生物信息学方法的进步加速了从大自然中发现药物的速度
Magdalena Maciejewska-Turska1, Milen I Georgiev2, Guoyin Kai3
1Department of Pharmacognosy with Medicinal Plants Garden, Medical University of Lublin, 20-093 Lublin, Poland.
概括
生物信息学通过分析复杂的数据来加速从自然来源发现药物. 这些计算工具可以识别治疗化合物及其机制,使人们重新对草药产生兴趣.
科学领域:
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
- 药物发现 药物发现 药物发现
背景情况:
- 自然资源对于识别药物线索和活性分子至关重要.
- 民族医学为从自然中发现现代药物的发现提供了基础.
- 生物信息学和计算生物学方面的进步凸显了草药的作用.
研究的目的:
- 审查最近从自然来源发现药物中使用的生物信息方法.
- 检查系统生物学和人工智能在天然产品药物发现中的应用.
主要方法:
- 在PubMed,SciFinder和谷歌数据库中进行文献搜索.
- 分析分子网络,途径分析和网络药理学方面的进展.
- 整合人工智能来评估治疗潜力.
主要成果:
- 生物信息学对于药物发现中的高通量数据分析至关重要.
- 计算工具有助于目标识别,机制阐明和副作用预测.
- 欧米克斯数据分析揭示了疾病相关条件的相互作用和模式.
结论:
- 生物信息学有助于表征草药制剂和选择生物活性化合物.
- 这些方法揭示了自然化合物的多目标效应和分子机制.
- 整合网络使天然来源的药物发现有了新的活力.
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