SAAINT-DB:用于抗体建模和设计的全面结构性抗体数据库
Xiaoqiang Huang1, Jun Zhou2, Shuang Chen2
1Center for Advanced Models for Translational Sciences and Therapeutics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA. xiaoqiah@umich.edu.
Acta pharmacologica Sinica
|June 30, 2025
概括
SAAINT-parser精确地从PDB数据中提取抗体结构和相互作用. 这个新的计算工具和数据库 (SAAINT-DB) 改进了像SAbDab这样的现有资源,用于抗体研究.
科学领域:
- 结构生物学 结构生物学
- 免疫学 免疫学 免疫学
- 生物信息学是一种生物信息学.
背景情况:
- 抗体 (Ab) 结构和抗体-抗原相互作用 (AAI) 对免疫识别和治疗开发至关重要.
- 现有的结构性 Ab 数据库在数据准确性,完整性和更新频率方面存在局限性.
研究的目的:
- 开发一个计算工作流程 (SAAINT-parser) 来从蛋白质数据库 (PDB) 快速,准确和可靠地提取Ab和AAI信息.
- 为抗体结构信息创建一个更新和全面的数据库 (SAAINT-DB).
主要方法:
- 实施SAAINT-parser,用于精确检测和配对Ab链.
- 在PDB结构中可靠地识别抗体-抗原相互作用 (AAI).
- 创建SAAINT-DB,来自9757个PDB结构的19128条条目,最后更新时间为2025年5月1日.
主要成果:
- 与SAbDab相比,SAAINT-DB显示出更高的数据准确性和完整性.
- 与SAbDab相比,SAAINT-DB提供了近两倍的非冗余,手动策划的Ab-Ag结合亲和度条目.
- 该SAAINT-解析器工作流确保精确的Ab链检测,准确的配对和可靠的AAI识别.
结论:
- SAAINT-parser和SAAINT-DB为抗体研究提供了一个有价值的,最新的资源.
- 开发的工具提高了结构性抗体数据的准确性和完整性.
- 对SAAINT-parser,SAAINT-DB和处理模型的开放访问有助于更广泛的科学进步.
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