The Beilstein workshops address contemporary issues in the chemical and related sciences by employing an interdisciplinary approach. Scientists from a wide range of areas - often outside chemistry - are invited to present aspects of their work for discussion with the aim of not only to advance science, but also, to enhance interdisciplinary communication.

To set the stage for the workshop, it is useful to consider the development of both natural and life sciences from their early origins in natural philosophy. Technical equipment and methodologies, as well as, the systematizing and cataloguing of phenomena and entities, have always underpinned scientific advances. However, even in science, there can be resistance to change, and it has often taken a generation of overwhelming experimental evidence to swing opinion, and allow new paradigms to be accepted into the collective scientific wisdom. Whilst technology and information are the driving forces for advances, it is interesting to note that the most significant developments often take place at the intersections of different lines of thought.

In the natural sciences the search for a "life-force" has given way to the generalization that biology can be defined as being interdependent "complicated chemistry". To gain the insights that lead to the understanding of complex processes, the usual scientific method is to break down the problem into smaller units, create a model for each of them, and through refinement of the models attempt to develop a unified theory. Whereas initial insight into biological systems can be obtained by modelling the chemistry of the parts of the system, the properties and functions of the components of a biological system are not those of discrete molecular entities; they are dependent on the presence or absence of other components and their behaviours in relation to one another. Thus modelling the system as a whole is a very complicated if not a highly complex task.

One of the most current challenging problems of the natural and life sciences is the understanding and prediction of the biological chemistry of the cell, with particular reference to the role of organic compounds therein. These molecules are the products of highly refined in vivo and in vitro organic syntheses; they have complex biological functions - making up the systems themselves as well as interacting with and perturbing them. It is our belief that advances can only realistically be achieved in an interdisciplinary environment, where the lines of thought of different scientific cultures are related sufficiently to each other that given the right circumstances, interactions can take place and new developments can follow.

By raising the curtain on the 'Chemical Theatre of Biological Systems' and through the performances of players invited from the areas of chemical, biological and information sciences, our aim is that this workshop, supported by the active participation of the audience, will afford new insights into contemporary scientific issues.

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

Frankfurt/Main, July 2005

Martin G. Hicks
Carsten Kettner

As the global emphasis towards more eco-efficient and sustainable practices unfolds before us, so does the new remit for chemistry. We are already applying the principles of this new paradigm to environmentally cleaner and more efficient chemical processes, products and services. This discussion looks more deeply into some of the ways this remit will lead to the evolution of new tools for the molecule maker and how it is poised to revolutionize the way in which synthesis chemists will conduct their programmes in the future.

To understand what chemical genetics is and how it can add value to the drug discovery process we must first consider some of the challenges and needs in the pharmaceutical industry. The process of discovering new drugs is a highly complex, multidisciplinary activity requiring very large investments of time, intellectual capital, and money. Today the average cost of bringing an NCE to market is on the order of $900 million. For every 5000 compounds synthesized only one makes it to the market. Only three of ten drugs generate revenue that meets or exceeds average R&D costs, and 70% of total returns are generated by only 20% of the products. Given this gloomy backdrop it is even more disturbing to learn that despite the proliferation of many new technologies of great potential (and great cost!) pharmaceutical productivity levels have not increased over the last ten years. [...] Working harder is not likely to overcome this productivity gap to deliver more drugs. Working smarter, doing things differently, and focusing on what we actually need to deliver, i.e., knowledge may be a new way to approach the problem. Ultimately, spanning the "knowledge gap" will lead us to the efficient exploitation of the human genome to discover new drugs to meet major medical needs.

The strategies of drug design have changed significantly within the past few decades. Whereas chemistry, biological activity hypotheses and animal experiments dominated drug research, especially in its "golden age", from the sixties to the eighties of the last century, many new technologies have developed over the past 20 years. A vast amount of new drugs was expected to result from combinatorial chemistry and high-throughput screening; however, the yield of new drug candidates was relatively poor. Molecular modelling, virtual screening and 3D structure-based design support the selection and rational design of highaffinity protein ligands. But high affinity to a disease-relevant target is only one important property; in addition, a drug must be orally bioavailable, it should have favourable pharmacokinetics and no unacceptable side effects or toxicity. The following questions are discussed in detail: what are the reasons for the productivity gap between R&D costs and the number of NCE's? Is there a "druggable genome"? Is target focus always best? Is poor ADME the main problem in clinical development? Are we using the right virtual screening tools? What are the main problems in virtual screening and structure-based design? What is wrong and what could we do better?

In drug discovery, active compounds identified by screening or other approaches usually bind to their targets with micromolar or weaker affinities. To become effective drugs, the binding affinities of those compounds need to be improved by three or more orders of magnitude. This task is not trivial if one considers that it needs to be done while satisfying several stringent constraints related to bioavailability, membrane permeability, water solubility, pharmacokinetics, toxicity, etc.. In addition, successful candidates need to exhibit appropriate selectivity and in the case of anti-infectives low susceptibility to mutations associated with drug resistance. These constraints emphasize the need for accurate ways of predicting the various effects of introducing diverse chemical functionalities or scaffold modifications during lead optimization, in particular effects on affinity and selectivity. Recently, it has become evident that the attainment of extremely high affinity, selectivity or adaptability is related to the proportion in which the enthalpy and entropy changes contribute to the binding affinity, and that appropriate control over these variables is critical during the design process. Since modern microcalorimetry provides extremely accurate measurements of the enthalpy and entropy contributions to binding affinity, it provides the basis for the development of rigorous algorithms aimed at: 1) Binding affinity optimization; 2) Improvement of binding selectivity between similar targets; 3) Incorporation of binding adaptability to mutations that cause drug resistance. In this chapter, the role of thermodynamics and enthalpy/entropy profiling in lead optimization will be discussed.

Biosynthetic engineering entails reprogramming the genes involved in the biosynthesis of natural products so as to generate new molecules, which would otherwise not exist in nature. Potentially this approach can be used to providing large numbers of secondary metabolites variants, with improved biological activities, many of which are too complex for effective total synthesis.

The calcium dependent antibiotic (CDA), from Streptomyces coelicolor, is nonribosomal lipopeptide. CDA is structurally related to the therapeutically important antibiotic daptomycin. The CDA producer, S. coelicolor, is also highly amenable to genetic modification, which makes CDA an ideal template for biosynthetic engineering. To this end we have probed the biosynthetic origins of CDA and utilized this information to develop methods which have enabled the first engineered biosynthesis of novel CDA-type lipopeptides. Notably a mutasynthesis approach was developed to generate CDAs with modified arylglycine residues. Active site modification of adenylation domains within the CDA nonribosomal peptide synthases also led to new lipopeptides.

Enzymes are able to catalyse a broad range of chemical transformations not only with impressive rate enhancements but also with both regio- and stereo-selectivity and so are attractive candidates as practical alternatives to traditional small molecule catalysts. With applications as diverse as chemical synthesis, reagents for commercial products and biomedical research, and even therapeutics, there is a great demand for enzymes with both improved activity and novel catalytic function. In theory, the properties of an enzyme can be altered by rational design; however, rational design is greatly hindered in practice by the complexity of protein function. With advances in molecular biology the possibility has arisen that an enzyme with the desired catalytic property can instead be isolated from a large pool of protein variants. Recently directed evolution has been used successfully to modify the substrate or cofactor specificity of an existing enzyme. These experiments, however, are limited to reactions that are inherently screenable or selectable-reactions where the substrate is a peptide or the product is fluorescent or an essential metabolite. What is needed now to realize the power of directed evolution experiments are screening and selection strategies that are generalstrategies that do not limit the chemistry and that can readily be adapted to a new target reaction.

Early success with assays based on binding to transition-state analogues and suicide substrates convinced researchers that it should be possible to engineer proteins to catalyse a broad range of reactions, but it was difficult to translate binding events into read-outs for enhanced catalytic activity. Recently, attention has turned to direct selections for catalytic activity. While strategies ranging from in vitro fluorescence assays to physically linking the enzyme to its substrate have all recently been reported, a general solution to this problem is yet to emerge. In vivo complementation, in which an enzyme is selected based on its ability to complement an essential activity that has been deleted from a wild-type cell, has proven to be one of the most powerful approaches to enzyme evolution. However, complementation assays are limited to natural reactions that are selectable. In this paper we describe our efforts to develop a "chemical complementation" system, which would allow us to control the chemical reaction linked to cell survival, extending complementation approaches to a broad range of chemical transformations.

This paper discusses a range of procedures for virtual screening of chemical databases in which the molecules are represented by 2D fragment bit-strings. Training-sets containing active and inactive molecules from the NCI AIDS dataset and from the Syngenta corporate pesticide file were processed using binary kernel discrimination (BKD), similarity searching, and substructural analysis methods. The effectiveness of these methods was judged by the extent to which active test-set molecules were clustered towards the top of the resultant rankings. The BKD approach was found consistently to yield the best rankings, and its general effectiveness was confirmed in similarity searches of the MDL Drug Data Report database based on multiple reference structures. As well as being effective, BKD is reasonably efficient, and the method would hence appear to be well suited to virtual screening of 2D structure databases.

High-throughput screening is meanwhile well established in most pharmaceutical companies. Although it is routinely applied for most biological targets, several limitations ask for alternative methodologies. This article will describe two different approaches where highly potent ligands for G-protein coupled receptor targets were identified without the application of random high-throughput screening.

Selective small molecule inhibitors of protein function provide a method of studying biological processes that is often complementary to classical genetic and RNAi-based approaches. This article focuses on a recently identified small molecule known as blebbistatin. We review blebbistatin's discovery, biological characterization, selectivity and continuing use. Synthetic chemistry has played a key role in the blebbistatin story and we also review our recent work relating to the asymmetric synthesis and absolute stereochemical assignment of the active enantiomer, (S)-(-)-blebbistatin. High-throughput synthetic approaches to blebbistatin analogues are discussed and a novel analogue is described that has significantly improved physical properties for use in fluorescence-based imaging experiments on live cells. This article looks to emphasize the multidisciplinary nature of research projects in chemical genetics.

The famous Biochemical Pathways wall chart has been converted into a reaction database. The web based retrieval system C@ROL has been interfaced to this BioPath database providing a wide variety of search methods for chemical structures, enzymes, and reactions that can allow one to explore the endogenous metabolism of different species. The database has been made accessible on the internet at: www2.chemie.uni-erlangen.de/services/biopath/index.html and www.mol-net.de/databases/biopath.html.

It is shown how the information in this database can be used to explore enzyme inhibitors as transition state mimics. Furthermore, it is shown how the classification of biochemical reactions based on physicochemical effects at the reaction site, corresponds with the classification of enzymes by the EC code.

Thermodynamic constraints are essential for understanding the behaviour of living systems, but they are far from sufficient, because they allow a wide range of possibilities. Additional constraints imposed by kinetic considerations are often crucial in determining not merely whether a process can occur, but whether it does. Entropies of activation are in principle very useful for analysing experimental properties, but in practice they are rendered almost useless by the impossibility of estimating them accurately from observations spread over a narrow temperature range. Such estimation typically involves extrapolating more than 10-times the range of the data, and involves huge errors. Another common problem in the literature, results from confusion between actual and standard Gibbs energies of reaction: supposedly unfavourable equilibrium constants can suggest that processes necessary for life, such as reduction of sulphate by organisms that use sulphate as a terminal electron acceptor, are impossible; but as long as an organism has efficient mechanisms for maintaining reactant concentrations far from their standard states, a reaction can be driven in either direction regardless of the magnitude of its equilibrium constant. The increasing importance of computer modelling in studying metabolism has now focused attention on the question of how to handle reactions that are essentially irreversible. It has often been assumed that if the reverse reaction is negligible then all the effects of products can be neglected, but that is a potentially serious error: many enzymes are known where product inhibition has important effect on the rate of a reaction that is for practical purposes irreversible.

Correlation-vector representation (CVR) of molecular structure and properties results in an alignment-free descriptor. This facilitates rapid virtual screening of large virtual compound libraries and chemical databases. The approach has a tradition in chemoinformatics and has already led to the identification of several new lead structures. Its foremost application is ligand-based design of activity-enriched, focused compound libraries. Before applying CVR it is essential to consider appropriate descriptor scaling, select a suitable similarity metric and choose meaningful reference molecules. It was demonstrated that there exists no cure-all recipe for this task. Both three-dimensional and two-dimensional CVR and different similarity metrics complement each other yielding an improved hit rate of the combined approach.

Biochemists, molecular biologists, and biophysicists, when confronted with the exquisite matching of natural organisms to their environment, have generally interpreted the properties of proteins as resulting from adaptation. Conversely, since 1962, evolutionary theory has been emphasizing the stochastic nature of neutral evolution and random drift. It is actually possible to explain many of the seemingly adaptive features of proteins as resulting through neutral evolution. In this paper, we use a simple computational model to demonstrate how marginal stability as well as the robustness of proteins to site mutations can be explained by neutral evolution of populations.

Pharmacokinetics and pharmacodynamics in drug discovery are often viewed as simple data generation processes. Candidate compounds are screened for various ADME and physico-chemical properties together with their potency in vitro and their effectiveness in in vivo models. In many cases simple summary parameters are used for comparison between drug candidates and for project decision-making. However, weighing the relevance and importance of such data in isolation or in a qualitative manner is not a simple task. Modelling and simulation provides a framework for integrating these data, providing outputs that contain more information than can be elucidated from the data in isolation. The use of biologically realistic models allows for the separation of the biological and compound-specific components of the pharmacokinetic and pharmacodynamic systems. One can then begin to develop a generic approach that is applicable to the drug discovery process. Physiologically based pharmacokinetic (PBPK) modelling is integral to Roche's approach. PBPK models, by design, are capable of integrating information about various pharmacokinetic processes, including absorption, metabolism and distribution. They can be used not only to estimate summary in vivo pharmacokinetic parameters, but also to predict the complete drug concentration time-course in both plasma and tissues. However, a commonly held view is that PBPK models are complex and data-intensive, and therefore, not applicable to the early phases of drug development. Many of the biochemical and physico-chemical parameters are generated routinely in vitro in the lead generation and optimization phases.

The 2004 Beilstein Bozen Workshop succeeded admirably in its stated goal of bringing together a diverse collection of interdisciplinary researchers, resulting in a stimulating and provocative conference. Despite their broad range of backgrounds - chemistry and biology, mathematics and biophysics, academia and big pharma - the speakers and attendees were united in their desire to understand more fully the dynamic interaction of genes, proteins and other cellular constituents, whether it be to model cellular pathways, or design and synthesize improved libraries of smallmolecule drugs. [...] In this concluding chapter, I will simply aim to put some of these advances into a broader context.