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首页> 外文期刊>Journal of receptor and signal transduction research >A study of the allosteric inhibition of HCV RNA-dependent RNA polymerase and implementing virtual screening for the selection of promising dual-site inhibitors with low resistance potential
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A study of the allosteric inhibition of HCV RNA-dependent RNA polymerase and implementing virtual screening for the selection of promising dual-site inhibitors with low resistance potential

机译:HCV RNA依赖性RNA聚合酶的变构抑制研究,实施具有低电阻电位的有前途的双位点抑制剂的虚拟筛选

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Structure-based pharmacophores were generated and validated using the bioactive conformations of different co-crystallized enzyme-inhibitor complexes for allosteric palm-1 and thumb-2 inhibitors of NS5B. Two pharmacophore models were obtained, one for palm-1 inhibitors with sensitivity=0.929 and specificity=0.983, and the other for thumb-2 inhibitors with sensitivity=1 and specificity=0.979. In addition, a quantitative structure activity relationship (QSAR) models were developed based on using the values of different scoring functions as descriptors predicting the activity on both allosteric binding sites (palm-1 and thumb-2). QSAR studies revealed good predictive and statistically significant two descriptor models (r(2)=.837, r(adjusted)(2)=.792 and r(prediction)(2)=.688 for palm-1 model and r(2)=.927, r(adjusted)(2)=.908 and r(prediction)(2)=.779 for thumb-2 model). External validation for the QSAR models assured their prediction power with r(ext)(2)=.72 and .89 for palm-1 and thumb-2, respectively. Different docking protocols were examined for their validity to predict the correct binding poses of inhibitors inside their respective binding sites. Virtual screening was carried out on ZINC database using the generated pharmacophores, the selected valid docking algorithms and QSAR models to find compounds that could theoretically bind to both sites simultaneously.
机译:使用不同共结晶的酶抑制剂复合物的生物活性构象来产生和验证基于结构的药物,用于BASESCLIC-1和NS5B的拇指-2抑制剂。获得了两种药效模型,一种用于棕榈-1抑制剂,灵敏度= 0.929和特异性= 0.983,另一个具有灵敏度的拇指-2抑制剂= 1和特异性= 0.979。此外,基于使用不同评分功能的值开发了定量结构活动关系(QSAR)模型,作为预测颠覆结合位点(Palm-1和Thumb-2)上的活动的描述符。 QSAR研究揭示了良好的预测性和统计学意义的两个描述符模型(R(2)=。837,R(调整后)(2)=。792和R(预测)(2)=。688用于Palm-1型号和R(2 )=。927,R(调整)(2)=。908和R(预测)(2)=。779用于拇指-2模型)。 QSAR模型的外部验证将其预测功率与R(EXT)(2)=。72和.89分别用于Palm-1和Thumb-2。检查不同的对接方案的有效性以预测其各自结合位点内的正确结合抑制剂的正确结合姿势。虚拟筛选使用所生成的药理,所选的有效对接算法和QSAR模型在锌库中进行,以找到可以同时与两个站点定位的化合物。

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