Combinatorial Chemistry & High Throughput Screening - Volume 10, Issue 8, 2007

The availability of a fully sequenced genome is an enticing biological resource - sufficiently enticing, in fact, to spur the establishment of well over 300 eukaryotic genome-sequencing projects at this time. The investment of labor and resources in these projects is obviously sizable, and the expected scientific gain from these projects is equally sizable. In truth, the realistic advancement in biological knowledge resulting from a sequenced genome will likely never fulfill the associated promise; however, genomics has indeed affected a wide array of disciplines, with an increasing number of studies combining, in particular, chemistry and genomics. Over the last few years, researchers in academics and industry have undertaken many interesting projects interfacing large-scale genomic methods with synthetic chemical tools - an interface that is broadly termed “chemical genomics.” Chemical genomics occurs at the intersection of genomics, bioinformatics, proteomics, chemoinformatics, structural biology, analytical chemistry, combinatorial chemistry, and chemical biology. Thus, new discoveries in these individual fields are, in turn, driving the development of chemical genomics. Moreover, rapidly maturing ideas that merge traditionally disparate areas are providing additional research opportunities, and the development of new technology is further expanding research avenues. This emerging field has already been successful in identifying new drug targets, in providing powerful chemical probes and in illuminating the mechanism of action of new chemical entities. Future studies will build upon this scientific foundation. In this issue of Combinatorial Chemistry & High Throughput Screening, we present an overview of chemical genomics, authored by leaders in fields of research relevant to this discipline. Here, we summarize influential studies using chemical genomic screens and highlight recent technological developments with applicability to chemical genomics. This issue brings together researchers from both academics and industry, with unique and complementary insight into the current state of the art (and future potential) in marrying genomic resources and methodologies to combinatorial chemistry and small molecule screening. In particular, model organisms are gaining increasing popularity in drug-based screening studies; here, Nike Bharucha and I provide an overview of chemical genomic studies in yeast using genome-wide collections of mutants and other genomic approaches to help identify pathways and proteins targeted by small-molecule drugs. Recent studies have also utilized small molecule-based screens to provide insight into specific biological problems. In this issue, Fang et al. discuss applications of small molecules in studying various aspects of stem cell differentiation. Ratika Krishnamurthy and Dustin Maly review experimental techniques for the determination of protein kinase inhibitor selectivity and further summarize important insights gained from these studies. An exciting slate of technologies applicable on a genomic scale are now being developed and implemented as tools in small molecule screening and drug-based discovery; here, we review several recent technological advances with relevance to chemical genomics. Specifically, Jason Gestwicki and Paul Marinec present an overview of bifunctional molecules as tools in manipulating and probing protein-protein interactions, potentially on a genomic scale. Robert Powers offers a thorough review that summarizes applications of nuclear magnetic resonance energy (NMR) spectroscopy for the large-scale study of protein and protein-ligand complexes. Seergazhi Srivatsan and Michael Famulok review the development of functional nucleic acids, such as aptamers and ribozymes, and their utility in molecular screening. Tao and Chen in Heng Zhu’s group at Johns Hopkins provide a current overview of nascent protein microarray technologies with strong potential implications for future screens of small molecule-protein interactions. Finally, Bender et al. address the growing role of informatics in chemical genomics, both in predicting compound targets and in integrating and interpreting biological descriptors of drugs and small molecules....

The budding yeast Saccharomyces cerevisiae is well recognized as a preferred eukaryote for the development of genomic technologies and approaches. Accordingly, a sizeable complement of genomic resources has been developed in yeast, and this genomic foundation is now informing a wide variety of disciplines. In particular, yeast genomic methodologies are gaining an expanding foothold in drug development studies, most notably as a preliminary tool towards drug target identification. In this review, we highlight many applications of yeast genomics in the identification of targeted genes and pathways of small molecules or therapeutic drugs. The applicability of genome-wide resources of yeast disruption and deletion mutants for drug-sensitivity/resistance screening is presented here, along with a summary of microarray technologies for drug-based transcriptional profiling and synthetic interaction mapping. Applications of proteininteraction traps for potential drug target identification are also considered. Collectively, this overview of yeast genomics emphasizes the growing intersection between high-throughput model organism biology and medicinal chemistry — an intersection promising tangible advances for both academic and pharmaceutical fields alike.

Stem cell-based technologies have the potential to help cure a number of cell degenerative diseases. Combinatorial and high throughput screening techniques could provide tools to control and manipulate the self-renewal and differentiation of stem cells. This review chronicles historic and recent progress in the stem cell field involving both pluripotent and multipotent cells, and it highlights relevant cellular signal transduction pathways. This review further describes screens using libraries of soluble, small-molecule ligands, and arrays of molecules immobilized onto surfaces while proposing future trends in similar studies. It is hoped that by reviewing both the stem cell and the relevant high throughput screening literature, this paper can act as a resource to the combinatorial science community.

The clinical success of the Bcr-Abl tyrosine kinase inhibitor Gleevec® and the recent clinical approval of a number of small molecule drugs that target protein kinases have intensified the search for novel protein kinase inhibitors. Since most small molecule kinase inhibitors target the highly conserved ATP-binding pocket of this enzyme family, the target selectivity of these molecules is a major concern. Due to the large size of the human kinome, it is a formidable challenge to determine the absolute specificity of a given protein kinase inhibitor, but recent technological developments have made substantial progress in achieving this goal. This review summarizes some of the most recent experimental techniques that have been developed for the determination of protein kinase inhibitor selectivity. Special emphasis is placed on the results of these screens and the general insights that they provide into kinase inhibitor target selectivity.

Protein-protein interactions have become attractive drug targets and recent studies suggest that these interfaces may be amenable to inhibition by small molecules. However, blocking specific interactions may not be the only way of manipulating the extensive network of interacting proteins. Recently, several approaches have emerged for promoting these interactions rather than inhibiting them. Typically, these strategies employ a bifunctional ligand to simultaneously bind two targets, forcing their juxtaposition. Chemically “riveting” specific protein contacts can reveal important aspects of regulation, such as the consequences of stable dimerization or the effects of prolonged dwell time. Moreover, in some cases, entirely new functions arise when two proteins, which normally do not interact, are brought into close proximity with one another. Together with inhibitors, bifunctional molecules are part of a growing toolbox of chemical probes that can be used to reversibly and selectively control the interact-ome. Using these reagents, new insights into the dynamics of protein-protein interactions and their importance in biology are beginning to emerge. Future hurdles in this area lie in the development of robust synthetic platforms for rapidly generating compounds to meet the challenges of diverse proteinprotein interfaces.

The recent success of the human genome project and the continued accomplishment in obtaining DNA sequences for a vast array of organisms is providing an unprecedented wealth of information. Nevertheless, an abundance of the proteome contains hypothetical proteins or proteins of unknown function, where high throughput approaches for genome- wide functional annotation (functional genomics) has evolved as the necessary next step. Nuclear magnetic resonance spectroscopy is playing an important role in functional genomics by providing information on the structure of protein and protein-ligand complexes, from metabolite fingerprinting and profiling, from the analysis of the metabolome, and from ligand affinity screens to identify chemical probes.

In vitro selection can be used to generate functional nucleic acids such as aptamers and ribozymes that can recognize a variety of molecules with high affinity and specificity. Most often these recognition events are associated with structural alterations that can be converted into detectable signals. Several signaling aptamers and ribozymes constructed by both design and selection have been successfully utilized as sensitive detection reagents. Here we summarize the development of different types of signaling nucleic acids, and approaches that have been implemented in the screening format.

Protein microarrays, an emerging class of proteomic technologies, are quickly becoming essential tools for large-scale and high throughput biochemistry and molecular biology. Recent progress has been made in all the key steps of protein microarray fabrication and application, such as the large-scale cloning of expression-ready prokaryotic and eukaryotic ORFs, high throughput protein purification, surface chemistry, protein delivery systems, and detection methods. Two classes of protein microarrays are currently available: analytical and functional protein microarrays. In the case of analytical protein microarrays, well-characterized molecules with specific activity, such as antibodies, peptide-MHC complexes, or lectins, are used as immobilized probes. These arrays have become one of the most powerful multiplexed detection platforms. Functional protein microarrays are being increasingly applied to many areas of biological discovery, including drug target identification/validation and studies of protein interaction, biochemical activity, and immune responses. Great progress has been achieved in both classes of protein microarrays in terms of sensitivity and specificity, and new protein microarray technologies are continuing to emerge. Finally, protein microarrays have found novel applications in both scientific research and clinical diagnostics.

Chemogenomics comprises a systematic relationship between targets and ligands that are used as target modulators in living systems such as cells or organisms. In recent years, data on small molecule-bioactivity relationships have become increasingly available, and consequently so have the number of approaches used to translate bioactivity data into knowledge. This review will focus on two aspects of chemogenomics. Firstly, in cases such as cell-based screens, the question of which target(s) a compound is modulating in order to cause the observed phenotype is crucial. In silico target prediction tools can suggest likely biological targets of small molecules via data mining in target-annotated chemical databases. This review presents some of the current tools available for this task and shows some sample applications relevant to a pharmaceutical industry setting. These applications are the prediction of false-positives in cell-based reporter gene assays, the prediction of targets by linking bioassay data with protein domain annotations, and the direct prediction of adverse reactions. Secondly, in recent years a shift from structure-derived chemical descriptors to biological descriptors has occurred. Here, the effect of a compound on a number of biological endpoints is used to make predictions about other properties, such as putative targets, associated adverse reactions, and pathways modulated by the compound. This review further summarizes these “performance” descriptors and their applications, focusing on gene expression profiles and highcontent screening data. The advent of such biological fingerprints suggests that the field of drug discovery is currently at a crossroads, where single target bioassay results are supplanted by multidimensional biological fingerprints that reflect a new awareness of biological networks and polypharmacology.

Dr. Anuj Kumar is an Assistant Professor in the Department of Molecular, Cellular, and Developmental Biology and Research Assistant Professor in the Life Sciences Institute at the University of Michigan. Dr. Kumar's research employs methods in functional genomics, proteomics, and bioinformatics to investigate fundamental questions in eukaryotic cellular and molecular biology using the budding yeast Saccharomyces cerevisiae as a model. Dr. Kumar completed his PhD in molecular genetics at Wright State University in 1997 studying a pathway regulating sulfur utilization and metabolism in Neurospora crassa. Dr. Kumar subsequently joined Michael Snyder's lab at Yale University as a postdoctoral research fellow, where he began his genomic and proteomic studies in the budding yeast. Dr. Kumar joined the faculty at the University of Michigan in 2003 and is currently a Basil O'Connor Scholar of the March of Dimes and a research scholar of the American Cancer Society. SELECTED PUBLICATIONS [1] Ma, J.; Jin, R.; Jia, X.; Dobry, C.J.; Wang, L.; Reggiori, F.; Zhu, J.; Kumar, A. An interrelationship between autophagy and filamentous growth in budding yeast. Genetics 2007, 177, 205-214. [2] Wiwatwattana, N.; Kumar, A. Organelle DB: a cross-species database of protein localization and function. Nucleic Acids Res. 2005, 33, D598-604. [3] Kumar, A.; Seringhaus, M.; Biery, M.C.; Sarnovsky, R.J.; Umansky, L.; Piccirillo, S.; Heidtman, M.; Cheung, K.-H.; Dobry, C.J.; Gerstein, M.B.; Craig, N.L.; Snyder, M. Large-scale mutagenesis of the yeast genome using a Tn7-derived multipurpose transposon. Genome Res. 2004, 14, 1975-1986. [4] Kumar, A.; Agarwal, S.; Heyman, J.A.; Matson, S.; Heidtman, M.; Piccirillo, S.; Umansky, L.; Drawid, A.; Jansen, R.; Liu, Y.; Cheung, K.-H.; Miller, P.; Gerstein, M.; Roeder, G.S.; Snyder, M. Subcellular localization of the yeast proteome. Genes & Dev. 2002, 16, 707-719. [5] Kumar, A.; Harrison, P.M.; Cheung, K.-H.; Lan, N.; Echols, N.; Bertone, P.; Miller, P.; Gerstein, M.B.; Snyder, M. An integrated approach for finding overlooked genes in yeast. Nature Biotech. 2002, 20, 58-63. [6] Kumar, A.; Vidan, S.; Snyder, M. Insertional mutagenesis: transposon-insertion libraries as mutagens in yeast. Methods Enzymol. 2002, 350, 219-229. [7] Kumar, A.; des Etages, S.A.; Coelho, P.S.R.; Roeder, G.S.; Snyder, M. High-throughput methods for the large-scale analysis of gene function by transposon tagging. Methods Enzymol. 2000, 328, 550-574. [8] Ross-Macdonald, P.; Coelho, P.; Roemer, T.; Agarwal, S.; Kumar, A.; Cheung, K.-H.; Jansen, R.; Symoniatis, D.; Umansky, L.; Nelson, K.; Iwasaki, H.; Hager, K.; Gerstein, M.; Miller, P.; Roeder, G.S.; Snyder, M. Large-scale analysis of the yeast genome by transposon tagging and gene disruption. Nature 1999, 402, 413-418. [9] Kumar, A.; Paietta, J.V. A new role for the F-Box motif: gene regulation within the Neurospora crassa sulfur control network. Proc. Natl. Acad. Sci. USA 1998, 95, 2417-2422.