破解硫密码:大生物活性分子作为药物发现的多目标蓝图
Faizul Azam1, Md Jamir Anwar2, Jordan Kahfi3
1Department of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, Qassim University, Buraydah 51452, Saudi Arabia.
Pharmaceuticals (Basel, Switzerland)
|November 27, 2025
概括
大 大 大 大 大 大
科学领域:
- 草药和药理学 在草药和药理学.
- 自然产品化学 自然产品化学
- 计算化学和药物发现
背景情况:
- 大 (Allium sativum L.) 具有作为食物和药物使用的悠久历史.
- 它的生物活性化合物,如素和有机硫衍生物,表现出不同的药理作用.
- 这些作用包括抗氧化,抗炎,抗血栓,抗癌,抗微生物和神经保护性质.
研究的目的:
- 探索大治疗功能的机械基础.
- 研究计算方法在了解大生物活性化合物的作用.
- 评估配方策略,以增强大衍生物制药.
主要方法:
- 机理学研究对氧化还原稳定,炎症,血小板激活和亡.
- 计算方法包括密度函数理论 (DFT),分子对接,分子动力学和MM-GBSA.
- 在 silico ADME / Tox 预测和人工智能 / 机器学习 (AI / ML) 管道.
- 配方策略,如纳米封装和控制释放系统.
主要成果:
- 大化合物调节与各种疾病相关的关键生物通路.
- 计算研究为抗氧化剂和药理学活动提供了分子层面的洞察力.
- 在 silico 模型预测一些化合物具有有利的药物动力学特征,极性衍生物在脑透方面受到限制.
- 人工智能/ML有助于目标识别和药物开发优先级.
- 配方方法可以稳定活性化合物并控制它们的释放.
结论:
- 整合机械,计算和配方数据为开发衍生物剂提供了一个系统的途径.
- 计算和配方策略对于将天然产品推进到可复制药品中至关重要.
- 应对标准化和药物动力学变异性方面的挑战是临床翻译的关键.
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