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OPEN ACCESS PLUS
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Contents
14(7): Pp. 616 - 621
Kenji Sorimachi and Takaaki Nakamoto
[Open Access Plus] |
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All medicines pose a potential health risk, be they Eastern or Western medicines. Newly developed Western drugs must undergo rigorous testing to ensure their efficacy and safety, while with Eastern drugs, safety has generally been established because of their long histories of safe usage as traditional medicines. The regulation of Western medicines is much stronger than that of Eastern medicines, partly as pure chemicals are used and their effects and side effects are more likely to be acute. Eastern medicines consist of multiple components, generally extracted from a single or several plants or other natural sources, and their effects are not so acute, with delayed onset of side effects. However, the chronic usage of many Eastern medicines may result in the gradual accumulation of toxic compounds in the body. For example, Agaricus blazei extracts have been used as alternative medicines for cancer, but contain the known carcinogen agaritine (this carcinogen is also present in Agaricus bisporus). To ensure the safety of this alternative medicine, agaritine should be removed or its content reduced if the extract is to be taken chronically. Clearly, the safety of not only pure medicines, but also alternative medicines and daily foods, should be carefully controlled.
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14(6): Pp. 521 - 531
C. John Harris, Richard D. Hill, David W. Sheppard, Martin J. Slater and Pieter F.W. Stouten
[Open Access Plus] |
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Target-focused compound libraries are collections of compounds which are designed to interact with an individual protein target or, frequently, a family of related targets (such as kinases, voltage-gated ion channels, serine/cysteine proteases). They are used for screening against therapeutic targets in order to find hit compounds that might be further developed into drugs. The design of such libraries generally utilizes structural information about the target or family of interest. In the absence of such structural information, a chemogenomic model that incorporates sequence and mutagenesis data to predict the properties of the binding site can be employed. A third option, usually pursued when no structural data are available, utilizes knowledge of the ligands of the target from which focused libraries can be developed via scaffold hopping. Consequently, the methods used for the design of target-focused libraries vary according to the quantity and quality of structural or ligand data that is available for each target family. This article describes examples of each of these design approaches and illustrates them with case studies, which highlight some of the issues and successes observed when screening target-focused libraries.
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14(4): Pp. 248 - 266
David Sedlak, Aileen Paguio and Petr Bartunek
[Open Access Plus] |
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Steroid hormone receptors represent a major target in drug discovery. As ligand inducible transcription factors, their activity can be modulated by small lipophilic molecules. Here we describe two panels of potent and selective luciferase reporter cell lines based on cells with low endogenous steroid receptor activity (U2OS). The panels contain reporter cell lines for estrogen receptors α and β, androgen, glucocorticoid, mineralocorticoid, and progesterone receptors. In the first panel, the activation of either synthetic, steroid response elements containing promoter or viral promoter is mediated by full-length steroid receptors. The second panel is based on the expression of the chimeric receptor, which was created by the replacement of the N-terminal part of the molecule by Gal4 DBD and that binds to multiple UAS sites in the reporter promoter. Both panels were extensively characterized by profiling 28 ligands in dose response manner in agonist and antagonist mode. We have analyzed and compared the responses to tested ligands from both panels and concluded that in general both systems generated similar qualitative response in terms of potency, efficacy, partial agonism/antagonism, mixed agonistic/antagonistic profiles and the rank of potencies was well conserved between both panels. However, we have also identified some artifacts introduced by the Gal4/LBD reporter assays in contrast to their full-length receptor reporter counterparts. Keeping in mind the advantages and drawbacks of each reporter format, these cell lines represent powerful and selective tools for profiling large compound libraries (HTS) and for detailed study of mechanisms by which compounds exert their biological effects.
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13(2): Pp. 188 - 206
James M. McKim Jr.
[Open Access Plus] |
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One of the greatest challenges facing the pharmaceutical industry today is the failure of promising new drug candidates due to unanticipated adverse effects discovered during preclinical animal safety studies and clinical trials. Late stage attrition increases the time required to bring a new drug to market, inflates development costs, and represents a major source of inefficiency in the drug discovery/development process. It is generally recognized that early evaluation of new drug candidates is necessary to improve the process. Building in vitro data sets that can accurately predict adverse effects in vivo would allow compounds with high risk profiles to be deprioritized, while those that possess the requisite drug attributes and a lower risk profile are brought forward. In vitro cytotoxicity assays have been used for decades as a tool to understand hypotheses driven questions regarding mechanisms of toxicity. However, when used in a prospective manner, they have not been highly predictive of in vivo toxicity. Therefore, the issue may not be how to collect in vitro toxicity data, but rather how to translate in vitro toxicity data into meaningful in vivo effects. This review will focus on the development of an in vitro toxicity screening strategy that is based on a tiered approach to data collection combined with data interpretation.
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12(9): Pp. 917 - 925
Mark A. Collins
[Open Access Plus] |
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High Content Screening (HCS) and High Content Analysis (HCA) have emerged over the past 10 years as a powerful technology for both drug discovery and systems biology. Founded on the automated, quantitative image analysis of fluorescently labeled cells or engineered cell lines, HCS provides unparalleled levels of multi-parameter data on cellular events and is being widely adopted, with great benefits, in many aspects of life science from gaining a better understanding of disease processes, through better models of toxicity, to generating systems views of cellular processes. This paper looks at the role of informatics and bioinformatics in both enabling and driving HCS to further our understanding of both the genome and the cellome and looks into the future to see where such deep knowledge could take us.
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12(9): Pp. 870 - 876
Joseph M. Zock
[Open Access Plus] |
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Over the last decade, imaging as a detection mode for cell based assays has opened a new world of opportunities to measure “phenotypic endpoints” in both current and developing biological models. These “high content” methods combine multiple measurements of cell physiology, whether it comes from sub-cellular compartments, multicellular structures, or model organisms. The resulting multifaceted data can be used to derive new insights into complex phenomena from cell differentiation to compound pharmacology and toxicity. Exploring the major application areas through review of the growing compendium of literature provides evidence that this technology is having a tangible impact on drug discovery and the life sciences.
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11(9): Pp. 723 - 733
Douglas J. Klein, Teodora Ivanciuc, Anton Ryzhov and Ovidiu Ivanciuc
[Open Access Plus] |
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Reaction networks are viewed as derived from ordinary molecular structures related in reactant-product pairs so as to manifest a chemical super-structure. Such super-structures then are candidates for applications in a general combinatoric chemistry. Notable additional characterization of a reaction super-structure occurs when such reaction graphs are directed, as for example when there is progressive substitution (or addition) on a fixed molecular skeleton. Such a set of partially ordered entities is in mathematics termed a poset, which further manifests a number of special properties, as then might be utilized in different applications. Focus on the overall “super-structural” poset goes beyond ordinary molecular structure in attending to how a structure fits into a (reaction) network, and thereby brings an extra “dimension” to conventional stereochemical theory. The possibility that different molecular properties vary smoothly along chains of interconnections in such a super-structure is a natural assumption for a novel approach to molecular property and bioactivity correlations. Different manners to interpolate/ extrapolate on a poset network yield quantitative super-structure/activity relationships (QSSARs), with some numerical fits, e.g., for properties of polychlorinated biphenyls (PCBs) seemingly being quite reasonable. There seems to be promise for combinatoric posetic ideas.
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11(8): Pp. 677 - 685
Jean-Philippe Vert and Laurent Jacob
[Open Access Plus] |
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Support vector machines and kernel methods belong to the same class of machine learning algorithms that has recently become prominent in both computational biology and chemistry, although both fields have largely ignored each other. These methods are based on a sound mathematical and computationally efficient framework that implicitly embeds the data of interest, respectively proteins and small molecules, in high-dimensional feature spaces where various classification or regression tasks can be performed with linear algorithms. In this review, we present the main ideas underlying these approaches, survey how both the “biological” and the “chemical” spaces have been separately constructed using the same mathematical framework and tricks, and suggest different avenues to unify both spaces for the purpose of in silico chemogenomics.
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11(7): Pp. 505 - 513
George T. Hanson and Bonnie J. Hanson
[Open Access Plus] |
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A fluorescent probe is a fluorophore designed to localize within a specific region of a biological specimen or to respond to a specific stimulus. Fluorescent probes have been used for nearly a century to study cellular processes due to their exquisite sensitivity and selectivity. Fluorescent probes have also gained in popularity as safety and environmental concerns over the use of radioactive probes have grown. At the same time, cellular assays are being more widely used now than ever before. This review will give a broad overview of types of fluorescent probes, types of fluorescent assays, and their application in cellular assays for a number of pharmaceutically relevant target classes.
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11(5): Pp. 357 - 369
Ye Fang, Anthony G. Frutos and Ronald Verklereen
[Open Access Plus] |
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G protein-coupled receptors (GPCRs) have been proven to be the largest family of druggable targets in the human genome. Given the importance of GPCRs as drug targets and the de-orphanization of novel targets, GPCRs are likely to remain the frequent targets of many drug discovery programs. With recent advances in instrumentation and understanding of cellular mechanisms for the signals measured, biosensor-centered label-free cell assay technologies become a very active area for GPCR screening. This article reviews the principles and potential of current label-free cell assay technologies in GPCR drug discovery.
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11(4): Pp. 304 - 315
Kasper B. Hansen, Hans Brauner-Osborne and Jan Egebjerg
[Open Access Plus] |
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Generation of in vitro cellular assays using fluorescence measurements at heterologously expressed NMDA receptors would speed up the process of ligand characterization and enable high-throughput screening. The major drawback to the development of such assays is the cytotoxicity caused by Ca2+-flux into the cell via NMDA receptors upon prolonged activation by agonists present in the culture medium. In the present study, we established four cell lines with stable expression of NMDA receptor subtypes NR1/NR2A, NR1/NR2B, NR1/NR2C, or NR1/NR2D in BHK-21 cells. To assess the usefulness of the stable cell lines in conjunction with intracellular calcium ([Ca2+]i) measurements for evaluation of NMDA receptor pharmacology, several ligands were characterized using this method. The results were compared to parallel data obtained by electrophysiological recordings at NMDA receptors expressed in Xenopus oocytes. This comparison showed that agonist potencies determined by [Ca2+]i measurements and electrophysiological recordings correlated well, meaning that the stable cell lines in conjunction with [Ca2+]i measurements provide a useful tool for characterization of NMDA receptor ligands. The agonist series of conformationally constrained glutamate analogues (2S,3R,4S)-α- (carboxycyclopropyl)glycine (CCG), 1-aminocyclobutane-r-1,cis-3-dicarboxylic acid (trans-ACBD), and (±)-1- aminocyclopentane-r-1,cis-3-dicarboxylic acid (cis-ACPD), as well as the highly potent agonist tetrazolylglycine were among the characterized ligands that were assessed with respect to subtype selectivity at NMDA receptors. However, none of the characterized agonists displays more than 2-3 fold selectivity towards a specific NMDA receptor subtype. Thus, the present study provides a broad pharmacological characterization of structurally diverse ligands at recombinant NMDA receptor subtypes.
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11(3): Pp. 231 - 237
Andrew K. Shiau, Mark E. Massari and Can C. Ozbal
[Open Access Plus] |
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Small molecule high-throughput screening in drug discovery today is dominated by techniques which are dependent upon artificial labels or reporter systems. While effective, these approaches can be affected by certain experimental limitations, such as conformational restrictions imposed by the selected label or compound fluorescence/quenching. Label-free approaches potentially address many of these issues by allowing researchers to investigate more native systems without fluorescence- or luminescence-based readouts. However, due to throughput and expense constraints, label-free methods have been largely relegated to a supporting role as the basis of secondary assays. In this review, we describe recent improvements in impedance-based, optical biosensor-based, automated patch clamp and mass spectrometry technologies that have enhanced their ease of use and throughput and, hence, their utility for primary screening of small- to medium-sized compound libraries. The ultimate maturation of these techniques will enable drug discovery researchers to screen large chemical libraries against minimally manipulated biological systems.
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11(3): Pp. 175 - 184
Paul D. Kassner
[Open Access Plus] |
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High throughput technologies have the potential to affect all aspects of drug discovery. Considerable attention is paid to high throughput screening (HTS) for small molecule lead compounds. The identification of the targets that enter those HTS campaigns had been driven by basic research until the advent of genomics level data acquisition such as sequencing and gene expression microarrays. Large-scale profiling approaches (e.g., microarrays, protein analysis by mass spectrometry, and metabolite profiling) can yield vast quantities of data and important information. However, these approaches usually require painstaking in silico analysis and low-throughput basic wet-lab research to identify the function of a gene and validate the gene product as a potential therapeutic drug target. Functional genomic screening offers the promise of direct identification of genes involved in phenotypes of interest. In this review, RNA interference (RNAi) mediated loss-of-function screens will be discussed and as well as their utility in target identification. Some of the genes identified in these screens should produce similar phenotypes if their gene products are antagonized with drugs. With a carefully chosen phenotype, an understanding of the biology of RNAi and appreciation of the limitations of RNAi screening, there is great potential for the discovery of new drug targets.
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11(2): Pp. 159 - 172
Michael Sturzl, Andreas Konrad, Gaby Sander, Effi Wies, Frank Neipel, Elisabeth Naschberger, Simone Reipschlager, Nathalie Gonin-Laurent, Raymund E. Horch, Ulrich Kneser, Werner Hohenberger, Holger Erfle and Mathias Thurau
[Open Access Plus] |
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Reversely transfected cell microarrays (RTCM) have been introduced as a method for parallel high throughput analysis of gene functions in mammalian cells. Hundreds to thousands of different recombinant DNA or RNA molecules can be transfected into different cell clusters at the same time on a single glass slide with this method. This allows either the simultaneous overexpression or - by using the recently developed RNA interference (RNAi) techniques - knockdown of a huge number of target genes. A growing number of sophisticated detection systems have been established to determine quantitatively the effects of the transfected molecules on the cell phenotype. Several different cell types have been successfully used for this procedure. This review summarizes the presently available knowledge on this technique and provides a laboratory protocol.
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10(8): Pp. 618 - 634
Nike Bharucha and Anuj Kumar
[Open Access Plus] |
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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.
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