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首页> 外文期刊>BMC Genomics >Novel drug-regulated transcriptional networks in brain reveal pharmacological properties of psychotropic drugs
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Novel drug-regulated transcriptional networks in brain reveal pharmacological properties of psychotropic drugs

机译:脑中新型药物调节的转录网络揭示了精神药物的药理特性

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Background Despite their widespread use, the biological mechanisms underlying the efficacy of psychotropic drugs are still incompletely known; improved understanding of these is essential for development of novel more effective drugs and rational design of therapy. Given the large number of psychotropic drugs available and their differential pharmacological effects, it would be important to establish specific predictors of response to various classes of drugs. Results To identify the molecular mechanisms that may initiate therapeutic effects, whole-genome expression profiling (using 324 Illumina Mouse WG-6 microarrays) of drug-induced alterations in the mouse brain was undertaken, with a focus on the time-course (1, 2, 4 and 8?h) of gene expression changes produced by eighteen major psychotropic drugs: antidepressants, antipsychotics, anxiolytics, psychostimulants and opioids. The resulting database is freely accessible at http://www.genes2mind.org webcite . Bioinformatics approaches led to the identification of three main drug-responsive genomic networks and indicated neurobiological pathways that mediate the alterations in transcription. Each tested psychotropic drug was characterized by a unique gene network expression profile related to its neuropharmacological properties. Functional links that connect expression of the networks to the development of neuronal adaptations (MAPK signaling pathway), control of brain metabolism (adipocytokine pathway), and organization of cell projections (mTOR pathway) were found. Conclusions The comparison of gene expression alterations between various drugs opened a new means to classify the different psychoactive compounds and to predict their cellular targets; this is well exemplified in the case of tianeptine, an antidepressant with unknown mechanisms of action. This work represents the first proof-of-concept study of a molecular classification of psychoactive drugs.
机译:背景技术尽管广泛使用,但精神药物疗效的生物学机制仍不完全清楚。对于新的更有效的药物的开发和合理设计疗法,对这些知识的更好理解至关重要。鉴于可用的精神药物数量众多,并且它们具有不同的药理作用,因此重要的是建立对各种药物反应的具体预测指标。结果为了确定可能启动治疗作用的分子机制,进行了小鼠脑中药物诱导的改变的全基因组表达谱分析(使用324 Illumina Mouse WG-6芯片),重点是时间过程(1, 2,4和8?h)十八种主要精神药物产生的基因表达变化:抗抑郁药,抗精神病药,抗焦虑药,精神兴奋药和阿片类药物。可以在http://www.genes2mind.org网站上免费访问生成的数据库。生物信息学方法导致了三个主要的药物反应性基因组网络的鉴定,并指出了介导转录改变的神经生物学途径。每种测试的精神药物的特征在于与其神经药理特性有关的独特基因网络表达谱。发现了将网络表达与神经元适应发展(MAPK信号传导途径),脑代谢控制(adipocytokine途径)和细胞投射组织(mTOR途径)联系起来的功能链接。结论比较各种药物之间的基因表达变化,为分类不同的精神活性化合物并预测其细胞靶点提供了新的手段。在噻庚汀(一种具有未知作用机理的抗抑郁药)中,这已得到很好的例证。这项工作代表了精神活性药物分子分类的首次概念验证研究。

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