A new, structurally nonredundant, diverse data set of protein-protein interfaces and its implications
A new, structurally nonredundant, diverse data set of protein-protein interfaces and its implications
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DOI：
10.1110/ps.03484604
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发表时间：
2004-04-01
期刊：
影响因子：
8
通讯作者：
Nussinov, R
中科院分区：
文献类型：
--
作者：
Keskin, O;Tsai, CJ;Nussinov, R
在此，我们展示了一个多样的、结构上无冗余的双链蛋白质 - 蛋白质相互作用界面数据集，该数据集源自蛋白质数据库（PDB）。通过使用一种不依赖序列顺序的结构比较算法和层次聚类方法，获得了3799个界面聚类。其中有103个聚类至少包含五个非同源成员。我们将这些聚类分为三种类型。在I型聚类中，产生这些界面的链的整体结构也是相似的。出现这种聚类类型是预料之中的，因为一般来说，相关蛋白质以相似的方式相互作用。在II型中，界面是相似的；然而，值得注意的是，链的整体结构和功能是不同的。其功能范围很广，从酶/抑制剂到免疫球蛋白和毒素。结构不同的单体以相似方式相互作用这一事实表明存在“良好”的结合结构。这一观察结果扩展了蛋白质科学中的一个范式：众所周知，结构相似的蛋白质可能具有不同的功能。在此，我们表明这也适用于蛋白质的相互作用界面。在III型聚类中，整个聚类中只有界面的一侧是相似的。这个结构上无冗余的数据集为蛋白质 - 蛋白质相互作用和识别、细胞网络以及药物设计的研究提供了丰富的数据。特别是，它可能有助于解决蛋白质相互作用的有利方式是什么这一难题。
Here. we present a diverse, structurally nonredundant data set of two-chain protein-protein interfaces derived from the PDB. Using a sequence order-independent structural comparison algorithm and hierarchical clustering, 3799 interface clusters are obtained. These yield 103 clusters with at least five nonhomologous members. We divide the clusters into three types. In Type I clusters, the global structures of the chains from which the interfaces are derived are also similar. This cluster type is expected because, in general, related proteins associate in similar ways. In Type II, the interfaces are similar; however, remark ably, the overall structures and functions of the chains are different. The functional spectrum is broad, from enzymes/inhibitors to immunoglobulins and toxins. The fact that structurally different monomers associate in similar ways. suggests "good" binding architectures. This observation extends a paradigm in protein science: It has been well known that proteins with similar structures may have different functions. Here, we show that it extends to inter-faces. In Type III clusters, only one side of the interface is similar across the cluster. This structurally nonredundant data set provides rich data for studies of protein-protein interactions and recognition, cellular networks and drug design. In particular, it may be useful in addressing the difficult question of what are the favorable ways for proteins to interact.