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相关概念视频

Antibody Structure01:10

Antibody Structure

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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...
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相关实验视频

Updated: May 1, 2026

Scalable High Throughput Selection From Phage-displayed Synthetic Antibody Libraries
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基于AI的IsAb2.0用于抗体设计.

Tianjian Liang1,2,3,4,5, Ze-Yu Sun1,2,3,4,5, Margaret G Hines6

  • 1Department of Pharmaceutical Sciences, Computational Chemical Genomics Screening Center, Pharmacometrics & System Pharmacology PharmacoAnalytics, School of Pharmacy, University of Pittsburgh, 335 Sutherland Drive, Pittsburgh, PA 15261, United States.

Briefings in bioinformatics
|September 16, 2024
PubMed
概括

我们开发了IsAb2.0,这是一种人工智能驱动的计算工具,用于设计治疗性抗体,包括纳米体和人性化抗体. 这种改进的协议增强了结合亲和力,加速了免疫治疗的发展.

关键词:
阿尔法折叠-多元化艾滋病毒-1纳米体这就是IsAbAbAb.抗体设计 抗体设计深度学习是一种深度学习.人性化的抗体.

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科学领域:

  • 生物技术和生物信息学
  • 免疫学 免疫学 免疫学
  • 计算生物学 计算生物学

背景情况:

  • 治疗性抗体设计至关重要,但面临着昂贵的实验方法带来的挑战.
  • 像IsAb1.0这样的现有计算工具在准确性,复杂性和范围上有局限性,特别是对于纳米体和人性化抗体.
  • 缺乏足够的结构数据和缺乏标准化的协议阻碍了有效的抗体工程.

研究的目的:

  • 开发一个先进的计算协议,IsAb2.0,用于准确高效的in silico抗体设计.
  • 通过整合人工智能和先进的建模技术,克服以前方法的局限性.
  • 特别是为了使纳米体和人性化抗体的设计能够用于治疗应用.

主要方法:

  • IsAb2.0将人工智能与AlphaFold-Multimer (2.3/3.0版本) 集成在一起,用于无模板建模和复杂构建.
  • 采用FlexddG方法用于精确的in silico抗体优化.
  • 该协议使用人性化纳米体 (HuJ3) 进行验证,该纳米体针对HIV-1 gp120.

主要成果:

  • IsAb2.0准确地预测了五种突变,以增强人性化纳米体HuJ3与HIV-1 gp120的结合亲和力.
  • 这些预测得到商业软件的证实,并通过结合和中和试验进行实验验证.
  • 该研究表明,IsAb2.0能够简化抗体设计并提高结合亲和力.

结论:

  • IsAb2.0代表了计算抗体设计的重大进步,提供了更高的准确性和效率.
  • 由人工智能驱动的协议有助于开发治疗性抗体,包括纳米体和人性化抗体.
  • 通过简化设计流程,IsAb2.0为加速未来免疫疗法开发提供了基础.