The application of RAGE and GECKO in cell-based target discovery screens

While significant advancements have been made in identifying the genes that comprise the human genome, considerable work remains in gaining an understanding of the functions of these gene products. Improved knowledge of protein function is of particular relevance to the drug discovery process, as the elucidation of new targets that are involved in disease processes will most probably lead to improvements in health care. Reverse genetic approaches that attempt to assign protein function on a gene-by-gene basis are labor intensive and have low throughput. Although forward genetic (function-to-gene) approaches often allow for the more efficient identification of disease-relevant drug targets, most existing methodologies are not capable of sampling the entire genome. Here we review current target discovery strategies and discuss two relatively new technologies, RAGE (random activation of gene expression) and GECKO (genome-wide cellular knockout). These tools provide cellular libraries that can be utilized in genome-wide target discovery screens. Examples are given of how these methodologies may facilitate the identification of new drug targets that are involved in human disease and pathology.     

Deductive genomics: a functional approach to identify innovative drug targets in the post-genome era

The sequencing of the human genome has generated a drug discovery process that is based on sequence analysis and hypothesis-driven (inductive) prediction of gene function. This approach, which we term inductive genomics, is currently dominating the efforts of the pharmaceutical industry to identify new drug targets. According to recent studies, this sequence-driven discovery process is paradoxically increasing the average cost of drug development, thus falling short of the promise of the Human Genome Project to simplify the creation of much needed novel therapeutics. In the early stages of discovery, the flurry of new gene sequences makes it difficult to pick and prioritize the most promising product candidates for product development, as with existing technologies important decisions have to be based on circumstantial evidence that does not strongly predict therapeutic potential. This is because the physiological function of a potential target cannot be predicted by gene sequence analysis and in vitro technologies alone. In contrast, deductive genomics, or large-scale forward genetics, bridges the gap between sequence and function by providing a function-driven in vivo screen of a highly orthologous mammalian model genome for medically relevant physiological functions and drug targets. This approach allows drug discovery to move beyond the focus on sequence-driven identification of new members of classical drug-able protein families towards the biology-driven identification of innovative targets and biological pathways.     

In silico research in drug discovery

Target and lead discovery constitute the main components of today's early pharmaceutical research. The aim of target discovery is the identification and validation of suitable drug targets for therapeutic intervention, whereas lead discovery identifies novel chemical molecules that act on those targets. With the near completion of the human genome sequencing, bioinformatics has established itself as an essential tool in target discovery and the in silico analysis of gene expression and gene function are now an integral part of it, facilitating the selection of the most relevant targets for a disease under study. In lead discovery, advances in chemoinformatics have led to the design of compound libraries in silico that can be screened virtually. Moreover, computational methods are being developed to predict the drug-likeness of compounds. Thus, drug discovery is already on the road towards electronic R&D.     

Unravelling novel intracellular pathways in cell-based assays

The pharmaceutical industry is currently facing several challenges to identify and develop novel drug targets. Traditional drug discovery focussed on a small number of well-characterized gene products. Recently, this picture has changed with the completion of the draft sequence of the human genome, which has led to the identification of thousands of novel genes with unknown or poorly understood function. To cope with this overwhelming number of potential drug target candidates, new strategies for the elucidation of gene function, as well as their involvement in intracellular pathways, are required.     

Fulfilling the promise: drug discovery in the post-genomic era

The genomic era has brought with it a basic change in experimentation, enabling researchers to look more comprehensively at biological systems. The sequencing of the human genome coupled with advances in automation and parallelization technologies have afforded a fundamental transformation in the drug target discovery paradigm, towards systematic whole genome and proteome analyses. In conjunction with novel proteomic techniques, genome-wide annotation of function in cellular models is possible. Overlaying data derived from whole genome sequence, expression and functional analysis will facilitate the identification of causal genes in disease and significantly streamline the target validation process. Moreover, several parallel technological advances in small molecule screening have resulted in the development of expeditious and powerful platforms for elucidating inhibitors of protein or pathway function. Conversely, high-throughput and automated systems are currently being used to identify targets of orphan small molecules. The consolidation of these emerging functional genomics and drug discovery technologies promises to reap the fruits of the genomic revolution.     

High-throughput crystallization and structure determination in drug discovery

High-throughput protein X-ray crystallography offers an unprecedented opportunity to facilitate drug discovery. The key bottlenecks in the path from target gene to three-dimensional protein structure determination are defined. Special emphasis is placed on the concept that drug discovery projects are typically directed at a key protein target whose structure must be solved within a reasonable time frame to have an impact on the drug discovery process. The time-sensitive nature of structural data has placed growing pressure on the need to automate all aspects of protein crystallography, from gene identification to model building and refinement. Current technological innovations and strategies for automation are discussed with respect to the bottleneck they are intended to eliminate.     

Using grid techniques for drug target identification

The completion of the sequencing of the human genome has opened an unprecedented opportunity in the discovery of novel drug targets for disease therapy. However, one of the major challenges facing the drug discovery community is the expanding of data and the need of large-scale computational power in a collaborative environment. Grid techniques can present an architectural framework that aims to provide access to heterogeneous resources in a secure, reliable and scalable manner across various administrative boundaries for drug discovery, which has been a promising strategy for solving large-scale problems in modern pharmaceutical R&D. In this review, we discuss the current applications of Grid technology in drug target protein identification process; and an overview of drug target discovery system architecture, focusing in particular on the data manager service system architecture is also proposed.     

Using grid techniques for drug target identification

The completion of the sequencing of the human genome has opened an unprecedented opportunity in the discovery of novel drug targets for disease therapy. However, one of the major challenges facing the drug discovery community is the expanding of data and the need of large-scale computational power in a collaborative environment. Grid techniques can present an architectural framework that aims to provide access to heterogeneous resources in a secure, reliable and scalable manner across various administrative boundaries for drug discovery, which has been a promising strategy for solving large-scale problems in modern pharmaceutical R&D. In this review, we discuss the current applications of Grid technology in drug target protein identification process; and an overview of drug target discovery system architecture, focusing in particular on the data manager service system architecture is also proposed.     

siRNA for gene silencing: a route to drug target discovery

The identification of RNA interference in mammalian cells, mediated via both virally-derived short interference RNA (siRNA) and endogenously produced microRNA, has revolutionised our understanding of the translational control of gene expression. Indeed, since its initial discovery, siRNA has been rapidly deployed for the elucidation of gene function and the identification of potential drug targets, a process often known as target discovery. In this review, we briefly discuss the mechanism of RNA interference and then critically examine the use of siRNA in target discovery, with a particular emphasis upon issues such as efficacy, selectivity, delivery and application in high-throughput studies.     

Genomics in drug discovery: the best things come to those who wait

The year 2007 has been marked by the maturation of high-throughput technologies that combine automation and miniaturization to enable systematic surveys of genome sequence variation, gene expression and gene function. These technologies have the potential to affect drug discovery in many ways, from target identification and validation, to pinpointing the molecular variants that influence medicine response. In the current climate of declining pharmaceutical R&D productivity, these approaches offer hope, but a price tag is attached. This review covers exciting advances in the field of genomics, and discusses when to act on genomic data versus when to wait for further information.     

Structural biology and drug discovery

It has long been recognized that knowledge of the 3D structures of proteins has the potential to accelerate drug discovery, but recent developments in genome sequencing, robotics and bioinformatics have radically transformed the opportunities. Many new protein targets have been identified from genome analyses and studied by X-ray analysis or NMR spectroscopy. Structural biology has been instrumental in directing not only lead optimization and target identification, where it has well-established roles, but also lead discovery, now that high-throughput methods of structure determination can provide powerful approaches to screening.     

Genome-based drug discovery: prioritizing disease-susceptibility/disease-associated genes as novel drug targets for schizophrenia

The search for new classes of antipsychotics based on novel targets identified from linkage/linkage association in diseased cohorts and microarray approaches using tissue from affected individuals is a high priority in central nervous system research. Genes linked to schizophrenia, a disease affecting 1% of the population, have been identified on nearly every chromosome of the human genome leading to a diverse choice of targets for validation. Interestingly, while the majority of currently used antipsychotic medications act by blocking dopamine receptors, there have been few genetic studies implicating the dopamine receptor family in disease etiology. Recently, four genes have been identified that encode dysbindin, neuroregulin, D-amino acid oxidase and G72, respectively, that support previous studies suggesting that schizophrenia may result from a hypofunction of glutamatergic neurotransmission. Linkage and microarray studies have similarly supported studies implicating the alpha 7 neuronal nicotinic receptor in the etiology of schizophrenia. Microarray studies using brain tissue from schizophrenic patients have shown changes in gene expression that number in the thousands, involving a number of proteins related to synaptic structure and function (PSYN gene group) and cellular metabolism. The majority of these proteins are not traditional drug discovery targets, nor are their functional roles in schizophrenia obvious, providing a challenge to validate them from the drug target identification/drug discovery perspective. The current state-of-the-art in genome-based approaches to schizophrenia, target discovery highlights a need for a multidisciplinary, integrative, null hypothesis-based approach to sort through these novel genes as drug targets.     

Pharmacogenomics and the Drug Discovery Pipeline

One of the key factors in developing improved medicines lies in understanding the molecular basis of the complex diseases we treat. Investigation of genetic associations with disease utilizing advances in linkage disequilibrium-based whole genome association strategies will provide novel targets for therapy and define relevant pathways contributing to disease pathogenesis. Genetic studies in conjunction with gene expression, proteomic, and metabonomic analyses provide a powerful tool to identify molecular subtypes of disease. Using these molecular data, pharmacogenomics has the potential to impact on the drug discovery and development process at many stages of the pipeline, contributing to both target identification and increased confidence in the therapeutic rationale. This is exemplified by the identified association of 5-lipoxygenase-activating protein (ALOX5AP/FLAP) with increased risk of myocardial infarction, and of the chemokine receptor 5 (CCR5) with HIV infection and therapy. Pharmacogenomics has already been used in oncology to demonstrate that molecular data facilitates assessment of disease heterogeneity, and thus identification of molecular markers of response to drugs such as imatinib mesylate (Gleevec) and trastuzumab (Herceptin).Knowledge of genetic variation in a target allows early assessment of the clinical significance of polymorphism through the appropriate design of preclinical studies and use of relevant animal models. A focussed pharmacogenomic strategy at the preclinical phase of drug development will produce data to inform the pharmacogenomic plan for exploratory and full development of compounds. Opportunities post-approval show the value of large well-characterized data sets for a systematic assessment of the contribution of genetic determinants to adverse drug reactions and efficacy. The availability of genomic samples in large phase IV trials also provides a valuable resource for further understanding the molecular basis of disease heterogeneity, providing data that feeds back into the drug discovery process in target identification and validation for the next generation of improved medicines.     

Aptamers as tools for target prioritization and lead identification

The increasing number of potential drug target candidates has driven the development of novel technologies designed to identify functionally important targets and enhance the subsequent lead discovery process. Highly specific synthetic nucleic acid ligands – also known as aptamers – offer a new exciting route in the drug discovery process by linking target validation directly with HTS. Recently, aptamers have proven to be valuable tools for modulating the function of endogenous cellular proteins in their natural environment. A set of technologies has been developed to use these sophisticated ligands for the validation of potential drug targets in disease models. Moreover, aptamers that are specific antagonists of protein function can act as substitute interaction partners in HTS assays to facilitate the identification of small-molecule lead compounds.     

Bioinformatics and the discovery of novel anti-microbial targets

Genomic research is playing a critical role in the discovery of new anti-microbial drugs. The rapid increase in bacterial and eukaryotic genome sequences allows for new and innovative ways for obtaining antimicrobial protein targets. Here, we describe a two level strategy for target identification and validation using computers (in silico). First, large scale comparative analyses of genome sequences were used to identify highly conserved genes which might be essential for in vitro and/or in vivo survival of bacterial pathogens. Lab-based experiments provided confirmation or validation of the hypothesis of in silico essentiality for over 350 individual genes. Over 200 validated, broad spectrum; yet highly specific gene targets, were identified in community infection pathogens. The second part of the target discovery strategy is an in-depth evolutionary, structural and cellular analysis of key drug targets. As an example, phylogenetic and structural analyses suggest that sequence and binding-pocket conservation in FabH (beta-ketoacyl-ACP synthase III) would allow for the development of small molecule inhibitors not only effective against a broad species spectrum of community bacterial pathogens but also as potential new therapies for tuberculosis and malaria.     

The purinome, a complex mix of drug and toxicity targets

Much attention has focused on the development of protein kinases as drug targets to treat a variety of human diseases including diabetes, cancer, hypertension and arthritis. To date, Gleevec is one example of a drug targeting protein that has successfully treated human cancer. Several other protein kinase inhibitors are in clinical development. However, protein kinases are in fact part of a larger collection of some 2000 distinct proteins expressed by the genome that like the protein kinases also bind purines (the purinome), either to be utilized as substrates or as co-factors in the form of NAD, NADP and co-enzyme A. The solution structures of many representative gene family members within the purinome show these proteins bind purines in a similar orientations to that observed in all protein kinases. Several non-protein kinase purine utilizing proteins are established drug targets such as HMG CoA reductase, dihydrofolate reductase, phosphodiesterase and HSP90. Searches of OMIM identifies many purine utilizing enzymes that are associated with inborn errors in metabolism. Inhibition of any one of which by a drug could lead to an undesirable side effect. The purinome is therefore somewhat of a drug discovery mixed blessing. It is a rich source of therapeutic targets, but also contains a large collection of diverse proteins whose inhibition could result in an adverse outcome. Drug discovery within the purinome should therefore encompass strategies that enable broad assessment of selectivity across the entire purinome at the earliest stages of the discovery process. In this article we review the purinome within the context of drug discovery and discuss approaches for avoiding off target binding during the discovery/lead optimization process with particular emphasis on use of proteome mining technology.     

Impact of human genome sequencing for in silico target discovery

The year 2000 stands as a landmark in modern biology: the first draft of the human genome sequence has been completed. For the pharmaceutical industry, this achievement provides tremendous opportunities because the genomic sequence exposes all human drug targets for therapeutic intervention. The challenge for the pharmaceutical companies is to exploit this definitive resource for the identification of potential molecular targets, rapid characterization of their function and validation of their involvement in disease pathology. Bioinformatics approaches provide increasingly crucial tools to systematically support this exploratory target drug discovery activity.     

Zebrafish as a genomics research model

The zebrafish (Danio rerio) is a recent addition to the genomic scientists' repertoire of vertebrate animal model systems. Unlike simple invertebrates such as the fly or the nematode, this teleost maintains the biological and genomic complexity found in higher vertebrates. Furthermore, the zebrafish has many advantageous technical and genomic properties that open the door to experimental approaches not practical using more classical models. The zebrafish genome can be functionally accessed using both forward and reverse genetics based approaches. A notable recent addition to the zebrafish genomics toolbox is the development of morpholino-based antisense gene inhibition for sequence-based 'knockdown' screening. This method offers the opportunity to examine the role of significant subsets of the vertebrate genome for specific gene function in vivo. The zebrafish embryo can rapidly provide critical information for drug target discovery purposes when examined with an emphasis on clinically-relevant biological processes. Finally, the advent of chemical genetics in zebrafish suggests that, in addition to the identification and understanding of drug targets and their biology, this system will be a powerful tool in the direct development of novel pharmaceuticals in the near future.     

Discovery of new small molecules and targets towards angiogenesis via chemical genomics approach

Chemical genetics/genomics is an inter- and multi-disciplinary research engine, which utilizes small molecules to explore the function of genes and accelerate the drug discovery. Bioactive small molecules that are permeable to cellular membrane and bind to its cognate target protein can exert the phenotype changes of the cells or organisms. Functional target proteins of these small molecules have been successfully identified by affinity, genetics and genomics based target identification. The specific molecular recognition of small molecule with target protein has facilitated to decipher the mode of actions of small molecules and developed better drug based on their structure activity relationship. Based on this idea, we have applied chemical genomics to angiogenesis, a new blood vessel formation, resulting in the identification of new small molecules as well as targets. In this review, our application of chemical genomics towards a cellular phenotype, angiogenesis, will be demonstrated.