用人工智能驱动的框架来设计和开发下一代鸟类病毒疫苗
Muddapuram Deeksha Goud1, Elisa Ramos1, Abid Ullah Shah1
1Department of Veterinary Biomedical Sciences, College of Veterinary Medicine, Long Island University, Brookville, NY 11548, USA.
Microorganisms
|October 29, 2025
概括
人工智能通过设计针对H5N1等禽类病毒的多表位疫苗来加速禽类疫苗的开发. 这个人工智能管道提供了一个可扩展的,数据驱动的方法,用于快速创建疫苗,提高全球家禽健康.
科学领域:
- 兽医医学 兽医医学 兽医医学
- 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:
- 禽类病毒病原体对家禽健康和粮食安全构成重大威胁.
- 传统的疫苗开发方法通常是缓慢的,昂贵的,并与病原体多样性作斗争.
研究的目的:
- 开发人工智能 (AI) 驱动的管道,用于设计,建模和优化针对关键禽类病毒的多表位疫苗.
- 展示AI在加速兽医疫苗学方面的潜力.
主要方法:
- 利用机器学习和深度学习进行表位预测,抗原性评估和结构建模 (AlphaFold2).
- 根据结合亲缘关系,保存和免疫性,选择B细胞和T细胞表位.
- 纳入辅助剂和链接剂,以增强结构稳定性和免疫反应;在体免疫模拟中进行.
主要成果:
- 人工智能管道成功设计了针对鸟类RNA和DNA病毒 (H5N1,NDV,IBV,IBDV,CAV,FPV) 的多表位疫苗.
- 在模拟预测了强烈的幽默和细胞免疫反应,包括细胞因子的产生和记忆细胞的激活.
- 确定了包括数据质量,模型解释性和道德考虑在内的挑战.
结论:
- 人工智能为兽医疫苗学中快速,数据驱动的疫苗开发提供了一种变革性和可扩展的方法.
- 这种人工智能驱动的管道可以显著改善对新出现的鸟类疾病的反应,并增强全球家禽健康.
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