Finding a needle in a haystack: the role of electrostatics in target lipid recognition by PH domains.
Finding a needle in a haystack: the role of electrostatics in target lipid recognition by PH domains.
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DOI：
10.1371/journal.pcbi.1002617
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发表时间：
2012
影响因子：
4.3
通讯作者：
Sansom MS
中科院分区：
文献类型：
--
作者：
Lumb CN;Sansom MS
蛋白质结构域和脂质分子之间的相互作用在控制细胞膜信号传导和运输中发挥着关键作用。 pleckstrin 同源 (PH) 结构域是最广泛的结构域之一，与细胞膜中的磷酸磷脂酰肌醇 (PIP) 特异性结合。 PH 结构域必须在质膜细胞质小叶内存在约 20% 阴离子脂质背景的情况下定位特定的 PIP。我们通过结合布朗动力学 (BD) 和分子动力学 (MD) 模拟 GRP1 PH 结构域与磷脂酰肌醇 (3,4,5)-三磷酸 (PI(3,4,5)P3) 相互作用的多尺度程序来研究这种识别的机制。将两性离子双层中 GRP1-PH 与 PI(3,4,5)P3 的相互作用与含有不同水平阴离子“诱饵”脂质的双层中的相互作用进行比较。 BD 模拟揭示了 PH 域向包含 PI(3,4,5)P3 的阴离子双层表面的平移和定向静电转向。非 PIP 阴离子脂质以有利的方向将 PH 结构域吸引到双层表面，与其作为“诱饵”的作用（破坏 GRP1-PH 与 PI(3,4,5)P3 分子的相互作用）之间存在回报。值得注意的是，双层细胞质小叶中大约 20% 的阴离子脂质对于增强定向转向和将 GRP1-PH 定位在膜表面附近几乎是最佳的，而不牺牲其在双层平面内定位 PI(3,4,5)P3 的能力。随后的 MD 模拟揭示了与 PI(3,4,5)P3 的结合，形成与 X 射线结构中的蛋白质-磷酸盐接触相当的接触。这些研究证明了一个计算框架，可以解决细胞膜环境中的脂质识别问题，提供结构和细胞生物学特征之间的联系。细胞信号传导途径对于许多生物过程（包括细胞增殖和存活）至关重要。信号传导受到细胞内复杂的相互作用网络的控制，信号传导的破坏可能导致多种人类疾病。通常，信号级联中的一个关键事件是外周膜蛋白可逆地募集到细胞膜表面，然后它们与特定的脂质结合以发挥其功能。然而，尚不清楚这些蛋白质如何在质膜复杂的多脂质环境中定位其目标脂质。在这里，我们使用了计算技术的组合来模拟信号蛋白与细胞膜表面的关联。我们证明膜结合的机制取决于脂质双层的脂质组成，结果表明，当我们的模型膜的阴离子脂质含量与细胞中观察到的生理组成相匹配时，蛋白质的方向和位置控制得到优化。
Interactions between protein domains and lipid molecules play key roles in controlling cell membrane signalling and trafficking. The pleckstrin homology (PH) domain is one of the most widespread, binding specifically to phosphatidylinositol phosphates (PIPs) in cell membranes. PH domains must locate specific PIPs in the presence of a background of approximately 20% anionic lipids within the cytoplasmic leaflet of the plasma membrane. We investigate the mechanism of such recognition via a multiscale procedure combining Brownian dynamics (BD) and molecular dynamics (MD) simulations of the GRP1 PH domain interacting with phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P3). The interaction of GRP1-PH with PI(3,4,5)P3 in a zwitterionic bilayer is compared with the interaction in bilayers containing different levels of anionic ‘decoy’ lipids. BD simulations reveal both translational and orientational electrostatic steering of the PH domain towards the PI(3,4,5)P3-containing anionic bilayer surface. There is a payoff between non-PIP anionic lipids attracting the PH domain to the bilayer surface in a favourable orientation and their role as ‘decoys’, disrupting the interaction of GRP1-PH with the PI(3,4,5)P3 molecule. Significantly, approximately 20% anionic lipid in the cytoplasmic leaflet of the bilayer is nearly optimal to both enhance orientational steering and to localise GRP1-PH proximal to the surface of the membrane without sacrificing its ability to locate PI(3,4,5)P3 within the bilayer plane. Subsequent MD simulations reveal binding to PI(3,4,5)P3, forming protein-phosphate contacts comparable to those in X-ray structures. These studies demonstrate a computational framework which addresses lipid recognition within a cell membrane environment, offering a link between structural and cell biological characterisation. Cell signalling pathways are crucial for many biological processes including cell proliferation and survival. Signalling is governed by a complex network of interactions within the cell, and disruption of signalling can lead to a variety of human diseases. Often, a key event in the signalling cascade is the reversible recruitment of peripheral membrane proteins to the surface of the cell membrane, where they then bind to a specific lipid in order to perform their function. However, it is not clear how these proteins locate their target lipid in the complex multi-lipid environment of the plasma membrane. Here, we have used a combination of computational techniques to simulate the association of a signalling protein with the surface of the cell membrane. We demonstrate that the mechanism of membrane binding is dependent upon the lipid composition of the lipid bilayer, and the results show that orientational and positional steering of the protein is optimised when the anionic lipid content of our model membrane matches the physiological composition observed in cells.
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