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Natively unstructured regions in proteins identified from contact predictions

机译:根据接触预测确定的蛋白质中天然非结构化区域

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Motivation: Natively unstructured (also dubbed intrinsically disordered) regions in proteins lack a defined 3D structure under physiological conditions and often adopt regular structures under particular conditions. Proteins with such regions are overly abundant in eukaryotes, they may increase functional complexity of organisms and they usually evade structure determination in the unbound form. Low propensity for the formation of internal residue contacts has been previously used to predict natively unstructured regions.Results: We combined PROFcon predictions for protein-specific contacts with a generic pairwise potential to predict unstructured regions. This novel method, Ucon, outperformed the best available methods in predicting proteins with long unstructured regions. Furthermore, Ucon correctly identified cases missed by other methods. By computing the difference between predictions based on specific contacts (approach introduced here) and those based on generic potentials (realized in other methods), we might identify unstructured regions that are involved in protein-protein binding. We discussed one example to illustrate this ambitious aim. Overall, Ucon added quality and an orthogonal aspect that may help in the experimental study of unstructured regions in network hubs.
机译:动机:蛋白质中的天然非结构化(也称为内在无序)区域在生理条件下缺乏定义的3D结构,在特定条件下通常采用规则结构。具有此类区域的蛋白质在真核生物中含量过多,它们可能会增加生物体的功能复杂性,并且通常会以未结合形式逃避结构确定。内部残基接触形成的可能性较低,以前曾被用来预测天然的非结构化区域。结果:我们结合了蛋白质特异性接触的PROFcon预测和通用的成对电位预测非结构化区域。 Ucon这种新方法在预测具有较长非结构化区域的蛋白质方面优于最佳方法。此外,Ucon可以正确识别其他方法遗漏的案例。通过计算基于特定接触(此处介绍的方法)的预测与基于通用潜力(以其他方法实现的预测)之间的差异,我们可以确定参与蛋白质-蛋白质结合的非结构化区域。我们讨论了一个例子来说明这一宏伟目标。总体而言,Ucon增加了质量和正交方面,这可能有助于网络集线器中非结构化区域的实验研究。

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