure 4 highlights the evolution of the [Ser + Maltitol + H]⁺ complex as a function of traveling wave conditions at varying pathlengths. From Figure 4, it is clear that the traveling wave conditions, particularly the traveling wave amplitude, have a major effect on transmission of the desired noncovalent complex where the gentlest conditions provide the greatest transmission efficiency. We believe this underscores the need for tuning experimental traveling wave conditions for labile species. Signal loss was attributed primarily to non-dissociative, transmission-based losses for the “gentle” and “intermediate” conditions, whereas in the “default” conditions, loss was attributed to be both transmission-based and dissociation-based, as shown by the fragment ion intensities in Figure S2.

Figure 4.

Evaluation of traveling wave conditions and pathlength on the stability of the [Ser + Maltitol + H]⁺ complex. “Default” is the standard traveling wave conditions that are used for initial instrument tuning. Arrival time peak area of the intact complex was normalized to the 1-meter data. [Ser + Maltitol + H]⁺ was quadrupole isolated prior to IMS-MS separation.

Enantiomer Separations

After determining that the complexes could be formed and subsequently be transmitted through the cIMS region, we assessed each of their separations. Figure 5 shows the resulting separations of d- and l-serine with all six carbohydrate adducts. For each experiment, the desired complex was quadrupole isolated based on its m/z prior to mobility separation. Then, the ions were cycled through the ~1 m traveling wave cyclic ion mobility region until either the enantiomers were near baseline resolved or ion lapping (i.e., wraparound effect) occurred. We observed that the best performing chiral carbohydrate adduct for separation of the serine enantiomers was maltitol, as baseline separation was achieved in only 15 m of separation. Other adducts showed varying degrees of separation; serine with stachyose showed ~80 % resolution at 45 m, whereas serine with maltotriitol showed almost no resolution of the enantiomers. Unsurprisingly, the arrival time order of d- and l-serine enantiomers was not consistent between adducts, which highlights the orthogonality of the separations. Although an equimolar mixture of each enantiomer was used for analysis, the relative intensities of the corresponding peaks were not always equal, which may be due to differences in relative stability or ionization efficiency of the complexes. In fact, it has been shown that amino acid-carbohydrate complexes differ in stability depending on chiral identity.⁴⁰ Only two arrival time features (one for each enantiomer) were observed for each mixture, and no unusual peak broadening was observed, suggesting that there is potentially only one stable conformation for each analyte-adduct complex. The complexes formed were simple in nature (i.e., a 1:1 inclusion complex between carbohydrate adduct and serine enantiomer), did not require additional reagents or metal ions (i.e., observed as their protonated versions), and were stable enough to survive many passes through the cyclic ion mobility region. We believe that the overall simplicity of our approach is an improvement over other methods that require derivatization or complex multimer formation.

Figure 5.

Arrival time distributions showing chiral separation of l- and d-serine complexed with each of six chiral carbohydrate adducts. Pathlengths (i.e., number of meters) are depicted with the cycle graphic. Traveling wave conditions are defined in Table S1. Assignments were established through individual analysis of the available enantiopure standard.

After showing one pair of amino acid enantiomers could be successfully separated with our various chiral carbohydrate hosts, we sought to extend our analysis to other amino acids as well as small molecules. Figure 6 shows a selection of particularly high-resolution separations of these enantiomer pairs. One of the more interesting results is the baseline separation of l- and d-tyrosine using maltotetraitol as the chiral carbohydrate adduct after only 1 m. To the best of our knowledge, this is the first report of such a separation at this pathlength. Other amino acid enantiomer pairs including aspartic acid, arginine, and penicillamine also showed excellent resolution at modest pathlengths (≤13 m). Epinephrine, omeprazole, ketamine, and warfarin, all of which have varying functional groups, were baseline or near baseline resolved using a variety of carbohydrate adducts.

Figure 6.

Arrival time distributions showing chiral separation of amino acid and drug enantiomer pairs using a variety of carbohydrate adducts. Pathlengths (i.e., number of meters) are depicted with the cycle graphic. Traveling wave conditions are defined in Table S1. Assignments were established through individual analysis of the available enantiopure standard.

Until this point, we have only qualitatively described the separation between enantiomers using our chiral carbohydrate hosts. In order to quantitatively compare separations between different enantiomeric analytes and corresponding carbohydrate adducts in an unbiased manner, we needed a mathematical descriptor to quantify the quality of the separation. Traditionally, this is done by calculating peak-to-peak resolution values. However, this is a pathlength dependent term, and because our separations are at varying pathlengths, it cannot be used. Also, there is a component of peak widths, which may be biased based on the pathlength, speed of the separation (i.e., traveling wave conditions), as well as being difficult to measure for poorly resolved species. Thus, we elected to use a percent relative arrival time (t_Rel., Equation 1) metric that is pathlength and traveling wave independent, giving us an unbiased way to compare separations.^{41, 42} Although relative arrival time is not a substitute for conventional resolution measurements, it provides an unbiased descriptor of intrinsic mobility differences that facilitates comparison across experiments performed at different pathlengths and instrument settings. Peak arrival times (t_b and t_a) were defined as the local maxima of a 5-point moving average smooth of the raw arrival time distributions.

$$t_{Rel.}=\left(\frac{t_b}{t_a}-1\right)\times 100$$ (1)

Table 1 contains the calculated t_Rel. values for all separations performed in this study as well as a color-coded ranking of the values; enantiomers that showed poor, modest, and good separations are color coded red, yellow, and green, respectively. We speculate that separations with t_Rel. values >2 (green) may show at least partial resolution on the commercial 1-meter drift tube IMS-MS platform, values between 1 and 2 may be routinely separable on modern high resolution IMS-MS platforms such as 13 m MOBIE-SLIM or high-resolution TIMS, and values <1 would require ultrahigh resolution devices such as multi-pass SLIM or the multi-pass cIMS in this work. These thresholds are purely speculative and are meant to serve as approximate guidance; future work should be done to accurately assess performance across instrument platforms. All arrival time distributions are shown in Figure S3–S4. Table 1 is meant to serve as a general guideline when choosing chiral hosts depending on the structure of the desired analyte. For example, the structures of tyrosine and DOPA differ by only one hydroxy group but show similar separation profiles for each chiral carbohydrate adduct (e.g., excellent separation using maltotetraitol and poor separation using maltitol). Also, Table 1 enables us to survey general trends in the effectiveness of each carbohydrate host for separating small-molecule enantiomers. Sucrose, for example, was relatively ineffective for most of the chosen analytes. Fortunately, all analytes showed moderate separation with at least one carbohydrate adduct, showing that this set of six adducts is a comprehensive array of chiral selectors for ion mobility separations of enantiomers. We would like to reiterate here that the use of relative arrival times (i.e., t_Rel.) as opposed to resolution is done because of the nature of the separations on a cIMS instrument. Resolution could, in theory, be scaled to any desired value by employing ultralong pathlength separations and compression strategies^{24, 29, 43, 44}, whereas t_Rel. can unbiasedly describe intrinsic mobility differences and potential performance of the particular separation. Furthermore, t_Rel. is a pathlength independent metric, unlike resolution which can depend on pathlength and can be manipulated with post-processing (i.e., high-resolution demultiplexing⁴⁵) or through experimental ion manipulations (i.e., compression strategies^{24, 43, 44}). We note that these are all single trial experiments, but errors using t_Rel. values are ~ 0.01 based on triplicate trials from our previous work using this same cIMS-MS platform.⁴⁶ The limit of detection for this method varies depending on the particular complex, but is estimated to be as low as 5 nM chiral analyte (Figure S5).

Table 1.

Percent relative arrival time (t_Rel.) values for all separations as their [Analyte + Carbohydrate Adduct + H/Na]⁺ adducts. Separation pathlengths, traveling wave conditions, adduct information, and resulting arrival time distributions are shown in the Supporting Information. A value of n/a indicates that the complex was not detected. A value of zero indicates that no separation was observed and data was not collected. Values <1 are colored red, between 1 and 2 are yellow, and >2 are green. Green with bold indicates excellent separation in ≤5 meters.

	Maltitol	Maltotriitol	Maltotetraitol	Sucrose	Raffinose	Stachyose
Ser	2.79	0.30	0.42	0.96	0.86	1.06
Arg	n/a	2.76	0.19	n/a	0.00	0.88
Asp	0.00	1.63	0.00	0.00	1.87	5.02
Tyr	0.00	1.15	10.38	0.00	1.34	0.38
DOPA	0.68	2.69	8.57	0.00	0.00	1.31
Ibu	0.63	0.93	0.70	0.00	1.11	1.04
War	1.29	2.09	1.98	0.00	2.57	2.38
Bac	2.69	1.42	2.17	1.02	0.00	0.00
Pen	3.26	0.95	0.88	2.51	2.03	2.84
Met	n/a	0.00	1.22	n/a	0.00	0.00
Ket	n/a	0.00	0.00	0.00	0.00	1.55
Cet	0.95	1.53	2.21	0.00	1.69	0.74
Epi	1.44	1.96	1.17	0.00	3.18	0.00
Ome	0.00	0.75	1.24	1.85	2.94	0.00
Ate	n/a	1.20	0.00	n/a	0.78	2.06

Enantiomeric Excess

After assessing the scope of this panel of carbohydrates as chiral adducts and quantifying the separations, we wanted to determine if our method was quantitative in nature in terms of concentration. Enantiomeric excess (ee) is an important metric in pharmaceutical research, and IMS-MS may be used to quickly and accurately determine ee.^{17, 47, 48} To determine whether our established method could accurately quantify ee, we chose d- and l-tyrosine with maltotetraitol because of its excellent separation at a short pathlength. Individual d- and l-tyrosine standards were prepared in a series of relative concentrations with an equimolar amount of maltotetraitol. The resulting [Tyr + Maltotetraitol + H]⁺ complexes were separated to a pathlength of 2 meters to ensure that the enantiomers are fully separated and do not contribute to each other’s peak areas. Figure 7 shows the results of the ee experiment, where theoretical ee was calculated by Equation 2 using the concentrations of the individual enantiomers; experimental ee was calculated using the peak areas in place of the concentrations in Equation 2.

$$ee\left(A\right)=\frac{\left[A\right]-\left[B\right]}{\left[A\right]+\left[B\right]}$$ (2)

The plot showed excellent linearity (R² = 0.9991) supporting that high-resolution ion mobility may be used to accurately quantify ee down to a 99:1 molar ratio. The stability, ionization efficiencies, or linear dynamic ranges of the l-complex versus the d-complex may not always be equivalent in ion mobility measurements, thus resulting in differing peak areas at 1:1 molar ratio. So, when using this method to determine actual ee, one must create calibration ranges for each species (i.e., vary the concentrations) to account for these differences. Beyond qualitative differentiation, our results demonstrate that IMS-MS with chiral carbohydrate adducts can provide quantitative stereochemical information (R² > 0.999 for ee) on a rapid (<1 s) timescale. This capability may be valuable for rapid assessment and quality control of synthetic products, pharmaceutical formulations, or biological samples where enantiomeric composition is important.

Figure 7.

2-meter cIMS-MS separation of a 99:1 molar ratio of l- and d-tyrosine as the [Tyr + Maltotetraitol + H]⁺ complex (A). Enantiomeric excess (ee) plot from 1:99 l/d to 99:1 l/d molar ratios (B).

Conclusions

Enantiomeric identification is important for accurately characterizing molecules for new drug applications, yet their separations remain particularly challenging with conventional analytical methods. Chiral LC is the gold standard for such separations, but suffers from low throughput, expensive column chemistries, and labor-intensive method development. IMS-MS has gained in popularity for rapid isomer separation, and techniques such as covalent derivatization and noncovalent host-guest chemistry has allowed for separation of enantiomers. However, such approaches are limited by their spectral complexity, requirement for metal adduction, or involve multimer formation which is less analytically useful. In this work, we explored the use of simple, commercially available carbohydrates for enantiomeric separations that require no modification and form simple (e.g., [M + Carbohydrate Adduct + H/Na]⁺) and stable (i.e., survive 10s of meters of IMS separation) complexes with a range of chiral analytes.

Our choice of carbohydrates as chiral adducts was based on ones that contain no alpha/beta anomers to complicate our analyses and potentially convolute the IMS peak space. We globally observed all 15 of our enantiomeric pairs to form simple adducts with these carbohydrates and were all resolved in modest cIMS-MS separation pathlengths (≤30 m). More importantly, all species except for one (Figure S4) displayed an individual peak for each individual enantiomer with no obvious fronting/tailing or unexplained peak widths. We then further characterized our separations in a pathlength independent manner by calculating relative arrival times between each pair of peaks enabling us to assess the degree of separation for all complexes in a concise, unbiased way. Sucrose was the weakest adduct in terms of separation capability across the various chiral analytes, but all analytes showed at least some degree of separation between enantiomers. There is no clear trend regarding which chiral carbohydrate adducts perform best overall, nor the arrival time order of enantiomers. Successful separations were observed for amino acids and structurally diverse drug-like compounds, suggesting that the interactions responsible for stereochemical discrimination are broadly applicable across multiple functional groups. Thus, these results demonstrate that this panel of six carbohydrate adducts can facilitate chiral separation of a variety of small-molecule enantiomers and may be more broadly applicable to other enantiomer sets.

Unlike many existing approaches that rely on derivatization, metal coordination chemistry, or complex multimeric assemblies, our presented strategy uses simple noncovalent complexes analyzed on sub-second timescales. Our methodology requires no additional sample preparation other than adding the desired chiral host in approximately equimolar quantity. Our method produces clean mass spectra and ion mobility arrival time distributions, as evidenced by the simple adduct formation and two mobility peaks for each enantiomeric mixture. The broad range of successful separations observed across amino acids and pharmaceutical compounds suggests that carbohydrate-based chiral recognition may represent a generally useful platform for rapid stereochemical analysis. Future work may focus on defining the structural features governing chiral recognition and expanding the library of carbohydrate selectors.

Supplementary Material

Structure and configurations of all enantiomers, traveling wave settings for each experiment, pathlength-dependent fragment ions, arrival time distributions for all separations, limit of detection determination.