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Establishment and application of a high throughput model for rho kinase inhibitors screening based on fluorescence polarization.

机译:基于荧光偏振的高通量rho激酶抑制剂筛选模型的建立和应用。

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Rho kinase (ROCK) inhibitors are effective candidates for neural or cardiovascular disorders. High throughput model for screening ROCK inhibitors is a basic foundation to pick up ROCK inhibitors from thousands of compounds for drug developing. The high throughput model was established based on purified recombinant rat ROCK catalytic domain (rROCK-CD) from Escherichia coli (E. coli). There are two steps of reaction in the model: incubation of 5.0 mul recombinant rROCK-CD (2.0 mug/ml), 5.0 mul different compounds, 5.0 mul fluorescent S6-peptide (200 nM), and 5.0 mul ATP (10 muM) at 37 degrees C for 60 min was made the first reaction, and the second reaction was made by incubating them with additional 60 mul binding reagent at ambient temperature for 30 min. The phosphorylated S6 peptide can bind to a binding reagent, and the fluorescence varies from low polarization to high according to the amount of the phosphorylated peptide. IC(50) was calculated based on polarization variation. Compound, which IC(50)was less than 10 muM, was recognized as a lead compound which taken bioactivity evaluation in PC12 by observing neurite outgrowth. The Z'-factor of the model is 0.81 (above 0.5). The model screened five lead compounds from 3294, which promoted neurite outgrowth to different extent. The results suggested that the model is suitable for high throughput screening (HTS), and the five lead compounds are worth of further investigation.
机译:Rho激酶(ROCK)抑制剂可有效治疗神经或心血管疾病。用于筛选ROCK抑制剂的高通量模型是从数千种用于药物开发的化合物中提取ROCK抑制剂的基础。基于来自大肠杆菌(E.coli)的纯化的重组大鼠ROCK催化结构域(rROCK-CD)建立了高通量模型。该模型中的反应分为两个步骤:在室温下孵育5.0 mul重组rROCK-CD(2.0 cup / ml),5.0 mul不同化合物,5.0 mul荧光S6-肽(200 nM)和5.0 mul ATP(10μM)。在37℃下进行第一反应60分钟,并且通过在环境温度下将它们与另外的60μl结合试剂一起温育30分钟来进行第二反应。磷酸化的S6肽可以结合结合剂,并且荧光根据磷酸化的肽的量从低极化变化到高极化。基于极化变化计算IC(50)。 IC(50)小于10μM的化合物被认为是先导化合物,通过观察神经突的生长在PC12中进行了生物活性评估。模型的Z'因子为0.81(高于0.5)。该模型从3294中筛选出5种铅化合物,这些化合物在不同程度上促进了神经突的生长。结果表明该模型适用于高通量筛选(HTS),并且五种前导化合物值得进一步研究。

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