952 resultados para Opportunity discovery and exploitation


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Genomics encompasses a range of powerful technologies that can be applied at all levels of gene expression, from transcription to mRNA translation. Collectively, these technologies have great potential for improving drug discovery, both target and molecule recognition, and development. In this article we review the current and potential future status of established and novel genomic methods within drug discovery.

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During the course of our research efforts to develop a potent and selective gamma-secretase inhibitor for the treatment of Alzheimer's disease, we investigated a series of carboxamide-substituted sulfonamides. Optimization based on potency, Notch/amyloid-beta precursor protein selectivity, and brain efficacy after oral dosing led to the discovery of 4 (BMS-708163). Compound 4 is a potent inhibitor of gamma-secretase (A beta 40 IC50 = 0.30 nM), demonstrating a 193-fold selectivity against Notch. Oral administration of 4 significantly reduced A beta 40 levels for sustained periods in brain, plasma, and cerebrospinal fluid in rats and dogs.

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This article describes the discovery and development of the first highly selective, small molecule antagonist of the muscarinic acetylcholine receptor subtype I (mAChR1 or M-1). An M-1 functional, cell-based, calcium-mobilization assay identified three distinct chemical series with initial selectivity for M-1 versus M-4. An iterative parallel synthesis approach was employed to optimize all three series in parallel, which led to the development of novel microwave-assisted chemistry and provided important take home lessons for probe development projects. Ultimately, this effort produced VU0255035, a potent (IC50 = 130 nM) and selective (>75-fold vs. M-2-M-5 and >10 mu M vs. a panel of 75 GPCRs, ion channels and transporters) small molecule M-1 antagonist. Further profiling demonstrated that VU0255035 was centrally penetrant (Brain(AUC)/Plasma(AUC) of 0.48) and active in vivo, rendering it acceptable as both an in vitro and in vivo MLSCN/MLPCN probe molecule for studying and dissecting M-1 function.

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Porcine circoviruses (PCVs) belong to the genus Circovirus, family Circoviridae. and are the smallest non-enveloped, single stranded, negative sense, circular DNA viruses that replicate autonomously in mammalian cells. Two types of PCV have been characterised, PCV1 and PCV2 and these two viruses show 83% sequence identity at open reading frame (ORF) 1 and 67% identity at ORF2. PCV1 is a nonpathogenic virus of pigs. In contrast, PCV2 has emerged as a major pathogen of swine around the world. The discovery of PCV1 and how the subsequent studies on this virus eventually led to the recognition and characterisation of PCV2, and the disease scenarios associated with PCV2, serve as a model of how multidisciplinary collaboration among field veterinarians, diagnosticians and researchers can lead to the rapid characterisation and control of a globally important emerging disease. (C) 2011 Elsevier B.V. All rights reserved.

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Herein we report the discovery and SAR of a novel series of non-MPEP site metabotropic glutamate receptor 5 (mGlu(5)) positive allosteric modulators (PAMs) based on an aryl glycine sulfonamide scaffold. This series represents a rare non-MPEP site mGlu(5) PAM chemotype.

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This paper identifies and analyses the means of accessing and collecting foreign-based evidence in transnational antitrust cases. It makes an original contribution to the existing scholarship by critically addressing the available mechanisms of judicial cooperation, the possibility of reliance on domestic discovery in transnational context, as well as the existing instruments allowing for cooperation between antitrust agencies. It identifies the shortcomings of the current regulatory framework and points out to the existing good practices in those jurisdictions which provide their antitrust agencies with more leeway in sharing confidential information with foreign counterparts.

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G-protein coupled receptors (GPCRs) are the targets of over half of all prescribed drugs today. The UniProt database has records for about 800 proteins classified as GPCRs, but drugs have only been developed against 50 of these. Thus, there is huge potential in terms of the number of targets for new therapies to be designed. Several breakthroughs in GPCRs biased pharmacology, structural biology, modelling and scoring have resulted in a resurgence of interest in GPCRs as drug targets. Therefore, an international conference, sponsored by the Royal Society, with world-renowned researchers from industry and academia was recently held to discuss recent progress and highlight key areas of future research needed to accelerate GPCR drug discovery. Several key points emerged. Firstly, structures for all three major classes of GPCRs have now been solved and there is increasing coverage across the GPCR phylogenetic tree. This is likely to be substantially enhanced with data from x-ray free electron sources as they move beyond proof of concept. Secondly, the concept of biased signalling or functional selectivity is likely to be prevalent in many GPCRs, and this presents exciting new opportunities for selectivity and the control of side effects, especially when combined with increasing data regarding allosteric modulation. Thirdly, there will almost certainly be some GPCRs that will remain difficult targets because they exhibit complex ligand dependencies and have many metastable states rendering them difficult to resolve by crystallographic methods. Subtle effects within the packing of the transmembrane helices are likely to mask and contribute to this aspect, which may play a role in species dependent behaviour. This is particularly important because it has ramifications for how we interpret pre-clinical data. In summary, collaborative efforts between industry and academia have delivered significant progress in terms of structure and understanding of GPCRs and will be essential for resolving problems associated with the more difficult targets in the future.

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BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.