对利波卡林-2的配体的AI辅助设计
Jacopo Sgrignani1, Sara Buscarini1, Patrizia Locatelli1
1Institute for Research in Biomedicine (IRB), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.
Frontiers in immunology
|September 29, 2025
概括
人工智能设计了针对Lipocalin-2 (LCN2) 的新型微蛋白,这是神经炎症的关键因素. 主要候选物MiniP-2显示出高结合亲和力和治疗应用的潜力.
科学领域:
- 生物化学 生物化学
- 计算生物学 计算生物学
- 蛋白质工程是指蛋白质工程.
背景情况:
- 利波卡林-2 (LCN2) 是一种急性阶段蛋白质,与血脑屏障破坏和神经炎症有关.
- 在病理过程中LCN2的作用为诊断和治疗干预提供了机会.
研究的目的:
- 开发一种人工智能驱动的工作流程,用于针对LCN2的微蛋白的新设计.
- 为了识别和表征高亲和度LCN2结合剂,以潜在的治疗用途.
主要方法:
- 利用射频扩散用于支架生成和蛋白MPNN用于序列优化.
- 使用AlphaFold2和Prodigy进行10,000个设计候选人的in silico过.
- 通过生物层干涉测量 (BLI) 评估结合亲和力,并通过计算建模分析结构相互作用.
主要成果:
- 确定MiniP-2为主要的LCN2结合剂,其离合常数 (Kd) 为4.2nM.
- 结构分析揭示了关键相互作用,包括键和MiniP-2和LCN2之间的盐桥.
- 使用表面等离子体共振 (SPR) 证明了MiniP-2抑制LCN2与MMP-9结合的能力.
结论:
- 一个完全计算的工作流成功地在一个设计-构建-测试周期中生成了纳米分子LCN2结合剂.
- MiniP-2 是一个有前途的候选人,可以作为成像探头或LCN2信号对抗剂进一步开发.
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