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抗体碎片的亲和度成熟:一个综述,涵盖从随机方法到计算理性优化计算的发展
Jiaqi Li1, Guangbo Kang1, Jiewen Wang1
1School of Chemical Engineering and Technology, Tianjin University, Tianjin 300350, China; Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin 300072, China.
International journal of biological macromolecules
|July 9, 2023
概括
优化抗体碎片,特别是纳米体,对生物物理性质至关重要. 本综述探讨了生物信息学工具和深度学习方法,以理性地提高抗体片段的亲和力和稳定性.
科学领域:
- 生物技术是生物技术.
- 结构生物学 结构生物学
- 生物信息学是一种生物信息学.
背景情况:
- 抗体碎片通常需要在体外成熟以获得最佳的生物物理特性,如亲和力和稳定性.
- 目前的优化方法包括盲目的体外策略,随机突变和专注于特定残留物的理性方法.
研究的目的:
- 审查生物信息仪器,以优化抗体碎片,特别是纳米体.
- 分析这些工具在改善抗体碎片特征方面的应用.
- 总结抗体碎片优化的新兴趋势和挑战.
主要方法:
- 探索合理设计策略,以特定残留物为目标,以改善生物物理性质.
- 利用深度学习方法来提高抗体建模和对接的速度和准确性.
- 对生物信息学工具用于抗体碎片优化的应用现有文献的分析.
主要成果:
- 生物信息工具和深度学习显著加快了抗体碎片优化.
- 以结构数据为基础的合理设计是提高抗体亲和力和稳定性的关键.
- 深度学习方法在改进模型构建和对接步骤方面表现有前途.
结论:
- 生物信息仪器对于合理的抗体碎片优化至关重要.
- 深度学习的进步正在彻底改变抗体设计的速度和准确性.
- 需要进一步的研究来解决该领域的新兴趋势和未解决的问题.
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