Proceedings of the

1st Beilstein ESCEC Symposium

Experimental Standard Conditions of Enzyme Characterization

5 – 8 October 2003 in Rüdesheim, Germany

The articles of the conference proceedings are available in PDF format.

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The Beilstein-Institut organises and sponsors scientific meetings, workshops and seminars, with the aim to catalyse advances in chemical and biological science by facilitating the interdisciplinary exchange and communication of ideas amongst the attendees.

Functional characterization of enzymes and the subsequent computational analysis and modelling of the cellular metabolism and the interaction of cells within tissues and organs led to the foundation of a new branch within the life sciences called systems biology. At the present time, data from metabolic simulations show broad value ranges with high uncertainty because the accessible experimental data have been obviously generated under non-standardized experimental conditions. Successful biological analysis requires, however, comparable and reliable data from both enzyme and physiological interactions collected under standardized experimental conditions. The standardization or recommendation of experimental conditions firstly needs broad discussions within the scientific community, which hopefully will lead to enough common acceptance so that each researcher will carry out his/her experiments in accord with these recommendations.

Participants, as well as speakers were confronted with the following complex questions from experimental and theoretical enzymology:

  • are any standards used in the field of functional characterization of enzymes?
  • are there any standard procedures or instructions for experimental conditions?
  • is it possible to define laboratory procedures for common use?
  • do current repositories for enzyme characterization data meet the demands of users?
  • which data types for metabolic simulations are necessary?
  • are there any demands for the transfer of standardized experimental data to journals or databases?

Over the three days of the workshop, the participants not only heard excellent talks, took part in lively discussions, but in the time between the official sessions of the scientific program, exchanged ideas and thoughts and generally made a valuable and personal contribution to find a way out of the dilemma mentioned above. Whilst this meeting did not find answers to all questions, it succeeded in initiating a dialog between scientists from the different areas of enzymology. One notable outcome is the foundation of the STRENDA Commission under the auspices of the Beilstein-Institut.

We would like to thank particularly the authors who provided us with written versions of the papers that they presented. Special thanks also to all those involved with the preparation and organization of the workshop, to the chairmen who directed us successfully through the sessions, and to the speakers and participants for their contribution in making this workshop a success.

Frankfurt/Main, October 2004

Martin G. Hicks
Carsten Kettner


Functional characterization of enzymes plays an essential role in one of the major aims of proteomics research: the modelling of sections of the cellular metabolism with a view to being able to model the whole cellular metabolism and the interaction of cells within tissues and organs. With these purposes in mind, the scientific community established a new branch within the life sciences, called systems biology. However, meaningful modelling by necessity requires comparable and reliable data from standardized enzyme characterizations. From a short, but detailed, investigation of the BRENDA database, it is shown here that the quality of experimental data of enzymes is insufficient for the needs of theoretical biology. The first step to remedy the situation is to ensure that measurements carried out on enzymes are done so under standard conditions and that all the important information is recorded. With the aim of arriving at an acceptable set of recommendations for experimental conditions, the Beilstein Institut has initiated broad discussions within the scientific community and is further willing to organize and present them as long as appropriate and there is sufficient support.


Sinead Boyce, Keith Tipton and Andrew G. Mcdonald

Department of Biochemistry, Trinity College, Dublin, Ireland.

Classification of enzymes according to the reaction(s) catalysed is a relatively straightforward procedure, as it deals with more-or-less factual data. However, attempting to add meaning to those data by adding metabolic or kinetic information takes one into the field of parameters rather than absolutes. Thermodynamic data have been assembled for a number of reactions, but the direction in which a reaction is favoured in isolation does not necessarily mean that that will be the direction of the reaction in cellular metabolism; there are many metabolic examples of enzyme reactions proceeding in the thermodynamically less-favoured direction. Attempts to predict "missing enzymes" from metabolic pathways should also be treated with caution, since there are several cases where such guesses have proven to be wide of the mark. Incorporation of kinetic data requires the definition of standard conditions, which should ideally bear some relevance to the physiological situation in which the enzyme operates. However, not all enzymes operate under the same physiological conditions and there are, as yet, no universally accepted standard conditions, or sets of conditions, of temperature, pH, ionic strength etc. for the collection of such data.


Hans Georg Bock, Stefan Körkel, Ekaterina Kostina and Johannes P. Schlöder

Interdisciplinary Center for Scientific Computing (IWR), University of Heidelberg.

This paper deals with the identification of kinetic parameters in enzymecatalytic processes. Experience shows that the experiments performed do no deliver measurement data sufficient for the identification of parameters. New optimal experiments are needed. We suggest effective algorithms and software for parameter estimation and design of optimal experiments, based on multiple shooting and specially tailored, structure-exploiting reduced Gauss-Newton and SQP methods. The methods are applied to optimal experimental design and parameter estimation in enzyme catalytic processes.


Alisdair R. Fernie1 and Lee J. Sweetlove2

1Max-Planck-Institut für Molekulare Pflanzenphysiologie, Golm, Germany.
2Department of Plant Science, University of Oxford, Oxford, U.K.

In recent years the focus of experimental biology has shifted from reductionist towards more holistic approaches. This shift has been driven by the development of genetic tools that have allowed the creation of an unprecedented base of genetic diversity and by the development of technologies allowing the rapid determination of thegenetic, transcript, protein and metabolite complements of biological systems. Here we will describe experiences with broad-range metabolite analysis of potato and tomato development over the last few years: we will furthermore describe what information can be garnered from these experiments as well as describing recent attempts to analyse systems at the level of more than one molecular entity. Finally, the need for interdisciplinary collaboration and a perspective for this research field will be discussed.


Hartmut Schlüter1, Joachim Jankowski1, Achim Thieman1, Jana Rykl1, Sandra Kurzawski1 and Dieter Runge2

1Nephrology, Charité - University Medicine Berlin; Campus Benjamin Franklin, Berlin, Germany.
2Immunology, University Rostock, Faculty of Medicine, Rostock, Germany.

Enzymatic activities in complex protein fractions are often detected with spectroscopic methods, necessitating substrates, which are modified by chromogenic or fluorogenic agents or with radioactive isotopes. However, both approaches lack the control of the identity of the reaction products risking incorrect positive results. Mass spectrometry-assisted enzyme assays allow the direct and sensitive analysis of the reaction products of the enzymatic conversion of authentic natural substrates and give confidence about the identity of the reaction products. The newly developed mass-spectrometryassisted enzyme screening (MES) method enables the determination of enzyme activities by mass spectrometry even in raw extracts and cell lysates without sample pre-treatment prior to MS.


Hermann-Georg Holzhütter

Humboldt-University Berlin, Medical School (Charité), Institute of Biochemistry, Berlin, Germany.

Almost all chemical reactions and transport processes in a cell are catalysed by specific enzymes and transport proteins, respectively. Kinetic characterization of these auxiliary proteins is a necessary prerequisite for understanding the dynamics and regulation of cellular reactions networks. Progress-curve analysis, i.e. estimation of kinetic parameters by fitting of integrated rate laws to the time-course of a biochemical reaction, allows an efficient kinetic characterization of enzymes. This article outlines the mathematical fundamentals of progress-curve analysis and provides examples for the application of this method in enzyme kinetics and system biology.


Stefan Schuster1 and Ionela Zevedei-Oancea2

1Friedrich Schiller University Jena, Faculty of Biology and Pharmaceutics, Section of Bioinformatics, Jena, Germany.
2Humboldt University Berlin, Section of Theoretical Biophysics, Berlin, Germany.

The analysis of network properties of metabolic systems has recently attracted increasing interest. While enzymes are usually considered to be specific catalysts, many enzymes in living cells are characterized by broad substrate specificity. Here we discuss some aspects of the treatment of such multifunctional enzymes in metabolic pathway analysis, for example, their suitable representation. The fact that the choice of independent functions of multifunctional enzymes is nonunique is explained. We comment on the annotation of such enzymes in metabolic databases and give some suggestions to improve this. We then explain the proper definition of metabolic pathways (elementary flux modes) for systems involving multifunctional enzymes and discuss some ontological problems.


Jacky L. Snoep1,2, Brett G. Olivier1 and Hans V. Westerhoff2

1Triple-J group, Department of Biochemistry, University of Stellenbosch.
2Cellular BioInformatics, Free University, Amsterdam.

Rapid developments in bioinformatics over the last decade, coupled with a dramatic increase in the amount of available, quantitative data has necessitated the need for good analysis tools to quantitatively understand the functioning of biological systems. Detailed kinetic models offer one such tool and while such models have been developed since the 1960s little attention has been paid to the presentation and conservation of such models. Here we focus on the JWS Online project and its role in 1) offering a web based tool for analysis of kinetic models, 2) acting as a repository for published kinetic models and 3) facilitating the reviewing of new models. In addition we advocate the use of a specific type of kinetic models, the socalled "Silicon Cell" models ( By elaborating on the process of constructing one such model, based on yeast glycolysis, we illustrate the approach of "modular modelling" and "model combining." This approach is presented as a preferred method to model biological systems, as opposed to the building of single large models.


Kirill Degtyarenko

European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, U.K.

The diversity of objects and concepts in enzymology can be reflected in the number of possible classifications ('ontologies') needed to describe an 'elementary' biochemical event such as an enzymatic reaction: for example, the overall enzymatic reaction (including direction) taking place under physiological conditions; any other enzymatic reaction catalysed by the same enzyme observed in vivo or in vitro; the biochemical pathway of which the reaction is part; the mechanism of the enzymatic reaction; an enzyme itself; any of the subunits of a multimeric enzyme. These are all different classes of entities and as such have to be given their own terms and/or identifiers. In reality, the terminology used in publications or biological databases often is a mixture of terms borrowed from orthogonal (or contradicting) classifications.

In this respect, the Enzyme Nomenclature should provide the ultimate reference, whereas in fact it suffers the same problem. EC numbers form a strict hierarchy of IsA relationships and the enzymes often require re-classification. It is unlikely that in its current form, the Enzyme Nomenclature can cope with the growing demands of the biological and bioinformatics community in the 21st century. A more flexible, but at the same a time a more strictly defined, approach has been pioneered by the Gene Ontology Consortium, which provides controlled vocabulary for molecular functions used to annotate gene products. I am going to discuss the building of an Enzyme Ontology. Here, novel relationships unique to chemical ontologies have to be introduced.


John L. Andreassi and Thomas S. Leyh

Department of Biochemistry, The Albert Einstein College of Medicine, New York.

A worldwide initiative, the goal of which is to place all of nature's globular protein domains within modelling distance of a known threedimensional structure, is underway. The tens of thousands of structures slated to be delivered to the scientific community by the Initiative over the ensuing decade will create an acute need for a complementary program to characterize the functions of these proteins. It is timely to consider the design of such a program.


Ida Schomburg, Antje Chang, Christian Ebeling, Gregor Huhn, Oliver Hofmann and Dietmar Schomburg

CUBIC (Cologne University Bioinformatics Centre), Institute of Biochemistry, Köln, Germany.

BRENDA represents the most comprehensive information system on enzyme and metabolic information, based on primary literature. The database contains data from at least 83,000 different enzymes from 9800 different organisms, classified in approximately 4200 EC numbers. BRENDA includes biochemical and molecular information on classification and nomenclature, reaction and specificity, functional parameters, occurrence, enzyme structure, application, engineering, stability, disease, isolation, and preparation, links, and literature references. The data are extracted and evaluated from approximately 46,000 references, which are linked to PubMed as long as the reference is cited in PubMed. In the last year BRENDA underwent major changes including a large increase in updating speed with more than 50% of all data updated in 2002 or in the first half of 2003, the development of a new EC-tree browser, a taxonomy-tree browser, a chemical substructure search engine for ligand structure, the development of controlled vocabulary and an ontology for some information fields, and a thesaurus for ligand names. The database is accessible free of charge for the academic community at

Analysis of the experimental data stored in BRENDA shows a number of problems that prohibit a systematic comparison and evaluation of experimental protein data. This is caused by the fact that on the one hand, many experimental data are determined in a non-systematic way and that – on the other hand – the existing recommendations on nomenclature are systematically ignored by most authors of biochemical and molecular-biological papers. Examples will be given.


Richard Cammack

Department of Life Sciences, King’s College London, UK.

The aim of systematic nomenclature is to provide a name for each entity, such as a metabolite, an enzyme, or a measured quantity. There are different requirements for biochemical nomenclature, depending on how the name or symbol is to be stored and communicated, by written, printed, or spoken word, as a diagram, or as computer-readable data. Names are often related to biological function, structure or evolutionary relationships; nomenclature follows classification. For interaction with computers and databases, identifiers should be searchable, and referred to an authoritative source. The requirements for nomenclature are distinct from those of a dictionary, where the criterion for inclusion of a word is that it is used. When proposing systematic nomenclature, timely intervention is important, and much effort should be devoted to ensuring acceptance of within the scientific community.