Two methods for the determination of enantiomeric excess and concentration of a chiral sample with a single spectroscopic measurement

被引:49
作者
Zhu, Lei [1 ]
Shabbir, Shagufta H. [1 ]
Anslyn, Eric V. [1 ]
机构
[1] Univ Texas, Dept Chem & Biochem, Austin, TX 78712 USA
关键词
analytical methods; artificial neural networks; chirality; host-guest systems; supramolecular chemistry;
D O I
10.1002/chem.200600402
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页码:99 / 104
页数:6
相关论文
共 31 条
[1]   FEEDFORWARD NEURAL NETWORKS IN CHEMISTRY - MATHEMATICAL SYSTEMS FOR CLASSIFICATION AND PATTERN-RECOGNITION [J].
BURNS, JA ;
WHITESIDES, GM .
CHEMICAL REVIEWS, 1993, 93 (08) :2583-2601
[2]   Measurement of enantiomeric excess using molecularly imprinted polymers [J].
Chen, YZ ;
Shimizu, KD .
ORGANIC LETTERS, 2002, 4 (17) :2937-2940
[3]   Feed-forward artificial neural networks: Applications to spectroscopy [J].
Cirovic, DA .
TRAC-TRENDS IN ANALYTICAL CHEMISTRY, 1997, 16 (03) :148-155
[4]   Double-cuvette ISES: In situ estimation of enantioselectivity and relative rate for catalyst screening [J].
Dey, S ;
Karukurichi, KR ;
Shen, WJ ;
Berkowitz, DB .
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 2005, 127 (24) :8610-8611
[5]   Emerging methods for the rapid determination of enantiomeric excess [J].
Finn, MG .
CHIRALITY, 2002, 14 (07) :534-540
[6]  
Floriano P.N., 2003, ANGEW CHEM, V115, P2116
[7]   Colorimetric enantiodiscrimination of α-amino acids in protic media [J].
Folmer-Andersen, JF ;
Lynch, VM ;
Anslyn, EV .
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 2005, 127 (22) :7986-7987
[8]   High-throughput measurement of the enantiomeric excess of chiral alcohols by using two enzymes [J].
Li, Z ;
Bütikofer, L ;
Witholt, B .
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION, 2004, 43 (13) :1698-1702
[9]  
Li Z., 2004, ANGEW CHEM, V116, P1730
[10]   Citrate and calcium determination in flavored vodkas using artificial neural networks [J].
McCleskey, SC ;
Floriano, PN ;
Wiskur, SL ;
Anslyn, EV ;
McDevitt, JT .
TETRAHEDRON, 2003, 59 (50) :10089-10092