Two Methods for the Determination of Enantiomeric Excess and Concentration of a Chiral Sample with a Single Spectroscopic Measurement

Abstract

The previously established enantioselective indicator–displacement assays (eIDAs) for the determination of concentration and enantiomeric excess (ee) require two spectroscopic measurements for each chiral sample. To further simplify the operation of eIDAs, we now introduce two innovative analytical methods, both of which utilize a dual‐chamber quartz cuvette, which reduces the number of spectroscopic measurements from two to one. An attractive feature of this cuvette is that the concentration‐ and ee‐dependent absorption data can be collected at the isosbestic points or transparent regions of the spectra recorded in each individual chamber, thereby reflecting optical changes that occur in the other chamber. Therefore, two independent equations, which are needed to solve the values of the two independent variables—concentration and ee—can be established with only a single spectroscopic measurement. The first method takes advantage of this feature in conjunction with a judicious choice of indicator/host combinations to generate concentration‐ and ee‐dependent calibration curves. Our second method removes the requirement to measure equilibrium constants and molar absorptivities altogether through the use of artificial neural networks (ANNs). The most frequently used three‐layer feed‐forward network is generated, which relates the absorption data to concentration and ee of the samples by training with a back propagation procedure. Here, the data collection is not limited to the isosbestic points or transparent regions. Both approaches enabled accurate and rapid determination of concentration and ee of chiral samples. The technology removes the relative difficulty, which is the need for two separate measurements for concentration and ee respectively, of analyzing chiral samples compared to achiral samples. When implemented in a high‐throughput format, this technology should greatly facilitate the discovery of asymmetric catalysts in the same way as conventional high‐throughput screening assays.

Chiral Recognition by Fluorescence: One Measurement for Two Parameters

“…Anslyn and coworkers established enantioselective indicator displacement assays (eIDA), with which achiral and chiral sensors were used to determine the concentration and enantiomeric purity of a chiral sample, respectively [41]. To reduce the number of spectroscopic measurements from two to one, they utilized a dual-chamber quartz cuvette filled with careful choice of indicator/host combinations [42], with which information about the two samples in these two chambers can be acquired at two distinct wavelengths with a single spectroscopic measurement. They further employed the use of artificial neural networks (ANNs) to fingerprint chemical identity, concentration, and chirality of chiral compounds [43,44].…”

Artificial Neural Network in Drug Delivery and Pharmaceutical Research

“…Hasani et al used ANNs for detection and calibration of amino acids with similar structures and spectrums such as tryptophan, tyrosine, and histidine [32]. Moreover, ANNs are capable of assisting in determining of concentrations of a chiral sample and enantiomeric excess in a single spectrophotometric measurement due to their ability to identify non-linear relationships [34]. For instance, ranitidine hydrochloride, one of the most commonly prescribed antihistamines, exists in two forms, Form 1 and 2.…”

An ESI-MS Method to Determine Yield and Enantioselectivity in a Single Assay

“…Various optical strategies have been employed as a rapid and efficient method to determine both concentration and % ee in a single assay [27][28][29][30][31][32][33][34][35]. NMR assays have been developed to determine both concentration and enantioselectivity of a reaction [36].…”