Energy landscape of all-atom protein-protein interactions revealed by multiscale enhanced sampling.
Energy landscape of all-atom protein-protein interactions revealed by multiscale enhanced sampling.
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DOI：
10.1371/journal.pcbi.1003901
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发表时间：
2014-10
影响因子：
4.3
通讯作者：
Kidera A
中科院分区：
文献类型：
--
作者：
Moritsugu K;Terada T;Kidera A
蛋白质与蛋白质之间的相互作用是由复杂的原子相互作用和界面溶剂化作用的微妙平衡来调节的。为了理解这种难以捉摸的现象，有必要使用全原子模型在显式溶剂中彻底调查从稳定的复合物结构到解离态的大构型空间，并描绘蛋白质-蛋白质相互作用的能量景观。在这项研究中，我们进行了多尺度增强采样（MSES）模拟的barnase-barstar复合物的形成，这是一种蛋白质复合物，其特征在于一个非常紧密和快速的结合，以确定原子蛋白质-蛋白质相互作用的能量景观。MSES采用了多拷贝和多尺度方案，使大蛋白质的全原子模型，包括明确的溶剂的增强采样。在对barnase-barstar系统进行100 ns的MSES模拟过程中，我们多次观察到了蛋白质原子复合物在溶液中的缔合-解离过程，其中不仅包含天然的复合物结构，而且包含完全非天然的构型.抽样分布表明，大量的非原生状态走下坡路的稳定复杂的结构，像一个快速折叠的漏斗状的潜力。这种漏斗景观归因于在以近天然取向为特征的缔合过程的早期阶段的主导构型，这将加速天然分子间相互作用。这些配置主要是由芽孢杆菌和芽孢杆菌之间的形状互补性，并导致快速形成的最终复杂的结构沿着下坡能源景观。蛋白质相互作用的动力学性质是细胞代谢反应和信号转导等过程的重要组成部分，但其原子细节仍不清楚。利用分子动力学模拟的计算研究是一种简单的方法来阐明这些原子蛋白质-蛋白质相互作用过程。然而，一个足够的配置采样的大系统包含原子蛋白质复合物模型和明确的溶剂仍然是一个巨大的挑战，由于涉及的时间尺度长。在这里，我们证明了多尺度增强采样（MSES）成功地捕获了原子的细节的结合/解离过程的barnase-barstar复杂覆盖采样空间从本地复杂的结构，完全非本地配置。从模拟中得到的景观表明，缔合过程是漏斗状的下坡，类似于快速折叠蛋白质的漏斗景观。漏斗被发现起源于barnase和barstar之间的形状互补性引导的近天然取向，加速天然分子间相互作用的形成以完成最终的复合物结构。
Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES) simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape. Dynamic nature of the protein-protein interactions is an important element of cellular processes such as metabolic reactions and signal transduction, but its atomistic details are still unclear. Computational survey using molecular dynamics simulation is a straightforward method to elucidate these atomistic protein-protein interaction processes. However, a sufficient configurational sampling of the large system containing the atomistic protein complex model and explicit solvent remains a great challenge due to the long timescale involved. Here, we demonstrate that the multiscale enhanced sampling (MSES) successfully captured the atomistic details of the association/dissociation processes of a barnase-barstar complex covering the sampled space from the native complex structure to fully non-native configurations. The landscape derived from the simulation indicates that the association process is funnel-like downhill, analogously to the funnel landscape of fast-folding proteins. The funnel was found to be originated from near-native orientations guided by the shape complementarity between barnase and barstar, accelerating the formation of native inter-molecular interactions to complete the final complex structure.
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影响因子：
5.6
作者：
Hills RD Jr;Brooks CL 3rd
通讯作者：
Brooks CL 3rd
DOI：
10.1073/pnas.0914540107
发表时间：
2010-03-16
影响因子：
11.1
作者：
Abrams, Cameron F.;Vanden-Eijnden, Eric
通讯作者：
Vanden-Eijnden, Eric
DOI：
10.1073/pnas.070052697
发表时间：
2000-04-11
影响因子：
11.1
作者：
Baumgartner, W;Hinterdorfer, P;Drenckhahn, D
通讯作者：
Drenckhahn, D
影响因子：
4.4
作者：
Fukunishi, H;Watanabe, O;Takada, S
通讯作者：
Takada, S
影响因子：
56.9
作者：
FRAUENFELDER, H;SLIGAR, SG;WOLYNES, PG
通讯作者：
WOLYNES, PG