Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Antibody Structure01:10

Antibody Structure

61.2K
Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
61.2K
Antibody Structure and Classes01:25

Antibody Structure and Classes

4.1K
Antibodies, also known as immunoglobulins, are produced by B cells in response to foreign substances, such as bacteria and viruses. These proteins are critical for recognizing and neutralizing these substances, protecting the body from potential harm.
The basic structure of an antibody consists of four protein chains: two identical heavy chains and two identical light chains. These chains are held together by disulfide bonds and other non-covalent interactions, forming a Y-shaped structure.
4.1K
Antibody Actions01:26

Antibody Actions

1.3K
Antibodies, or immunoglobulins, are critical players in the immune system's arsenal against invading pathogens. Produced by B cells and plasma cells, their primary role is to detect and bind to specific antigens, molecules found on the surface of pathogens like bacteria or viruses. Beyond antigen recognition, antibodies perform several vital functions that contribute to immune defense.
Neutralization
Antibodies can bind to pathogens, preventing them from infecting host cells. This process...
1.3K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

ProphDR: An Interpretable Deep Learning Model for Predicting Cancer Drug Response via Multi-Omics and Cross-Attention Mechanisms.

Journal of chemical information and modeling·2026
Same author

Age-dependent prognostic value of biological age for metastasis and survival in gastrointestinal cancer.

Scientific reports·2026
Same author

Generative AI for controllable protein sequence design: A survey.

npj drug discovery·2026
Same author

Unified heterogeneity-aware benchmark of drug synergy prediction: a cross-study analysis of traditional machine learning and graph deep learning models.

Journal of cheminformatics·2026
Same author

Association of liver enzyme abnormalities and tobacco exposure with unexplained recurrent spontaneous abortion risk: A case-control study.

The Journal of international medical research·2026
Same author

Target Perturbation of Genetically Proxied Antidiabetic Drug Targets and Pneumonia Risk: A Mendelian Randomization Analysis.

Current topics in medicinal chemistry·2026

相关实验视频

Updated: Sep 10, 2025

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
08:51

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Published on: March 15, 2019

12.5K

S2ALM:序列结构预训练的大型语言模型用于全面的抗体表示学习

Mingze Yin1,2, Hanjing Zhou3, Jialu Wu4

  • 1College of Computer Science and Technology, Zhejiang University, Hangzhou, China.

Research (Washington, D.C.)
|August 21, 2025
PubMed
概括

新的序列结构多级预训练抗体语言模型 (S2ALM) 整合了抗体序列和结构,以改善治疗开发. 这种先进的模型提高了对各种疾病的抗体的理解和设计.

更多相关视频

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
08:09

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Published on: March 24, 2017

9.6K
Immunization of Alpacas Lama pacos with Protein Antigens and Production of Antigen-specific Single Domain Antibodies
05:27

Immunization of Alpacas Lama pacos with Protein Antigens and Production of Antigen-specific Single Domain Antibodies

Published on: January 26, 2019

23.8K

相关实验视频

Last Updated: Sep 10, 2025

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
08:51

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Published on: March 15, 2019

12.5K
Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
08:09

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Published on: March 24, 2017

9.6K
Immunization of Alpacas Lama pacos with Protein Antigens and Production of Antigen-specific Single Domain Antibodies
05:27

Immunization of Alpacas Lama pacos with Protein Antigens and Production of Antigen-specific Single Domain Antibodies

Published on: January 26, 2019

23.8K

科学领域:

  • 生物技术
  • 计算生物学
  • 免疫学

背景情况:

  • 抗体对于健康和疾病治疗至关重要, 生物医学语言模型显示出希望.
  • 目前的模型缺乏对抗体结构信息的明确考虑,限制了它们的预测能力.
  • 一维序列和三维结构都为抗体功能提供了补充的见解.

研究的目的:

  • 提出一个统一的抗体语言模型,即S2ALM,它既集成了序列信息,也集成了结构信息.
  • 开发一个层次化的预训练范式,以定制针对综合抗体表示的目标.
  • 证明S2ALM在各种下游任务中的实用性,包括结合亲和预测和治疗抗体设计.

主要方法:

  • 开发了序列结构多级预训练抗体语言模型 (S2ALM).
  • 采用分层的预培训模式,有两个定制的多级培训目标.
  • 在7500万个序列和1170万个结构的大数据集上进行了预训练.

主要成果:

  • S2ALM的表示空间揭示了功能结合机制,进化性质和结构相互作用模式.
  • 在预测抗原-抗体结合亲缘关系和B细胞成熟阶段方面取得了最先进的性能.
  • 在识别关键抗体结合部位和设计新型冠状病毒结合抗体方面取得了成功.

结论:

  • 通过整合序列和结构,S2ALM有效地建模了综合和通用的抗体表征.
  • 该模型显示了促进治疗抗体开发和解决未满足需求的巨大潜力.
  • 在各种抗体理解和生成任务中,S2ALM的表现优于现有的基线.