通过基于深度学习的药物重新定位和分子对接分析,Vismodegib被确定为一种新的COX-2抑制剂
Muhammad Yasir1, Jinyoung Park1, Eun-Taek Han2
1Department of Pharmacology, Kangwon National University School of Medicine, Chuncheon24341, Republic of Korea.
深度学习模型有效地选药物的新用途. 一种抗癌药物vismodegib被确定为一种新型的环氧化酶-2 (COX-2) 抑制剂,其活性与现有的药物相当.
科学领域:
- 计算化学和药理学计算化学和药理学
- 人工智能在药物发现中的作用
背景情况:
- 人工智能 (AI) 和深度学习加速了药物开发.
- 药物重新利用为现有药物确定新的治疗用途.
- 循环氧化酶-2 (COX-2) 是抗炎药物的标.
研究的目的:
- 应用深度学习模型来选FDA批准的药物作为新型COX-2抑制剂.
- 通过实验方法验证预测化合物的COX-2抑制潜力.
主要方法:
- 利用在DUD-E数据上训练的图形卷积网络 (GraphConvMol) 来进行分子特征提取和预测.
- 使用训练有素的深度学习模型对FDA批准的药物进行了选.
- 进行了分子对接和基于细胞的测试,以确认COX-2抑制vismodegib.
主要成果:
- 深度学习模型成功预测了COX-2抑制潜力.
- 一种抗癌药物Vismodegib被确定为潜在的COX-2抑制剂.
- 实验验证证证实了vismodegib显著的COX-2抑制活性,相当于赛莱科西布和布洛芬.
结论:
- 深度学习模型提高了虚拟药物查效率.
- 维斯莫迪吉布显示出作为一种新型治疗剂的潜力,用于COX-2抑制.
- 这项研究强调了人工智能在发现新药物应用中的实用性.
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