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相关概念视频

Protein Folding01:22

Protein Folding

Overview
Protein Folding01:25

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...

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用TriFlow进行大规模蛋白质设计的结构条件序列景观建模.

Harish Srinivasan1,2, Rongqing Yuan2,3, Qian Cong3,4,5

  • 1Department of Genetics Medicine, University of Chicago, Chicago, IL, USA.

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概括

通过整合全球结构上下文和高效的序列生成,TriFlow增强了计算蛋白质设计. 这种新型模型显著提高了各种蛋白质标的新型结合剂设计成功率.

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科学领域:

  • 计算生物学是一种计算生物学.
  • 蛋白质工程是一种蛋白质工程.
  • 机器学习是机器学习.

背景情况:

  • 生成模型是计算蛋白质设计的关键.
  • 目前的方法使用本地环境和自回归生成,限制效率和质量.
  • 从骨干结构开始高质量的序列设计至关重要.

研究的目的:

  • 开发一个高效和高质量的蛋白质序列设计模型.
  • 改进新的粘合剂设计能力.
  • 为了探索结构条件的序列景观.

主要方法:

  • 开发了TriFlow,一个使用RoseTTAFold类三轨架构的模型,用于全球结构上下文.
  • 采用离散流量匹配,以实现高效,少数步骤的序列生成.
  • 在相互作用的蛋白质链 (PDB) 和域 (AlphaFold DB) 上接受训练,以学习接口属性.

主要成果:

  • 在所有基准测试中,TriFlow表现有所改善,特别是在新型粘合剂设计中.
  • 提升了像BindCraft这样的最先进管道的in silico成功率.
  • 成功生成并验证了500多种不同的蛋白质标的结合剂.
  • 通过对比模型约束与进化配置文件,突出显示功能活跃区域.
  • 展示了针对人类I类细胞因子的特定结合物的系统设计,优化了亲和力,并最大限度地减少了非目标相互作用.

结论:

  • 三流为大规模蛋白质工程提供了一个强大的框架.
  • 提供了一种探索结构条件序列景观的基本原理的方法.
  • 提高了计算蛋白质设计的效率和质量,特别是在绑定器设计中.