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相关概念视频

Diversity of Antigen Receptors01:28

Diversity of Antigen Receptors

478
Antigen receptors are essential components of the immune system crucial in defending the body against foreign invaders. These receptors are present on the surface of B and T cells, enabling them to recognize antigens and mount an appropriate immune response.
Before encountering any antigen, lymphocytes express these receptors. On B cells, the antigen receptor is a membrane-bound antibody molecule called BCR; on T cells, it is a T cell receptor or TCR. B and T cell receptors are composed of two...
478

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相关实验视频

Updated: May 24, 2025

qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like Receptor Genes
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TRain:T细胞受体自动化免疫信息学

Austin Seamann1, Maia Bennett-Boehm1, Ryan Ehrlich1

  • 1School of Interdisciplinary Informatics, College of Information Science and Technology, University of Nebraska at Omaha, 1110 S 67TH, Omaha, NE, 68182, USA.

BMC bioinformatics
|March 6, 2025
PubMed
概括

一个新的Python工具TRain自动化了从序列数据中预测T细胞受体 (TCR) 和-MHC (pMHC) 复杂结构的复杂过程. 该工具通过简化TCR-pMHC结合分析,有助于理解自适应性免疫反应.

关键词:
免疫信息学是指免疫信息学.在TCR建模中,蛋白质对接的对接方式

更多相关视频

A TIRF Microscopy Technique for Real-time, Simultaneous Imaging of the TCR and its Associated Signaling Proteins
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T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing
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相关实验视频

Last Updated: May 24, 2025

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A TIRF Microscopy Technique for Real-time, Simultaneous Imaging of the TCR and its Associated Signaling Proteins
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科学领域:

  • 免疫学 免疫学 免疫学
  • 结构生物学 结构生物学
  • 计算生物学 计算生物学

背景情况:

  • 由于结构数据有限,特征T细胞受体 (TCR) 和-主要基因相容性复合体 (pMHC) 结合受到阻碍.
  • 测序的进步提供了丰富的TCR序列数据,使蛋白质结构建模成为一个有前途的方法.
  • 计算方法可以预测TCR-pMHC相互作用和3D复杂结构,但这个过程很复杂,需要专门的专业知识.

研究的目的:

  • 开发一种用于预测3D TCR-pMHC复合体的自动计算工具.
  • 简化工作流程从TCR序列数据到预测的复杂结构.
  • 为了促进对TCR-pMHC结合性质的分析,以深入了解适应性免疫.

主要方法:

  • 开发了一个基于Python的工具TRain (T细胞受体自动化免疫信息学).
  • 将测序数据自动转换为TCR氨基酸序列.
  • 集成现有的TCR建模管道和RosettaDock用于自动化的TCR-pMHC结构预测和分析.
  • 在对接之前,启用了模拟的TCR与pMHC晶体结构的非偏见配对.

主要成果:

  • 从序列数据中,TRain成功地简化了3D TCR-pMHC复合物的预测.
  • 该工具自动化了多个复杂的步骤,包括数据转换,模型提交和结构准备对接.
  • 一个案例研究表明了TRain的基本功能,并提供了一份手册以提供进一步指导.

结论:

  • 推出了一个开源工具TRain,简化了对3D TCR-pMHC复合体的预测.
  • 该工具利用已知的方法,从序列信息中提供预测结构.
  • 分析这些预测复合体,可以更深入地了解TCR结合和适应性免疫反应.