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Using in silico biology to facilitate drug development

机译:利用计算机生物学来促进药物开发

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G protein-coupled receptor (GPCR) mediation of cardiac excitability is often overlooked in predicting the likelihood that a compound will alter repolarization. While the areas of GPCR signal transduction and electrophysiology are rich in data, experiments combining the two are difficult. In silico modelling facilitates the integration of all relevant data in both areas to explore the hypothesis that critical associations may exist between the different GPCR signalling mechanisms and cardiac excitability and repolarization. An example of this linkage is suggested by the observation that a mutation of the gene encoding HERG, the pore-forming subunit of the rapidly activating delayed rectifier K~+ current (I_(KR)), leads to a form of long QT syndrome in which affected individuals are vulnerable to stress-induced arrhythmia following β-adrenergic stimulation. Using Physiome's In Silico CellTM, we constructed a model integrating the signalling mechanisms of second messengers cAMP and protein kinase A with I_(Kr) in a cardiac myocyte. We analysed the model to identify the second messengers that most strongly influence I_(Kr) behaviour. Our conclusions indicate that the dynamics of regulation are multifactorial, and that Physiome's approach to in silico modelling helps elucidate the subtle control mechanisms at play.
机译:在预测化合物改变复极的可能性时,通常会忽略心脏兴奋性的G蛋白偶联受体(GPCR)介导。尽管GPCR信号转导和电生理学领域的数据丰富,但将两者结合起来的实验却很困难。计算机模拟有助于促进这两个领域中所有相关数据的整合,以探讨以下假设:不同的GPCR信号传导机制与心脏兴奋性和复极化之间可能存在关键关联。这种联系的一个例子是通过观察发现,编码HERG的基因突变,即快速激活的延迟整流器K〜+电流(I_(KR))的成孔亚基,导致长QT综合征的形式。 β-肾上腺素刺激后,哪些受影响的个体易受应激性心律不齐的影响。我们使用Physiome的In Silico CellTM构建了一个模型,该模型整合了心肌细胞中第二信使cAMP和蛋白激酶A与I_(Kr)的信号传导机制。我们分析了该模型,以找出对I_(Kr)行为影响最大的第二个Messenger。我们的结论表明,调节的动力学是多因素的,而Physiome的计算机模拟方法有助于阐明起作用的微妙控制机制。

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