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相关概念视频

T Cell Activation and Clonal Selection01:22

T Cell Activation and Clonal Selection

679
T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...
679
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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Conserved Binding Sites01:49

Conserved Binding Sites

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Selectins01:25

Selectins

3.3K
Cell adhesion is  an essential aspect of multicellularity. While stable cell interactions usually occur between cells of the same type, transient cell interactions occur between cells of different tissue types, such as between neutrophils and endothelial cells. Selectins are one class of cell adhesion molecules (CAMs) that bind carbohydrate ligands to form transient cell adhesion. They are rod-like proteins with a long extracellular part of variable length ending with the lectin domain,...
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Ligand Binding Sites02:40

Ligand Binding Sites

12.8K
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: Jun 10, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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特性选择提高了对TCR特定相互作用的结预测.

Hamid Teimouri1,2, Zahra S Ghoreyshi2,3, Anatoly B Kolomeisky1,2,4

  • 1Department of Chemistry, Rice University, Houston, TX, 77005, USA.

bioRxiv : the preprint server for biology
|October 17, 2024
PubMed
概括

特征选择可以改善T细胞受体 (TCR) 和结合的预测. 这种方法通过识别针对性治疗的关键结合特征来增强免疫疗法和疫苗设计.

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Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
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Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay
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相关实验视频

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay
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科学领域:

  • 免疫学 免疫学 免疫学
  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • T细胞受体 (TCR) 识别-MHC复合体,对于适应性免疫至关重要.
  • 预测TCR-相互作用对于免疫疗法,疫苗开发和自身免疫性疾病研究至关重要.

研究的目的:

  • 开发和评估一种新的理论方法,以提高TCR-结合预测的准确性.
  • 研究特征选择技术对特定TCR预测模型的影响.

主要方法:

  • 利用类库的数据集对三种不同的小鼠TCR进行了测试.
  • 将物理化学特性 (氨基酸,二,三特征) 集成到机器学习框架中.
  • 应用特征选择以确定关键贡献者,以结合亲和力.

主要成果:

  • 优化的特征子集简化了模型的复杂性,提高了预测性能.
  • 该方法精确地确定了TCR-相互作用.
  • 结果与混合序列结构和实验数据保持一致.

结论:

  • 特征选择是理解TCR-相互作用的强大工具.
  • 这种理论方法有助于揭示T细胞反应机制.
  • 这些发现支持先进的向治疗的设计.