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相关概念视频

Induced-fit Model01:13

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Most chemical reactions in cells require enzymes—biological catalysts that speed up the reaction without being consumed or permanently changed. They reduce the activation energy needed to convert the reactants into products. Enzymes are proteins, that usually work by binding to a substrate—a reactant molecule that they act upon.
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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通过流量匹配来适应基于结构的蛋白质-蛋白质对接的共同折叠模型.

Da Xu1, Lee-Shin Chu1, Jeffrey J Gray1

  • 1Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.

bioRxiv : the preprint server for biology
|December 11, 2025
PubMed
概括
此摘要是机器生成的。

我们开发了AF2Dock,这是一种基于结构的新型蛋白质-蛋白质对接方法,适应了共折叠模型. AF2Dock在预测抗体-抗原复合体方面表现出色,优于纳米体目标的现有方法.

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科学领域:

  • 计算生物学是一种计算生物学.
  • 结构生物学是结构生物学.
  • 生物信息学是一种生物信息学.

背景情况:

  • 像AlphaFold这样的共同折叠模型在蛋白质复合体预测方面表现出色,但在缺乏多个序列对齐 (MSA) 的目标上扎.
  • 基于结构的蛋白质-蛋白质对接提供了一个替代方案,通过预测没有MSAs的未结合单体的结合结构.

研究的目的:

  • 为了适应基于结构的蛋白质-蛋白质对接的共同折叠模型.
  • 通过修改AlphaFold-Multimer (AF-M) 来开发一个名为AF2Dock的生成对接模型.

主要方法:

  • 用一个对接模块替换了AF-M的模板模块.
  • 使用流程匹配目标,对修改后的模型进行端到端的训练.
  • 将该方法应用于AF-M的OpenFold实现,创建了AF2Dock.

主要成果:

  • AF2Dock在使用非holo输入的PINDER-AF2基准和抗体/纳米体数据集上展示了具有竞争力的性能.
  • AF2Dock超越了对纳米体复合体的所有测试对接方法.
  • AF2Dock提供了直角预测,成功地解决了共同折叠模型失败的情况.

结论:

  • AF2Dock代表了基于结构的蛋白质-蛋白质对接的共同折叠模型的新适应.
  • 全参数微调对于AF-M组件在对接中的性能至关重要.
  • 该研究强调了将共同折叠架构集成到对接策略中的潜力和局限性.