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相关概念视频

Protein-protein Interfaces02:04

Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Protein Complexes with Interchangeable Parts01:57

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Multi-pass Transmembrane Proteins and β-barrels01:09

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In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
α-Helix containing multi-pass transmembrane proteins
Multi-pass transmembrane proteins such as...
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Ligand Binding Sites02:40

Ligand Binding Sites

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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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相关实验视频

Updated: Sep 13, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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滑窗交互语法 (SWING):用于和蛋白相互作用的通用交互语言模型.

Jane C Siwek1,2,3,4, Alisa A Omelchenko1,2,3,4, Prabal Chhibbar1,2,5

  • 1Center for Systems immunology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.

Nature methods
|July 28, 2025
PubMed
概括

我们开发了滑窗交互语法 (SWING),一种交互语言模型 (iLM),用于预测蛋白质交互. SWING准确地预测了主要基因相容性复杂相互作用和变异效应,优于现有方法.

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科学领域:

  • 计算生物学是一种计算生物学.
  • 生物信息学是一种生物信息学.
  • 蛋白质科学是一种蛋白质科学.

背景情况:

  • 蛋白质语言模型对于序列嵌入至关重要,但在相互作用预测方面存在困难.
  • 了解蛋白质-蛋白质相互作用对于生物和疾病研究至关重要.

研究的目的:

  • 开发一种用于预测蛋白质相互作用的新型相互作用语言模型 (iLM).
  • 为了利用氨基酸性质,为专业的蛋白质相互作用词汇.
  • 评估模型对MHC类I和II相互作用和变异效应的性能.

主要方法:

  • 开发了一个iLM架构的滑动窗口交互语法 (SWING).
  • 利用氨基酸性质的差异来创建一个交互词汇.
  • 应用SWING来预测主要基因相容性复合体 (pMHC) 类I和II相互作用.
  • 评估了SWING能够预测变体中断相互作用和MHC类之间的交叉预测的能力.

主要成果:

  • SWING成功地预测了pMHC类I和II相互作用.
  • 第I类SWING模型展示了对II类相互作用的独特交叉预测能力.
  • SWING准确地预测了与自身免疫性疾病风险等位基因相关的小鼠pMHCII类相互作用.
  • 该模型准确地预测了序列变异如何破坏蛋白质-蛋白质相互作用.

结论:

  • SWING是一种可泛化,零射击的iLM,有效地学习蛋白质-蛋白质相互作用的语言.
  • 在交互预测方面,SWING的性能优于被动蛋白语言模型的嵌入.
  • 开发的iLM架构提供了一个有价值的工具,仅从序列数据预测蛋白质相互作用中断.