Probing the flexibility of large conformational changes in protein structures through local perturbations.
Probing the flexibility of large conformational changes in protein structures through local perturbations.
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DOI：
10.1371/journal.pcbi.1000343
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发表时间：
2009-04
影响因子：
4.3
通讯作者：
Agard DA
中科院分区：
文献类型：
--
作者：
Ho BK;Agard DA
蛋白质的构象变化和动态行为是催化、调节和底物识别等过程的基础。尽管在计算机模拟中已经成功地探索了蛋白质动力学，但有一种中等规模的运动被证明是难以模拟的——独立于蛋白质体运动的单个片段或区域的运动。在这里，我们介绍了一种分子动力学摄动方法，即旋转诱导摄动（RIP），该方法通过对单个侧链施加大的扭转摄动，可以在皮秒内产生结构元件的大的相干运动。尽管有大规模的运动，二级结构元件保持完整，不需要施加骨干位置约束。由于它的计算效率，RIP可以应用于蛋白质中的每一个残基，产生一个全局的可变形性图。这张图非常稀疏，主要的变形位点通常出现在蛋白质表面。全球图谱可用于识别与蛋白质结合较不紧密的环和螺旋，因此可能是可能具有重要功能后果的动态调节位点。此外，他们还确定了具有驱动大规模相干构象变化潜力的单个残基。将RIP应用于两种研究得很好的蛋白质，二氢叶酸还原酶和三磷酸异构酶，它们具有在微秒/毫秒时间尺度上波动的功能相关的移动环，RIP变形图识别并再现了这些元素的灵活性。相比之下，α-裂解蛋白酶（一种动力学稳定的蛋白质）的RIP变形图没有明显的变形。在HSP90的n端结构域中，RIP变形图清楚地识别出配体结合盖是一个高度灵活的区域，能够发生大的构象变化。在雌激素受体配体结合区域，RIP变形图谱非常稀疏，除了涉及螺旋-12的一个大构象变化，螺旋-12是配体结合与受体激活变构连接的结构元件。RIP分析有可能发现功能性构象变化的位点和确定这些构象状态的关键残基。许多蛋白质通过剧烈运动来实现它们的生物学功能。这些运动的确切性质通常是从处于不同状态的蛋白质的晶体结构中推断出来的，这通常构成了一系列困难的实验。由于分子动力学被普遍接受为精确地模拟蛋白质的运动，因此有希望的是，足够长的模拟将产生给定蛋白质结构的所有运动。不幸的是，目前的系统运行速度太慢，除了最小的运动外，无法模拟所有的运动。为了克服这种计算限制，我们开发了一种分子动力学摄动方法，可以在很短的模拟时间内诱导蛋白质结构的大变化。这些变化与蛋白质表面特定结构元素的大运动相对应，这与几种具有良好特征的蛋白质的典型运动相吻合。这对我们的方法来说是个好兆头，对于任何给定的蛋白质结构，表面上可能结合药物、调节信号、经历化学修饰或变得非结构化的结构元素。
Protein conformational changes and dynamic behavior are fundamental for such processes as catalysis, regulation, and substrate recognition. Although protein dynamics have been successfully explored in computer simulation, there is an intermediate-scale of motions that has proven difficult to simulate—the motion of individual segments or domains that move independently of the body the protein. Here, we introduce a molecular-dynamics perturbation method, the Rotamerically Induced Perturbation (RIP), which can generate large, coherent motions of structural elements in picoseconds by applying large torsional perturbations to individual sidechains. Despite the large-scale motions, secondary structure elements remain intact without the need for applying backbone positional restraints. Owing to its computational efficiency, RIP can be applied to every residue in a protein, producing a global map of deformability. This map is remarkably sparse, with the dominant sites of deformation generally found on the protein surface. The global map can be used to identify loops and helices that are less tightly bound to the protein and thus are likely sites of dynamic modulation that may have important functional consequences. Additionally, they identify individual residues that have the potential to drive large-scale coherent conformational change. Applying RIP to two well-studied proteins, Dihdydrofolate Reductase and Triosephosphate Isomerase, which possess functionally-relevant mobile loops that fluctuate on the microsecond/millisecond timescale, the RIP deformation map identifies and recapitulates the flexibility of these elements. In contrast, the RIP deformation map of α-lytic protease, a kinetically stable protein, results in a map with no significant deformations. In the N-terminal domain of HSP90, the RIP deformation map clearly identifies the ligand-binding lid as a highly flexible region capable of large conformational changes. In the Estrogen Receptor ligand-binding domain, the RIP deformation map is quite sparse except for one large conformational change involving Helix-12, which is the structural element that allosterically links ligand binding to receptor activation. RIP analysis has the potential to discover sites of functional conformational changes and the linchpin residues critical in determining these conformational states. Many proteins undergo large motions to carry out their biological functions. The exact nature of these motions is typically inferred from the crystal structures of the protein trapped in different states, which normally constitutes a difficult series of experiments. As molecular dynamics is generally accepted to accurately model the motion of proteins, the promise is that a long enough simulation will generate all the motions of a given protein structure. Unfortunately, current systems run too slowly to simulate all but the smallest motions. To overcome this computational limit, we have developed a molecular-dynamics perturbation method that induces large changes in a protein structure in very short simulation times. The changes correspond to large motions of specific structural elements on the surface of the protein that corroborate well with the canonical motions of several well-characterized proteins. This bodes well for our method to identify, for any given protein structure, structural elements on the surface that might bind drugs, regulate signals, undergo chemical modifications, or become unstructured.
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