人工智能在小型核酸治疗药物的开发中:朝着更智能,更安全的药物发展
Pietro Delre1, Carmen Cerchia1, Antonio Lavecchia1
1Drug Discovery Laboratory, Department of Pharmacy, University of Naples Federico II, I-80131 Naples, Italy.
Drug discovery today
|October 12, 2025
概括
小型核酸疗法,如反感性寡核酸 (ASOs) 和siRNAs提供了新的治疗途径,但面临着稳定性挑战. 本综述比较了优化这些寡核酸药物的AI方法,解决了临床使用的关键局限性.
科学领域:
- 生物技术是生物技术.
- 分子生物学分子生物学
- 药物发现 药物发现 药物发现
背景情况:
- 小型核酸治疗药物,包括反感性寡核酸 (ASO),siRNA,miRNA和aptamer,是有前途的药物类别.
- 它们通过补充序列识别来调节基因表达而起作用,为遗传性,传染性和退行性疾病提供新的治疗策略.
- 然而,由于稳定性和药理动力学的问题,它们的临床应用受到阻碍.
研究的目的:
- 审查小核酸药物的主要类别及其作用机制.
- 讨论改善这些治疗药物的药理性质的化学修改.
- 批判性地比较基于人工智能 (AI) 的方法来设计和优化寡核酸治疗方法.
主要方法:
- 关于小核酸治疗的现有文献的综述.
- 分析化学修饰策略以增强药物特性.
- 对应用于寡核酸药物设计的各种AI方法的比较评估.
主要成果:
- 小型核酸药物为以前无法获得的途径提供有针对性的基因调制.
- 化学修饰可以显著改善稳定性和药理动力学特征.
- 人工智能方法显示出潜力,但面临诸如数据稀缺和准确的目标外预测等挑战.
结论:
- 小核酸疗法具有显著的前景,但需要进一步优化临床转化.
- 人工智能工具对于加速这些先进疗法的设计和开发至关重要.
- 解决人工智能模型的局限性对于克服临床翻译障碍至关重要.
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