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Ligand Docking to Intermediate and Close-To-Bound Conformers Generated by an Elastic Network Model Based Algorithm for Highly Flexible Proteins

机译:配体对接至基于弹性网络模型的高柔性蛋白质算法生成的中间和近界构象异构体

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摘要

Incorporating receptor flexibility in small ligand-protein docking still poses a challenge for proteins undergoing large conformational changes. In the absence of bound structures, sampling conformers that are accessible by apo state may facilitate docking and drug design studies. For this aim, we developed an unbiased conformational search algorithm, by integrating global modes from elastic network model, clustering and energy minimization with implicit solvation. Our dataset consists of five diverse proteins with apo to complex RMSDs 4.7–15 Å. Applying this iterative algorithm on apo structures, conformers close to the bound-state (RMSD 1.4–3.8 Å), as well as the intermediate states were generated. Dockings to a sequence of conformers consisting of a closed structure and its “parents” up to the apo were performed to compare binding poses on different states of the receptor. For two periplasmic binding proteins and biotin carboxylase that exhibit hinge-type closure of two dynamics domains, the best pose was obtained for the conformer closest to the bound structure (ligand RMSDs 1.5–2 Å). In contrast, the best pose for adenylate kinase corresponded to an intermediate state with partially closed LID domain and open NMP domain, in line with recent studies (ligand RMSD 2.9 Å). The docking of a helical peptide to calmodulin was the most challenging case due to the complexity of its 15 Å transition, for which a two-stage procedure was necessary. The technique was first applied on the extended calmodulin to generate intermediate conformers; then peptide docking and a second generation stage on the complex were performed, which in turn yielded a final peptide RMSD of 2.9 Å. Our algorithm is effective in producing conformational states based on the apo state. This study underlines the importance of such intermediate states for ligand docking to proteins undergoing large transitions.
机译:在小的配体-蛋白质对接中结合受体柔性仍然对经历大构象变化的蛋白质构成挑战。在没有结合结构的情况下,载脂蛋白状态可访问的采样构象异构体可能有助于对接和药物设计研究。为此,我们通过整合弹性网络模型,聚类和能量最小化与隐式溶剂化的全局模式,开发了一种无偏构象搜索算法。我们的数据集由五种多样的蛋白质组成,载脂蛋白为4.7–15Å的复杂RMSD。将这种迭代算法应用于载脂蛋白结构,可生成接近于结合态(RMSD 1.4–3.8Å)的构象异构体以及中间态。进行了对由封闭结构及其“亲本”组成的一系列构象异构体的对接,直至apo,以比较受体不同状态下的结合姿势。对于表现出两个动态结构域铰链型闭合的两种周质结合蛋白和生物素羧化酶,对于最接近结合结构的配体(配体RMSD 1.5–2Å)可获得最佳姿势。相反,根据最近的研究(配体RMSD 2.9Å),腺苷酸激酶的最佳姿势对应于一个中间状态,该状态具有部分关闭的LID结构域和开放的NMP结构域。螺旋肽与钙调蛋白的对接是最具挑战性的情况,因为其15Å过渡的复杂性,为此需要两步操作。该技术首先应用于扩展的钙调蛋白,以生成中间构象异构体。然后进行肽对接并在复合物上进行第二代测序,最终得到的肽RMSD为2.9。我们的算法有效地基于apo状态产生构象状态。这项研究强调了这种中间状态对于配体对接经历大转变的蛋白质的重要​​性。

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  • 年(卷),期 -1(11),6
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  • 页码 e0158063
  • 总页数 22
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