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DiMoVo: a Voronoi tessellation-based method for discriminating crystallographic and biological proteinprotein interactions

机译:DiMoVo:一种基于Voronoi镶嵌的方法,用于区分晶体学和生物蛋白相互作用

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Motivation: Knowledge of the oligomeric state of a protein is often essential for understanding its function and mechanism. Within a protein crystal, each protein monomer is in contact with many others, forming many small interfaces and a few larger ones that are biologically significant if the protein is a homodimer in solution, but not if the protein is monomeric. Telling such crystal dimers from real ones remains a difficult task. Results: It has already been demonstrated that the interfaces of native and non-native proteinprotein complexes can be distinguished using a combination of parameters computed with a method on the Voronoi tessellation. We show in this article that the same parameters highlight significant differences between the interfaces of biological and crystal dimers. Using these parameters as descriptors in machine learning methods leads to accurate classification of specific and non-specific proteinprotein interfaces.
机译:动机:了解蛋白质的低聚状态通常对于理解其功能和机制至关重要。在蛋白质晶体中,每种蛋白质单体都与许多其他单体接触,形成许多小的界面和一些较大的界面,如果该蛋白质是溶液中的同型二聚体,则具有生物学意义,但如果该蛋白质是单体则不是。从真实的二聚体中分辨出来仍然是一项艰巨的任务。结果:已经证明,可以使用通过Voronoi细分方法计算的参数组合来区分天然蛋白蛋白质复合物和非天然蛋白蛋白质复合物的界面。我们在本文中表明,相同的参数突出显示了生物二聚体和晶体二聚体之间的显着差异。在机器学习方法中使用这些参数作为描述符会导致对特定和非特定蛋白界面的准确分类。

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