Shulman-Peleg Alexandra, Shatsky Maxim, Nussinov Ruth, Wolfson Haim J
School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences Tel Aviv University, Tel Aviv 69978, Israel.
BMC Biol. 2007 Oct 9;5:43. doi: 10.1186/1741-7007-5-43.
Conservation of the spatial binding organizations at the level of physico-chemical interactions is important for the formation and stability of protein-protein complexes as well as protein and drug design. Due to the lack of computational tools for recognition of spatial patterns of interactions shared by a set of protein-protein complexes, the conservation of such interactions has not been addressed previously.
We performed extensive spatial comparisons of physico-chemical interactions common to different types of protein-protein complexes. We observed that 80% of these interactions correspond to known hot spots. Moreover, we show that spatially conserved interactions allow prediction of hot spots with a success rate higher than obtained by methods based on sequence or backbone similarity. Detection of spatially conserved interaction patterns was performed by our novel MAPPIS algorithm. MAPPIS performs multiple alignments of the physico-chemical interactions and the binding properties in three dimensional space. It is independent of the overall similarity in the protein sequences, folds or amino acid identities. We present examples of interactions shared between complexes of colicins with immunity proteins, serine proteases with inhibitors and T-cell receptors with superantigens. We unravel previously overlooked similarities, such as the interactions shared by the structurally different RNase-inhibitor families.
The key contribution of MAPPIS is in discovering the 3D patterns of physico-chemical interactions. The detected patterns describe the conserved binding organizations that involve energetically important hot spot residues and are crucial for the protein-protein associations.
在物理化学相互作用层面上,空间结合组织的保守性对于蛋白质 - 蛋白质复合物的形成与稳定性以及蛋白质和药物设计而言至关重要。由于缺乏用于识别一组蛋白质 - 蛋白质复合物所共有的相互作用空间模式的计算工具,此类相互作用的保守性此前尚未得到探讨。
我们对不同类型蛋白质 - 蛋白质复合物共有的物理化学相互作用进行了广泛的空间比较。我们观察到这些相互作用中有80%对应于已知的热点。此外,我们表明空间保守的相互作用能够预测热点,其成功率高于基于序列或主链相似性的方法。通过我们新颖的MAPPIS算法进行空间保守相互作用模式的检测。MAPPIS在三维空间中对物理化学相互作用和结合特性进行多重比对。它独立于蛋白质序列、折叠或氨基酸同一性的整体相似性。我们展示了大肠杆菌素与免疫蛋白复合物、丝氨酸蛋白酶与抑制剂复合物以及T细胞受体与超抗原复合物之间共享的相互作用实例。我们揭示了先前被忽视的相似性,例如结构不同的核糖核酸酶抑制剂家族之间共享的相互作用。
MAPPIS的关键贡献在于发现物理化学相互作用的三维模式。所检测到的模式描述了涉及能量上重要的热点残基且对蛋白质 - 蛋白质缔合至关重要的保守结合组织。