缓解小RNA的脱效应:传统方法,网络理论和人工智能
Zoltán Bereczki1,2,3, Bettina Benczik1,2,3,4, Olivér M Balogh1,2,3
1Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
British journal of pharmacology
|September 18, 2024
概括
像siRNAs和miRNAs这样的小RNA疗法提供了优势,但可能会导致目标外的影响. 本综述讨论了减少这些影响的方法,包括计算方法和人工智能,以实现更安全的药物开发.
科学领域:
- 生物技术是生物技术.
- 药理学 药理学是指药理学的学科.
- 遗传学 是一个遗传学.
背景情况:
- 小RNA疗法,包括小干扰RNAs (siRNAs),microRNAs (miRNAs) 和反感 oligonucleotides (ASOs),为小分子药物提供了有希望的替代品.
- 这些基于RNA的疗法可以针对任何基因产物,为各种疾病提供新的治疗策略.
- 在临床前研究中,合成小RNA对于基因沉默至关重要,有助于药物标的发现和验证.
研究的目的:
- 审查和讨论减少小型RNA疗法的杂交依赖非目标效应的策略.
- 强调在药物开发过程的早期解决这些非目标效应的重要性.
- 提供当前计算方法的概述,并提出预测和减轻这些影响的新方法.
主要方法:
- 对小RNA脱效应和缓解策略的现有文献的审查.
- 分析用于预测杂交依赖非目标效应的计算方法.
- 探索新的预测方法,包括网络理论和人工智能 (AI).
- 对验证in silico预测的实验方法的调查.
主要成果:
- 杂交依赖的非目标效应,特别是像miRNA这样的效应,在小RNA疗法开发中构成挑战.
- 目前用于预测这些非目标效应的方法缺乏标准化.
- 序列设计,化学修改和先进的计算工具 (人工智能,网络理论) 显示出减少目标外效应的潜力.
结论:
- 尽量减少依赖杂交的非目标效应对于成功开发安全有效的小RNA疗法至关重要.
- 将包括人工智能和网络理论在内的先进计算方法集成到预测工作流中可以提高准确性.
- 对in silico预测的实验验证对于解释结果和避免不良事件至关重要.
关键词:
生物信息学是一种生物信息学.网络 ceRNA 网络化学修饰 化学修饰 化学修饰功能分析是一种功能分析.机器学习是机器学习.神经网络的神经网络的神经网络转录后的法规 转录后的法规风险最小化 降低风险最小化目标识别 目标识别更多相关视频
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