一个基于相互作用的药物发现屏幕解释了已知的SARS-CoV-2抑制剂,并预测了新的化合物支架
Philipp Schake1, Klevia Dishnica2, Florian Kaiser3
1Bioinformatics, Biotechnology Center (BIOTEC), Technische Universität Dresden, Dresden, Saxony, Germany. philipp.schake@tu-dresden.de.
Scientific reports
|June 6, 2023
概括
这项研究使用了计算方法来识别SARS-CoV-2的潜在抑制剂.
科学领域:
- 计算机化药物发现.
- 病毒学 病毒学
- 药品化学 药品化学 是一个
背景情况:
- 随着COVID-19的爆发,人们越来越需要快速发现抗新型传染病的药物.
- 严重急性呼吸系统综合征-冠状病毒-2 (SARS-CoV-2) 主蛋白酶 (Mpro) 对于病毒复制至关重要,也是关键药物标.
研究的目的:
- 用基于相互作用的药物重新定位算法识别针对SARS-CoV-2的新型抑制剂和化学支架.
- 用现有的公共数据验证计算预测,并分析绑定模式.
主要方法:
- 将基于相互作用的药物重新定位算法应用于蛋白质数据库 (PDB) 中的蛋白质化合物复合体.
- 选潜在的Mpro抑制剂,包括已知的药物和新型支架.
- 使用公开可用的数据,在选后两年发布的验证的顶级预测.
主要成果:
- 确定了692种潜在的Mpro抑制剂,包括已知的化合物如达沙替尼和阿莫迪亚奎因,以及新的支架.
- 使用外部数据验证了前100个预测中的17%.
- 发现了以前与Mpro抑制无关的新型化学支架.
- 确定了一种关键的结合模式,涉及Mpro的活性位点氧化离子孔中的3个键.
结论:
- 这项研究证明了计算药物重新定位用于识别SARS-CoV-2 Mpro抑制剂的有效性.
- 研究结果为开发更有效的药物发现策略提供了基础,以应对未来的流行病.
- 鉴定的化合物和结合模式为抗病毒药物开发提供了新的途径.
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