综合性表位突变扫描数据库能够准确地预测T细胞受体交叉活性
Amitava Banerjee1, David J Pattinson2, Cornelia L Wincek1,3
1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
bioRxiv : the preprint server for biology
|February 19, 2024
概括
预测T细胞受体 (TCR) 激活是具有挑战性的. 我们开发了BATMAN,一个可解释的贝叶斯模型和数据库 (BATCAVE),以准确预测TCR-相互作用,并指导基于TCR的疗法.
科学领域:
- 免疫学 免疫学 免疫学
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 由于有限的数据集和对小突变不敏感的计算方法,难以预测T细胞受体 (TCR) 激活.
- 准确的预测对于理解免疫反应和开发基于TCR的疗法至关重要.
研究的目的:
- 创建一个全面的数据集,用于对比TCR激活预测.
- 开发一种新的,可解释的计算模型,用于预测TCR-相互作用.
- 为了能够有效地学习新型TCR的TCR绑定配置文件.
主要方法:
- 精选的BATCAVE数据库:来自25个表位和151个TCR的22,000个TCR-对.
- 开发了BATMAN:一种可解释的贝叶斯模型,用于预测TCRs的激活.
- 实施积极学习,以实现高效的新型TCR个人资料学习.
主要成果:
- 蝙蝠侠在预测TCR-相互作用方面优于现有的方法.
- 确定了TCR-结合的关键生化预测因素.
- 证明了BATMAN在预测非目标效应和多克隆T细胞反应方面的实用性.
结论:
- 蝙蝠侠为预测TCR激活提供了一个强大的和可解释的框架.
- BATCAVE数据库和BATMAN模型推进了TCR-相互作用研究.
- 应用包括增强基于TCR的疗法和理解免疫反应.
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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.
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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...
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