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首页> 外文期刊>Journal of chemical information and modeling >Integrating ligand-based and protein-centric virtual screening of kinase inhibitors using ensembles of multiple protein kinase genes and conformations
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Integrating ligand-based and protein-centric virtual screening of kinase inhibitors using ensembles of multiple protein kinase genes and conformations

机译:使用多个蛋白激酶基因和构象的整合体,对激酶抑制剂进行基于配体的和蛋白中心的虚拟筛选

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The rapidly growing wealth of structural and functional information about kinase genes and kinase inhibitors that is fueled by a significant therapeutic role of this protein family provides a significant impetus for development of targeted computational screening approaches. In this work, we explore an ensemble-based, protein-centric approach that allows for simultaneous virtual ligand screening against multiple kinase genes and multiple kinase receptor conformations. We systematically analyze and compare the results of ligand-based and protein-centric screening approaches using both single-receptor and ensemble-based docking protocols. A panel of protein kinase targets that includes ABL, EGFR, P38, CDK2, TK, and VEGFR2 kinases is used in this comparative analysis. By applying various performance metrics we have shown that ligand-centric shape matching can provide an effective enrichment of active compounds outperforming single-receptor docking screening. However, ligand-based approaches can be highly sensitive to the choice of inhibitor queries. Employment of multiple inhibitor queries combined with parallel selection ranking criteria can improve the performance and efficiency of ligand-based virtual screening. We also demonstrated that replica-exchange Monte Carlo docking with kinome-based ensembles of multiple crystal structures can provide a superior early enrichment on the kinase targets. The central finding of this study is that incorporation of the template-based structural information about kinase inhibitors and protein kinase structures in diverse functional states can significantly enhance the overall performance and robustness of both ligand and protein-centric screening strategies. The results of this study may be useful in virtual screening of kinase inhibitors potentially offering a beneficial spectrum of therapeutic activities across multiple disease states.
机译:由该蛋白家族的重要治疗作用推动的有关激酶基因和激酶抑制剂的结构和功能信息的迅速增长,为靶向计算筛选方法的发展提供了重要动力。在这项工作中,我们探索了一种基于整体的,以蛋白质为中心的方法,该方法可以针对多个激酶基因和多个激酶受体构象同时进行虚拟配体筛选。我们系统地分析和比较使用单受体和基于集合的对接协议的基于配体和蛋白质为中心的筛选方法的结果。在此比较分析中使用了一组蛋白激酶靶标,包括ABL,EGFR,P38,CDK2,TK和VEGFR2激酶。通过应用各种性能指标,我们已经表明,以配体为中心的形状匹配可以提供比单受体对接筛选更有效的活性化合物富集。但是,基于配体的方法对抑制剂查询的选择可能非常敏感。使用多个抑制剂查询与并行选择排名标准相结合,可以提高基于配体的虚拟筛选的性能和效率。我们还证明了副本交换蒙特卡罗对接与多个晶体结构的基于kinome的合奏可以在激酶靶标上提供优异的早期富集。这项研究的主要发现是,在各种功能状态下结合有关激酶抑制剂和蛋白激酶结构的基于模板的结构信息可以显着增强配体和以蛋白为中心的筛选策略的整体性能和鲁棒性。这项研究的结果可能在激酶抑制剂的虚拟筛选中很有用,可能会在多种疾病状态下提供有益的治疗活性。

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