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Plants produce complex small molecules — natural products — that exhibit anticancer, antimalarial and antimicrobial activity. These molecules play a key role in human medicine. However, plants typically produce these compounds in low quantities, and harvesting plant natural products is frequently expensive, time-consuming and environmentally damaging. Plant cell culture provides a renewable, easily scalable source of plant material. In this chapter we discuss the successes and pitfalls associated with natural product production in plant cell cultures. [ABSTRACT FROM AUTHOR]

Today we use many drugs produced by microorganisms. However, when these drugs were discovered it was found that the yields were low and a substantial effort had to be put in to develop commercially viable processes. A key part of this endeavor was the studies of the nutritional and the engineering parameters. In this chapter, the basic principles of optimizing the nutritional and engineering aspect of the production process are described with appropriate examples. It was found that two critical components of nutritional medium, carbon and nitrogen source regulated the synthesis of the compounds of interest. Rapidly utilizable carbon source such as glucose supported the growth but led to catabolite repression and alternative carbon sources or methods of addition had to be devised. Inorganic nitrogen sources led to undesirable changes in pH of the medium. Organic nitrogen sources could influence the yields positively or negatively and had to be chosen carefully. Essential nutrients like phosphates often inhibited the synthesis and its concentration had to be maintained below the inhibitory levels. On many occasions, trace nutrients like metal ions and vitamins were found to be critical for good production. Temperature and pH were important environmental variables and their optimum values had to be determined. The media were designed and optimized initially with ‘one variable at a time' approach and later with experimental design based on statistics. The latter approach is preferred because it is economical, considers interactions between medium components and allows rapid optimization of the process. The engineering aspects like aeration, agitation, medium sterilization, heat transfer, process monitoring and control, become critical as the process is scaled-up to the production size. Aeration and agitation are probably the most important variables. In many processes dissolved oxygen concentration had to be maintained above a critical value to obtain the best yields. The rheological properties of fermentation broth significantly affect the aeration and mixing efficiency. The removal of heat from the large fermentors can be difficult under certain conditions. However, new designs of impellers, availability of sensors to monitor important physiological and process variables and advent of computers have facilitated successful scale-up of fermentation processes. [ABSTRACT FROM AUTHOR]

Microbes have been good to us. They have given us thousands of valuable products with novel structures and activities. In nature, they only produce tiny amounts of these secondary metabolic products as a matter of survival. Thus, these metabolites are not overproduced in nature, but they must be overproduced in the pharmaceutical industry. Genetic manipulations are used in industry to obtain strains that produce hundreds or thousands of times more than that produced by the originally isolated strain. These strain improvement programs traditionally employ mutagenesis followed by screening or selection; this is known as ‘brute-force' technology. Today, they are supplemented by modern strategic technologies developed via advances in molecular biology, recombinant DNA technology, and genetics. The progress in strain improvement has increased fermentation productivity and decreased costs tremendously. These genetic programs also serve other goals such as the elimination of undesirable products or analogs, discovery of new antibiotics, and deciphering of biosynthetic pathways. [ABSTRACT FROM AUTHOR]

In this survey the impact of the virtual screening concept is discussed in the field of drug discovery from nature. Confronted by a steadily increasing number of secondary metabolites and a growing number of molecular targets relevant in the therapy of human disorders, the huge amount of information needs to be handled. Virtual screening filtering experiments already showed great promise for dealing with large libraries of potential bioactive molecules. It can be utilized for browsing databases for molecules fitting either an established pharmacophore model or a three dimensional (3D) structure of a macromolecular target. However, for the discovery of natural lead candidates the application of this in silico tool has so far almost been neglected. There are several reasons for that. One concerns the scarce availability of natural product (NP) 3D databases in contrast to synthetic libraries; another reason is the problematic compatibility of NPs with modern robotized high throughput screening (HTS) technologies. Further arguments deal with the incalculable availability of pure natural compounds and their often too complex chemistry. Thus research in this field is time-consuming, highly complex, expensive and ineffective. Nevertheless, naturally derived compounds are among the most favorable source of drug candidates. A more rational and economic search for new lead structures from nature must therefore be a priority in order to overcome these problems. Here we demonstrate some basic principles, requirements and limitations of virtual screening strategies and support their applicability in NP research with already performed studies. A sensible exploitation of the molecular diversity of secondary metabolites however asks for virtual screening concepts that are interfaced with well-established strategies from classical pharmacognosy that are used in an effort to maximize their efficacy in drug discovery. Such integrated virtual screening workflows are outlined here and shall help to motivate NP researchers to dare a step towards this powerful in silico tool. [ABSTRACT FROM AUTHOR]

Natural products have historically been a rich source of lead molecules in drug discovery. However, natural products have been de-emphasized as high throughput screening resources in the recent past, in part because of difficulties in obtaining high quality natural products screening libraries, or in applying modern screening assays to these libraries. In addition, natural products programs based on screening of extract libraries, bioassay-guided isolation, structure elucidation and subsequent production scale-up are challenged to meet the rapid cycle times that are characteristic of the modern HTS approach. Fortunately, new technologies in mass spectrometry, NMR and other spectroscopic techniques can greatly facilitate the first components of the process — namely the efficient creation of high-quality natural products libraries, bimolecular target or cell-based screening, and early hit characterization. The success of any high throughput screening campaign is dependent on the quality of the chemical library. The construction and maintenance of a high quality natural products library, whether based on microbial, plant, marine or other sources is a costly endeavor. The library itself may be composed of samples that are themselves mixtures — such as crude extracts, semi-pure mixtures or single purified natural products. Each of these library designs carries with it distinctive advantages and disadvantages. Crude extract libraries have lower resource requirements for sample preparation, but high requirements for identification of the bioactive constituents. Pre-fractionated libraries can be an effective strategy to alleviate interferences encountered with crude libraries, and may shorten the time needed to identify the active principle. Purified natural product libraries require substantial resources for preparation, but offer the advantage that the hit detection process is reduced to that of synthetic single component libraries. Whether the natural products library consists of crude or partially fractionated mixtures, the library contents should be profiled to identify the known components present — a process known as dereplication. The use of mass spectrometry and HPLC-mass spectrometry together with spectral databases is a powerful tool in the chemometric profiling of bio-sources for natural product production. High throughput, high sensitivity flow NMR is an emerging tool in this area as well. Whether by cell based or biomolecular target based assays, screening of natural product extract libraries continues to furnish novel lead molecules for further drug development, despite challenges in the analysis and prioritization of natural products hits. Spectroscopic techniques are now being used to directly screen natural product and synthetic libraries. Mass spectrometry in the form of methods such as ESI-ICRFTMS, and FACS-MS as well as NMR methods such as SAR by NMR and STD-NMR have been utilized to effectively screen molecular libraries. Overall, emerging advances in mass spectrometry, NMR and other technologies are making it possible to overcome the challenges encountered in screening natural products libraries in today's drug discovery environment. As we apply these technologies and develop them even further, we can look forward to increased impact of natural products in the HTS based drug discovery. [ABSTRACT FROM AUTHOR]

Drugs developed from microbial natural products are in the fundaments of modern pharmaceutical companies. Despite decades of research, all evidences suggest that there must remain many interesting natural molecules with potential therapeutic application yet to be discovered. Any efforts to successfully exploit the chemical diversity of microbial secondary metabolites need to rely heavily on a good understanding of microbial diversity, being the working hypothesis that maximizing biological diversity is the key strategy to maximizing chemical diversity. This chapter presents an overview of diverse topics related with this basic principle, always in relation with the discovery of novel secondary metabolites. The types of microorganisms more frequently used for natural products discovery are briefly reviewed, as well as the differences between terrestrial and marine habitats as sources of bioactive secondary metabolite producers. The concepts about microbial diversity as applied to prokaryotes have evolved in the last years, but recent data suggest the existence of true biogeographic patterns of bacterial diversity, which are also discussed. Special attention is dedicated to the existing strategies to exploit the microbial diversity that is not easy to tackle by conventional approaches. This refers explicitly to the current attempts to isolate and cultivate the previously uncultured bacteria, including the application of high throughput techniques. Likewise, the advances of microbial molecular biology has allowed the development of metagenomic approaches, i.e., the expression of biosynthetic pathways directly obtained from environmental DNA and cloned in a suitable host, as another way of accessing microbial genetic resources. Also, approaches relying on the genomics of metabolite producers are reviewed. [ABSTRACT FROM AUTHOR]

The enormous chemical diversity and the broad range of biological activities of secondary metabolites raise many questions about their role in nature and the specific traits leading to their evolution. The answers to these questions will not only be of fundamental interest but may also provide lessons that could help to improve the screening protocols of pharmaceutical companies and strategies for rational secondary metabolite engineering. In this review, we try to dissect evolutionary principles leading to the emergence, distribution, diversification and selection of genes involved in secondary metabolite biosyntheses. We give an overview about recent insights into the evolution of the different types of polyketide synthases (PKS) in microorganisms and plants and highlight unique mechanisms underlying polyketide diversity. Although phylogenetic and experimental data have significantly increased our knowledge about the role and evolution of secondary metabolites in the last decades there is still much dissent about the impact of natural selection. In order to understand the evolution towards metabolic diversity we therefore need more thorough investigations of the ecological role of secondary metabolites in the future. [ABSTRACT FROM AUTHOR]

An overview is given on current efforts in drug development based on plant-derived natural products. Emphasis is on projects which have advanced to clinical development. Therapeutic areas covered include cancer, viral infections including HIV, malaria, inflammatory diseases, nociception and vaccine adjuvants, metabolic disorders, and neurodegenerative diseases. Aspects which are specific to plant-based drug discovery and development are also addressed, such as supply issues in the commercial development, and the Convention on Biological Diversity. [ABSTRACT FROM AUTHOR]

This chapter is designed to demonstrate that compounds derived from nature are still in the forefront of drug discovery in diseases such as microbial and parasitic infections, carcinomas of many types and control of cholesterol/lipids in man. In each disease area we have provided short discussions of past, present and future agents, in general only considering compounds currently in clinical Phase II or later, that were/are derived from nature's chemical skeletons. Finishing with a discussion of the current and evolving role(s) of microbes (bacteria and fungi) in the production of old and new agents ostensibly produced by higher organisms. [ABSTRACT FROM AUTHOR]

The complete sequences of hundreds of microbial genomes have provided drug discovery pipelines with thousands of new potential drug targets. Their availability has also stimulated the development of a variety of innovative approaches that allow functional studies to be performed on the entire genome of an organism. This chapter describes how these approaches have been applied to the analysis of host-pathogen interactions and discusses how such studies might facilitate the development of new antibiotics. [ABSTRACT FROM AUTHOR]

The increasing availability of various system-level, or so-called ‘omics', datasets, in concert with existing data from the primary research literature, is facilitating the development of genome-scale metabolic models for many organisms. By incorporating the metabolic reaction stoichiometry as well as other physicochemical properties into systemic network reconstructions, these models account for the constraints that restrict an organism's phenotypic behavior. Accordingly, unlike many contemporary modeling strategies, this constraint-based modeling approach does not attempt to predict network behavior exactly; rather, it seeks to clearly distinguish those network states that a system can achieve from those that it cannot. A variety of analytical tools have been designed and developed to probe these models, thus enabling studies that investigate the metabolic capabilities of a number of organisms, that generate and test experimental hypotheses, and that predict accurately metabolic phenotypes and evolutionary outcomes. This chapter introduces the concepts that underlie the constraint-based modeling approach, and describes several of its applications with an emphasis on those potentially relevant to the drug development field. In addition, while this chapter focuses on the primary application of the constraint-based approach to date, namely in modeling metabolic networks, the latter sections of the chapter discuss its relatively recent application to modeling other cellular systems. Finally, the chapter concludes with an assessment of future directions focusing on the efforts that will be required to utilize the constraint-based approach in generating a holistic model of a viable organism. [ABSTRACT FROM AUTHOR]

Infectious diseases are still the number one killer of human beings. Even in developed countries, infectious diseases continue to be a major health threat. This article explores a conceptual framework for understanding infectious diseases in the context of the complex dynamics between microbe and host, and explores theoretical strategies for anti-infectives. The central pillar of this conceptual framework is that biological robustness is a fundamental property of systems that is closely interlinked with the evolution of symbiotic host-pathogen systems. There are specific architectural features of such robust yet evolvable systems and interpretable trade-offs between robustness, fragility, resource demands, and performance. This concept applies equally to both microbes and host. Pathogens have evolved to exploit the host using various strategies as well as effective escape mechanisms. Modular pathogenicity islands (PAI) derived from horizontal gene transfer, highly variable surface molecules, and a range of other countermeasures enhance the robustness of a pathogen against attacks from the host immune system. The host has likewise evolved complex defensive mechanisms to protect itself against pathogenic threats, but the host immune system includes several trade-offs that can be exploited by pathogens and induces undesirable inflammatory reactions. Due to the complexity of the dynamics emerging from the interactions of multiple microbes and a host, effective counter-measures require an in-depth understanding of system dynamics as well as detailed molecular mechanisms of the processes that are involved. [ABSTRACT FROM AUTHOR]

Toxicology is the perturbation of metabolism by external factors such as xenobiotics, environmental factors or drugs. As such, toxicology covers a broad range of fields from studies of the whole organism responses to minute biochemical events. Mechanistic toxicogenomics is an attempt to harness genomic tools to understand the physiological basis for a toxic event based on an analysis of transcriptional, translational or metabolomic profiles. These studies are complicated by non-toxic adaptive responses in transcript, protein or metabolite expression levels that have to be distinguished from those that are proximally related to the toxic event. Substantial progress has been made on the identification of biomarkers and the establishment of screens derived from such toxicogenomics studies. The ultimate goal, of course, is predictive toxicogenomics, which is an attempt to infer the likelihood of occurrence of a toxic event with exposure to a new agent based upon comparative responses with large databases of gene, protein or metabolite expression data. Gene expression databases are currently limited by the fact that measurable toxic phenotypes generally precede or at best coincide with the earliest observable changes in transcriptional profiles. Unfortunately, predictive protein databases have been limited by technical difficulties. Metabonomics-based databases, which would probably have the highest predictive value, are limited in turn by the inability to perform high dose studies in humans. This chapter will conclude by reviewing those elements of toxicogenomics that apply specifically to the development of anti-infectives and the potential for accuratelymodelling the toxicity of future drugs. [ABSTRACT FROM AUTHOR]

This chapter will review specific applications of microarray technology and related data analysis strategies in antibacterial research and development. We present examples of microarray applications spanning the entire antibiotics research and development pipeline, from target discovery, assay development, pharmacological evaluation, to compound safety studies. This review emphasizes the utility of microarrays for a systematic evaluation of novel chemistry as antibiotic agents. Transcriptional profiling has revolutionized the process of target elucidation and has the potential to offer substantial guidance in the identification of new targets. Microarrays will continue to be a workhorse of anti-infectives discovery programs ranging from efficacy assessments of antibiotics (‘forward pharmacology') to drug safety evaluations (‘toxicogenomics'). [ABSTRACT FROM AUTHOR]

Proteins are often referred to as the molecular workhorses of the cell since they are responsible for the majority of functions within a living cell. From the generation of energy, to the replication of DNA, proteins play a central role inmost cellular functions. Because of their importance to cellular viability, proteins are commonly the target of therapeutic drugs, ranging from antimicrobial to anticancer drugs. With the rise of drug resistant and multi-drug resistant forms of many diseases, it has become increasingly important to develop new strategies to identify alternative drug targets. One such strategy arises from the analysis of protein networks. Protein networks help define individual proteins within the context of all other cellular proteins. In this chapter we discuss methods for the identification and analysis of genome-wide protein networks, and discuss how protein networks can be used to aid the identification of novel drug targets. [ABSTRACT FROM AUTHOR]

This chapter describes the basic principles of Metabolic Control Analysis (MCA) which is a quantitative methodology to evaluate the importance and relative contribution of individual metabolic steps in the overall functioning of a particular system. The control on the flux through a metabolic pathway or subsystem can be quantified by the control coefficients of the individual enzymes or components which reflects the extent to which the component is rate-limiting. The perturbation of an individual step is measured by its elasticity coefficient. The effect of perturbation of a single step on the entire pathway or subsystemis, in turn, measured by the response coefficient. Differential control analysis can be used to compare flux through a single metabolic pathway in a pathogen with the same pathway in its host to identify uniquely vulnerable steps with the greatest potential for specifically inhibiting flux through the pathogen metabolic pathway. The utility of this methodology is illustrated with the glycolysis in Trypanosomes and with oncogenic signaling. [ABSTRACT FROM AUTHOR]

This chapter describes a three-stage approach to target identification based upon subsystem analysis. Subsystems analysis focuses on related metabolic pathways as a unit and is a biochemically-informed approach to target selection. The process involves three stages of analysis; the first stage, selection of the target subsystem, is guided by information about its essentiality and on the predicted vulnerability of the targeted pathway or enzyme to inhibition. The second stage involves analysis of the target subsystem by means of comparative genomics, including genome context analysis and metabolic reconstruction. The third stage evaluates the selection of the specific target genes within the subsystem by target prioritization and validation. The whole process allows for a careful consideration of spectrum, drugability, biological rationale and the metabolic role of the specific target within the context of an integrated circuit within a specific metabolic pathway. [ABSTRACT FROM AUTHOR]

Metabolite profiling has been carried out for decades and is as such not a new research area. However, the field has attracted increasing attention in the last couple of years, and the term metabolome is now often used to describe the complete pool of metabolites associated with an organism at any given time. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the best candidates for comprehensive analysis of the metabolome and the application of these technologies is presented in this chapter. In this relation, the importance of efficient metabolite screening for discovery of novel drugs is discussed. Related to metabolite profiling, the principals underlying the application of labeled substrates to quantify in vivo metabolic fluxes are introduced, and the chapter is concluded by discussing the perspectives of metabolite measurements in systems biology. [ABSTRACT FROM AUTHOR]

Proteomic profiling provides a global view of the protein composition of the cell. In contrast to the static nature of the genome sequence, which provides the blueprint for all protein-based cellular building blocks, the proteome is highly dynamic. The protein composition is constantly adjusting to facilitate survival, growth, and reproduction in an ever-changing environment. In a quest to understand the regulation of cellular networks in bacteria and the role of individual proteins in the adaptation process, the proteomic response to stress and starvation was analyzed in wild-type and mutant strains. The knowledge derived from these proteomic studies was applied to investigating the bacterial response to antibiotics. It was found that proteomics presents a powerful tool for hypothesis generation regarding antibiotic mechanism of action. [ABSTRACT FROM AUTHOR]

Chemical genetics combines chemistry with biology as a means of exploring the function of unknown proteins or identifying the proteins responsible for a particular phenotype. Chemical genetics is thus a valuable tool in the identification of novel drug targets. This chapter describes the application of chemical genetics in traditional and systems-based approaches to drug target discovery and the tools/approaches that appear most promising for guiding future pharmaceutical development. [ABSTRACT FROM AUTHOR]

Systems biology offers the potential for more effective selection of novel targets for anti-infective drugs. In contrast to conventional reductionist biology, a systems approach allows targets to be viewed in a wider context of the entire physiology of the cell, with the potential to identify key susceptible nodes and to predict synergistic effects of blocking multiple pathways. In addition to the holistic perspective provided by systems biology, the emphasis on quantitative analysis is likely to add further rigour to the process of target selection. Systems biology also offers the potential to incorporate different levels of information into the selection process. Consideration of data from microbial population biology may be important in the context of predicting future drug-resistance profiles associated with targeting a particular pathway, for example. This chapter provides an overview of major themes in the developing field of systems biology, summarising the core technologies and the strategies used to translate datasets into useful quantitative models capable of predicting complex biological behaviour. [ABSTRACT FROM AUTHOR]