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下一代抗病毒:人工智能驱动的设计,翻译传递平台和未来的治疗方向

Maryam Mashhadi Abolghasem Shirazi¹, Setareh Haghighat¹, Zahra Nikbakht¹

¹Department of Microbiology, TeMS.C., Islamic Azad University, Tehran, Iran.

|October 17, 2025

概括

抗病毒 (AVP) 由于其有效性和低毒性,显示出作为新疗法的前景. 本综述强调了人工智能 (AI) 在发现AVP和临床使用的创新交付方法方面.

科学领域:

生物化学和分子生物学
药理学药理学是指药理学的学科.
计算生物学计算生物学

背景情况:

抗病毒 (AVP) 是具有广泛活性,低毒性和克服药物耐药性的强效治疗剂.
在传染病治疗方面,AVP是下一代治疗药物中的一个有希望的类别.

研究的目的:

为抗病毒 (AVP) 研究提供综合的视角.
强调人工智能 (AI) 驱动的发现,新的交付策略和AVP的翻译应用.

主要方法:

总结AVP的起源,机制和结构多样性.
突出计算管道 (机器学习,深度学习,GAN,LLM,强化学习) 用于 de novo 设计.
讨论新的输送系统 (纳米粒子,水凝,鼻内/吸入配方) 和临床试验示例.

主要成果:

介绍了人工智能驱动的新设计的最新进展.
讨论了AVP的新型传递系统和成功的临床试验例子.
探索未来的方向,包括基于CRISPR和mRNA的传递和组合疗法.

结论:

人工智能驱动的设计和创新的交付平台增强了AVP的潜力.
AVP是多功能抗病毒药物,具有显著的临床转化潜力.
本综述巩固了AVP研究的当前知识和未来前景.

关键词:

抗病毒类的抗病毒.人工智能的人工智能是人工智能.药物耐药性药物耐药性药物耐药性生成性的对抗性网络.大型语言模型.机器学习是机器学习.

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