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At least 109 records · Page 6Linked to original sources
PubMed2000

Peroxisomal protein targeting and identification of peroxisomal targeting signals in cholesterol biosynthetic enzymes.

At least three different subcellular compartments, including peroxisomes, are involved in cholesterol synthesis. Recently, it has been demonstrated that peroxisomes contain a number of enzymes involved in cholesterol biogenesis that previously were considered to be cytosolic or located in the endoplasmic reticulum. Peroxisomes have been shown to contain acetoacetyl-CoA thiolase, HMG-CoA synthase, HMG-CoA reductase, mevalonate kinase, phosphomevalonate kinase, phosphomevalonate decarboxylase, isopentenyl diphosphate isomerase and FPP synthase. Moreover, the activities of these enzymes are also significantly decreased in liver tissue and fibroblast cells obtained from patients with peroxisomal deficiency diseases. In addition, the cholesterol biosynthetic capacity is severely impaired in cultured skin fibroblasts obtained from patients with peroxisomal deficiency diseases. These findings support the proposal that peroxisomes play an essential role in isoprenoid biosynthesis. This paper presents a review of peroxisomal protein targeting and of recent studies demonstrating the localization of cholesterol biosynthetic enzymes in peroxisomes and the identification of peroxisomal targeting signals in these proteins.

Amino Acid Sequence↗
PubMed2004

A novel genomics approach for the identification of drug targets in pathogens, with special reference to Pseudomonas aeruginosa.

Complete genome sequences of several pathogenic bacteria have been determined, and many more such projects are currently under way. While these data potentially contain all the determinants of host-pathogen interactions and possible drug targets, computational tools for selecting suitable candidates for further experimental analyses are currently limited. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug targets. We have used three-way genome comparisons to identify essential genes from Pseudomonas aeruginosa. Our approach identified 306 essential genes that may be considered as potential drug targets. The resultant analyses are in good agreement with the results of systematic gene deletion experiments. This approach enables rapid potential drug target identification, thereby greatly facilitating the search for new antibiotics. These results underscore the utility of large genomic databases for in silico systematic drug target identification in the post-genomic era.

Anti-Bacterial Agents↗
PubMed2003

Role of ADME characteristics in drug discovery and their in silico evaluation: in silico screening of chemicals for their metabolic stability.

Drug discovery is a long, arduous process broadly grouped into disease target identification, target validation, high-throughput identification of "hits" and "leads", lead optimization, and pre-clinical and clinical evaluation. Each area is a vast discipline in itself. However, all but the first two stages involve, to varying degrees, the characterization of absorption, distribution, metabolism, excretion, (ADME), and toxicity (T) of the molecules being pursued as potential drug candidates. Clinical failures of about 50% of the Investigational New Drug (IND) filings are attributed to their inadequate ADMET attributes. It is, therefore, no surprise that, in the current climate of social and regulatory pressure on healthcare costs, the pharmaceutical industry is searching for any means to minimize this attrition. Building mathematical models, called in silico screens, to reliably predict ADMET attributes solely from molecular structure is at the heart of this effort in reducing costs as well as development cycle times. This article reviews the emerging field of in silico evaluation of ADME characteristics. For different approaches that have been employed in this area, a critique of the scope and limitations of their descriptors, statistical methods, and reliability are presented. For instance, are geometry-based descriptors absolutely essential or is lower-level structure quantification equally good? What advantages, if any, do we have for methods like artificial neural networks over the least squares optimization methods with rigorous statistical diagnostics? Is any in silico screen worth application, let alone interpretation, if it is not adequately validated? Once deemed acceptable, what good is an in silico screen if it cannot be made available at the workbench of drug discovery teams distributed across the globe throughout multi-national pharmaceutical companies? These are not mere discussion points, rather this article embarks on the stepwise mechanics of developing a successful in silico screen. The process is exemplified by our efforts in developing one such screen for predicting metabolic stability of chemicals in a human S9 liver homogenate assay. A real-life use of this in silico screen in a variety of discovery projects at GlaxoSmithKline is presented, highlighting successes and limitations of such applications. Finally, we project some capabilities of in silico ADME tools for greater impact and contribution to successful, efficient drug discovery.

Computer-Aided Design↗
PubMed2006

The program for phenotyping of genetically modified animals at AstraZeneca.

Genetically modified mice offer a wide range of possibilities in preclinical drug discovery, e.g. for use in target identification, target validation and disease model generation. However, genomic modification and alteration in gene expression may cause unpredicted phenotypic alterations in the organism other than the intended ones. The aim of this study was to determine the importance of establishing the phenotype of transgenic and knockout mice models for use in pharmaceutical research. A total number of 51 mouse models (transgenic and knockout) produced at AstraZeneca during a 4 year period were subjected to a thorough phenotyping package covering clinical as well as morphological aspects. Phenotype abnormalities were recorded in 36 (70.6%) of the mouse models. The majority of findings were considered to be minor in magnitude. Histopathological changes related to the genotype of the animals were observed in 33% of the mouse models, underlining the importance of pathology in the phenotyping program.

Animals↗
PubMed1998

Novel approaches to the discovery of antimicrobial agents.

With the completion of numerous bacterial genome sequences, the discovery of antibacterial drugs has fully entered the genomic era. The strategies for effectively using genomic information for target identification, target characterization, screen development and compound evaluation are emerging, and have greatly increased the number of antibacterial targets available for screening. Fortunately, simultaneous efforts in improving miniaturization, robotics and database tools are underway so that the potential of genomics can be realized.

Anti-Infective Agents↗
PubMed2006

Target validation in silico: does the virtual patient cure the pharma pipeline?

Genomics has multiplied the number of targets for new therapeutic interventions, but this has not yet lead to a marked increase of pharma pipeline outputs. The complexity of protein function in higher order biological systems is often underestimated. Translation from in vitro and in vivo results to the human setting frequently fails due to unforeseen toxicity and efficacy issues. Biosimulation addresses these issues by capturing the complex dynamics of interacting molecules and cells in mechanistic, predictive models. A central concept is that of the virtual patient, an encapsulation of a specific pathophysiological behaviour in a biosimulation model. The authors describe how virtual patients are being used in target identification, target validation and clinical development, and discuss challenges for the acceptance of biosimulation methods.

Computer Simulation↗
PubMed2004

Monitoring therapy with gene expression profiling reveals physiological differences in drug action.

Gene expression profiling has become a versatile tool for biomedical research, which allows the assessment of a wide variety of basic questions in cellular regulation, in particular when a large number of molecular parameters have changed. There are various applications in drug research for which gene expression profiling is a very suitable approach. This includes: target identification, target validation, validation of drug specificity and monitoring of drug action during therapy. The focus of this article is the therapy monitoring and the interpretation of the gene expression profiles in respect to physiological differences of drug action. As an example, we will discuss changes in gene expression in blood samples from CML patients treated with the tyrosine kinase inhibitor (imatinib mesylate) and compare the observed effects on gene expression with the effects of IFNalpha treatment. In comparison with other examples of therapy monitoring the potential of this application of gene expression profiling for optimizing individual therapy will be discussed.

Animals↗
PubMed2007

A subsystems-based approach to the identification of drug targets in bacterial pathogens.

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.

Anti-Bacterial Agents↗
PubMed2006

Identification of miRNA targets with stable isotope labeling by amino acids in cell culture.

miRNAs are small noncoding RNAs that regulate gene expression. We have used stable isotope labeling by amino acids in cell culture (SILAC) to investigate the effect of miRNA-1 on the HeLa cell proteome. Expression of 12 out of 504 investigated proteins was repressed by miRNA-1 transfection. This repressed set of genes significantly overlaps with miRNA-1 regulated genes that have been identified with DNA array technology and are predicted by computational methods. Moreover, we find that the 3'-untranslated region for the repressed set are enriched in miRNA-1 complementary sites. Our findings demonstrate that SILAC can be used for miRNA target identification and that one highly expressed miRNA can regulate the levels of many different proteins.

3' Untranslated Regions↗
PubMed2003

The adenine nucleotide translocator: a new potential chemotherapeutic target.

Identification of new targets is of utmost importance for the development of efficient apoptosis-modulating drugs. This has become possible from the unraveling of the basic apoptosis mechanisms and notably, from the demonstration of the mitochondrial membrane permeabilization as a central rate-limiting step of numerous models of cell death. Indeed, molecular and pharmacological studies revealed that the adenine nucleotide translocator (ANT) could be a therapeutic target. First, ANT is a bi-functional protein. It mediates the exchange of cytosolic ADP and mitochondrial ATP, and contributes to apoptosis via its capacity to become a lethal pore. Second, both ANT functions are under the control of the (anti)-oncogenes from the Bax/Bcl-2 family, and third, agents as diverse as proteins, lipids, ions, pro-oxidants or chemotherapeutic agents directly modulate the pore-forming activity of ANT. Here, we will review the mode of apoptosis induction by various classes of chemotherapeutic agents, which all influence directly ANT pro-apoptotic function. Hopefully, this will yield several clues to the modulation of apoptosis from a therapeutic perspective.

Animals↗
PubMed2002

The use of transgenic systems in pharmaceutical research.

Those pharmaceutical companies whose goal is to generate novel innovative drugs are faced with the challenge that only a fraction of the compounds tested in clinical trials eventually become a registered drug. This problem of attrition is compounded by the fact that the clinical trial or development stage is by far the most costly phase of bringing a new drug to market, consuming around 80 per cent of the total spend. Transgenic technology represents an attractive approach to reducing the attrition rate of compounds entering clinical trials by increasing the quality of the target and compound combinations making the transition from discovery into development. Transgenic technology can impact at many points in the discovery process, including target identification and target validation, and provides models designed to alert researchers early to potential problems with drug metabolism and toxicity, as well as providing better models for human diseases. In target identification, transgenic animals harbouring large DNA fragments can be used to narrow down genetic regions. Genetic studies often result in the identification of large genomic regions and one way to decrease the region size is to do complementation studies in transgenic animals using, for example, inserts from bacterial artificial chromosome (BAC) clones. In target validation, transgenic animals can be used for in vivo validation of a specific target. Considerable efforts are being made to establish new, rapid and robust tools with general utility for in vivo validation, but, so far, only transgenic animals work reliably on a wide range of targets. Transgenic animals can also be used to generate better disease models. Predictive animal models to test new compounds and targets will significantly speed up the drug discovery process and, more importantly, increase the quality of the compounds taken further in the research and development process. Humanised transgenic animals harbouring the human target molecule can be used to understand the effect of a compound acting on the human target in vivo. Also, models mimicking human drug metabolism will provide a means of assessing the effect of human-specific metabolites and of understanding the pharmacokinetic properties of potential drugs. In toxicology studies, transgenic animals are providing more predictive models. A good example of this are those models routinely used to look for carcinogenicity associated with new compounds.

Animals↗