药物发现的微RNA小分子中介向:实验,计算技术和疾病影响
Jianfeng Sun1, Miaoer Xu2, Jinlong Ru3
1Botnar Research Centre, Nuffield Department of Orthopedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, OX3 7LD, UK.
European journal of medicinal chemistry
|June 1, 2023
概括
针对微RNA (miRNA) 的小分子抑制剂为疾病提供治疗潜力. 本综述整合了计算和实验方法,用于发现这些关键的miRNA向药物.
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.
- 生物信息学是一种生物信息学.
背景情况:
- 小分子在历史上推动了医学突破.
- 微RNA (miRNA) 向的小分子抑制剂正在成为一种重要的治疗策略.
- 挑战包括繁的查和药物化学优化.
研究的目的:
- 在miRNA向药物发现中提供生物学和计算方法的全面概述.
- 突出这种治疗方式的疾病影响和临床意义.
- 证明深度学习在表征药物向相互作用方面的有用性.
主要方法:
- 对现有关于实验和计算miRNA药物发现的文献的综述.
- 药物基因组学数据和基于序列的计算方法的整合.
- 应用深度学习模型来分析来自DrugBank的药物向相互作用 (DTI) 数据.
主要成果:
- 实验证据支持miRNA抑制剂在疾病治疗中的潜力.
- 通过算法增强的计算策略,有助于合理的药物设计.
- 深度学习有效地描述了DTI的物理化学特性.
结论:
- 结合计算和实验方法,加速了针对miRNA的药物发现.
- 针对miRNA的治疗方法对治疗各种疾病具有前景.
- 像深度学习这样的先进计算技术对于优化药物开发至关重要.
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