4th EucheMs chemistry congress

wednesday, 29-Aug 2012
s611
chem. Listy 106, s587–s1425 (2012)
Analytical chemistry Electrochemistry, Analysis, sample manipulation
New analytical methodologies
o - 2 6 5
SiMuLtAneouS or inCreMentAL
identifiCAtion of reACtion SySteMS?
J. BiLLeter 1 , S. SrinivASAn 1 , d. Bonvin 1
1 Ecole Polytechnique Fédérale de Lausanne (EPFL), Automatic
Control Laboratory (LA), Lausanne, Switzerland
Identification of kinetic models is essential for monitoring,
control and optimization of industrial processes. Robust kinetic
models are often based on first-principles and described by
differential equations. Identification of reaction kinetics, namely
rate expressions and rate parameters, represents the main
challenge in building first-principles models. The identification
task can be performed in one step via a simultaneous approach or
over several steps via an incremental approach.
In the simultaneous approach, a kinetic model that
encompasses all reactions is postulated and the corresponding
parameters are estimated by comparing predicted and measured
concentrations. The procedure is repeated for all combinations of
model candidates and the combination with the best fit is typically
selected. This approach can handle complex reaction rates and
leads to optimal parameters in the maximum-likelihood sense.
However, it is computationally costly when several candidates are
available for each reaction, and convergence problems can arise
for poor initial guesses. Furthermore, simultaneous identification
often leads to high parameters correlation, and a structural
mismatch in one part of the model can result in errors in all
estimated parameters.
In the incremental approach, the identification task is
decomposed into sub-problems of lower complexity. In the
differential method, reaction rates are first estimated by
differentiation of measured concentrations. Then, each estimated
rate profile is used to discriminate between several model
candidates, and the candidate with the best fit is selected.
However, because of the bias introduced in the differentiation
step, the estimated rate parameters are not statistically optimal. In
the integral method, measured concentrations are first transformed
to ‘experimental extents’. Subsequently, postulated rate
expressions are integrated for each reaction individually and rate
parameters are estimated by comparing predicted and
experimental extents.
This contribution reviews the simultaneous and incremental
methods of identification and compares them via simulated
examples taken from homogeneous and heterogeneous chemistry.
Keywords: Kinetics; Kinetic resolution; Industrial Chemistry;
Analytical Methods;
New analytical methodologies
4 th EucheMs chemistry congress
o - 2 6 6
SACChAride ProBeS for enzyMe ASSAyS And
MoLeCuLAr LoGiC
A. SChiLLer 1
1 Friedrich-Schiller-University Jena, Institute for Inorganic and
Analytical Chemistry, Jena, Germany
A two-component glucose sensing concept based on anionic
fluorescent dyes as reporters and boronic acid-appended
bipyridinium salts as receptors was formulated by Singaram et
al. [1–5] Going beyond glucose monitoring, real-time label-free
fluorescent enzyme assays have been developed for sucrose
phosphorylase (SPO) and phosphoglucomutase (PGM). [1, 2, 6] The
assays are suitable for high-throughput screening of novel
carbohydrate enzymes for industrial applications. [9] Glycoside
phosphorylases and transglycosidases are biocatalysts for the
glyco-sylation of small molecules which can be assayed with the
saccharide probes. [10] These probes can also perform Boolean logic
operations for “chemical computing”. The combination of a
boronic acid-appended viologen and perylene diimide was able
to perform a complementary implication (IMP) / notimplication
logic function. Fluorescence quenching and recovery with
fructose was analyzed with a conventional plate reader and by
fluorescence correlation spectroscopy on few molecule level of
the reporting dye. [11] IMP and FALSE operations are able to form
adder, subtractor and multiplicator logic systems, based on the
saccharide probe and fructose.
references:
1. A. Schiller, B. Vilozny, R. A. Wessling, B. Singaram, in
Reviews in Fluorescence 2009, Springer, 2011, 155.
2. A. Schiller, in Molecules at Work. Selfassembly,
Nanomaterials, Molecular Machinery (Ed.: B. Pignataro),
Wiley-VCH, Weinheim, 2012, 315.
3. B. Vilozny, A. Schiller, R. A. Wessling, B. Singaram,
J. Mater. Chem. 2011, 21, 7589.
4. A. Schiller, R. A. Wessling, B. Singaram, Angew. Chem.,
Int. Ed. 2007, 46, 6457.
5. A. Schiller, B. Vilozny, R. A. Wessling, B. Singaram,
Anal. Chim. Acta. 2008, 627, 203.
6. B. Vilozny, A. Schiller, R. A. Wessling, B. Singaram, Anal.
Chim. Acta. 2009, 649, 246.
9. www.novosides.eu.
10. T. Desmet, W. Soetaert, P. Bojarová, V. Kren,
L. Dijkhuizen, V. Eastwick-Field, A. Schiller, Chem. Eur.
J.2012, in press.
11. M. Elstner, K. Weisshart, K. Müllen, A. Schiller, J. Am.
Chem. Soc. 2012, DOI: 10.1021/ja303214r
Keywords: Sensors; Supramolecular chemistry; Enzyme
catalysis; Fluorescent probes; Fluorescence spectroscopy;
AUGUst 26–30, 2012, PrAGUE, cZEcH rEPUbLIc