从天然产品中识别抗炎药物分子的方法,策略和程序
Tenzin Jamtsho1,2, Karma Yeshi1,2, Matthew J Perry1,2
1College of Public Health, Medical, and Veterinary Sciences (CPHMVS), Cairns Campus, James Cook University, Cairns, QLD 4878, Australia.
Pharmaceuticals (Basel, Switzerland)
|March 28, 2024
概括
自然产品为治疗疾病提供潜在的抗炎化合物. 本综述详细介绍了使用先进技术和模型发现这些小分子的策略.
科学领域:
- 药理学和天然产品化学
- 药物发现和开发 药物发现和开发
背景情况:
- 自然产品 (NPs) 在传统医学中有着悠久的历史,用于治疗炎症疾病.
- 现代医学试图从NP中分离生物活性化合物,以开发新型抗炎药物,解决炎症性肠病等疾病的未满足需求.
研究的目的:
- 从自然产品中全面审查识别,提取,分成和分离小分子抗炎药物的策略.
- 在NP药物发现中讨论当前和新兴技术,包括人工智能 (AI),机器学习和计算方法.
- 概述使用动物模型和细胞系的体外和体内评估方法,以评估NP的抗炎潜力.
主要方法:
- 文献综述侧重于小分子抗炎药物从天然产品中获得的线索.
- 对化合物隔离和净化的既定和新技术的分析.
- 检查药物发现中的计算和人工智能驱动方法.
- 编制相关的体外和体外模型,用于抗炎性评估.
主要成果:
- 确定从NP中发现抗炎小分子的关键策略和技术.
- 强调人工智能,机器学习和计算方法在现代药物发现管道中的整合.
- 总结各种动物模型和细胞系用于验证抗炎活性的实用性.
结论:
- 自然产品仍然是发现新型抗炎药物的丰富来源.
- 像人工智能和机器学习这样的先进技术对于加速这些化合物的识别和开发至关重要.
- 强大的体外和体内模型对于验证NP衍生的抗炎药物的治疗潜力至关重要.
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