基于自然人工智能的药物设计,通过修改甲酸和黄素,通过使用分子动力学研究来对抗布普罗菲津毒性
Haleema Sadia1, Irfan Zia Qureshi2, Muhammad Naveed3
1Laboratory of Animal and Human Physiology, Department of Zoology, Quaid-i-Azam University, Islamabad, 45320, Pakistan.
Scientific reports
|November 18, 2024
概括
这项研究探讨了人工智能设计的药物,以抵消布普罗菲津.
科学领域:
- 环境毒理学环境毒理学
- 计算化学是一种计算化学.
- 药物发现 药物发现
背景情况:
- 昆虫杀虫剂布普罗菲津对非目标生物和生态系统构成风险.
- 由于环境持久性,研究更安全的替代品至关重要.
- 关键受体 (CAT,IL-1B,IL-6,TNF-alpha,SOD) 对于理解毒性影响至关重要.
研究的目的:
- 为了确定人工智能驱动的制药替代品,以减轻布普罗菲津的不良影响.
- 评估新型化合物的结合亲和力和类似药物的特性.
- 评估针对氧化应激和炎症的潜在治疗干预措施.
主要方法:
- 通过人工智能 (WADDAICA) 使用Web服务器辅助药物设计.
- 进行了吸收,分布,新陈代谢,分泌 (ADME) 分析.
- 进行了分子动力学 (MD) 模拟和MMGBSA/MMPBSA计算.
- 进行了分子对接实验.
主要成果:
- 人工智能衍生的甲酸药物显示强烈的结合 (-7.1 kcal/mol) 与catalase (CAT).
- 人工智能衍生库尔库明药物表现出强烈的相互作用 (-7.3 kcal/mol) 与互白素-1β (IL-1B).
- 这两种化合物都表现出有利的ADME概况和药物相似性,坚持Lipinski的五.规则.
结论:
- 人工智能驱动的药物设计为布普罗菲津毒性减轻提供了有希望的替代方案.
- 已识别的化合物具有作为治疗剂的潜力.
- 为了开发和应用,需要进一步的研究.
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