论文标题

低渗透性水合壳的空间布局指导蛋白质结合

Space Layout of Low-entropy Hydration Shells Guides Protein Binding

论文作者

Yang, Lin, Guo, Shuai, Hou, Chengyu, Liao, Chencheng, Li, Jiacheng, Shi, Liping, Ma, Xiaoliang, Jiang, Shenda, Zheng, Bing, Fang, Yi, Ye, Lin, He, Xiaodong

论文摘要

蛋白质 - 蛋白质结合可以有序,合法的生物学自我组织,因此被认为是自然的奇迹。蛋白质 - 蛋白质结合是通过静电力,氢键,范德华力和疏水相互作用来指导的。在这些物理力中,只能将疏水相互作用视为细胞内和细胞外液中蛋白质之间的长距离分子间吸引。蛋白质周围的水合壳的低渗透区域驱动它们之间的疏水吸引力,这些吸引在结合的指导阶段基本上是在相互取向的旋转构成空间中进行蛋白质 - 蛋白质对接的。在这里,开发了一种创新的方法,用于识别给定蛋白质的水合壳的低渗透区域,我们发现蛋白质上最大的水合壳的低渗透区域通常覆盖结合位点。根据确定的蛋白质复合物结构的分析,蛋白质最大的低渗透水合壳区域与其在结合位点的伴侣的形状匹配被揭示为常规模式。因此,发现蛋白质 - 蛋白质结合主要是由形状匹配的低渗透性水合壳之间的疏水性塌陷来指导,这些壳通过数百种蛋白质复合物结构的生物信息学分析来验证。开发了一种简单的算法来精确预测蛋白质结合位点。

Protein-protein binding enables orderly and lawful biological self-organization, and is therefore considered a miracle of nature. Protein-protein binding is steered by electrostatic forces, hydrogen bonding, van der Waals force, and hydrophobic interactions. Among these physical forces, only the hydrophobic interactions can be considered as long-range intermolecular attractions between proteins in intracellular and extracellular fluid. Low-entropy regions of hydration shells around proteins drive hydrophobic attraction among them that essentially coordinate protein-protein docking in rotational-conformational space of mutual orientations at the guidance stage of the binding. Here, an innovative method was developed for identifying the low-entropy regions of hydration shells of given proteins, and we discovered that the largest low-entropy regions of hydration shells on proteins typically cover the binding sites. According to an analysis of determined protein complex structures, shape matching between the largest low-entropy hydration shell region of a protein and that of its partner at the binding sites is revealed as a regular pattern. Protein-protein binding is thus found to be mainly guided by hydrophobic collapse between the shape-matched low-entropy hydration shells that is verified by bioinformatics analyses of hundreds of structures of protein complexes. A simple algorithm is developed to precisely predict protein binding sites.

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