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Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
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随着承诺者流:一个数据驱动的过渡途径的发现.

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  • 1Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n°7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy cedex, France.

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概括

这项研究引入了一种新的代框架,以准确识别分子过渡途径并估计反应速率. 该方法通过使用神经网络来改进犯人概率,以进行增强的分子动态模拟.

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科学领域:

  • 计算化学的计算化学
  • 分子动力学分子动力学
  • 反应机制的发现反应机制的发现

背景情况:

  • 在分子系统中识别罕见事件和过渡途径仍然是一个重大挑战.
  • 提交者概率是分子模拟中定义反应坐标的关键指标.
  • 确保过渡路径和提交函数之间的一致性对于机械准确性至关重要.

研究的目的:

  • 开发一个代框架来推断犯人概率.
  • 确定和完善分子系统中最相关的过渡途径.
  • 为了能够准确地估计反应速率常数.

主要方法:

  • 一种使用偏向抽样和神经网络近似进行犯人概率的代方法.
  • 从已学到的委托器同委托器表面提取主导过渡通道.
  • 代改进提交者和过渡路径,直到趋同.

主要成果:

  • 拟议的框架成功地推断了犯人概率,并确定了关键的过渡途径.
  • 在基准系统上证明有效性:2D模型潜力,过渡,迪尔斯-阿尔德反应和Trp折叠.
  • 精细的提交器可以准确地估计反应速率常数.

结论:

  • 代框架为发现过渡途径和理解反应机制提供了一个强大的方法.
  • 这种方法通过提高犯人估计的准确性来增强分子动力学模拟.
  • 该方法在研究分子系统中罕见事件方面取得了重大进展.