对抗SARS-CoV-2的药物设计中的对接和其他计算工具
A V Sulimov1,2, I S Ilin2, A S Tashchilova1,2
1Dimonta Ltd., Moscow, Russia.
SAR and QSAR in environmental research
|February 14, 2024
概括
计算机模拟对于发现SARS-CoV-2抗病毒药物至关重要. 本综述涵盖了用于识别和实验验证病毒潜在抑制剂的对接和分子动力学等计算方法.
科学领域:
- 计算化学和药理学计算化学和药理学
- 药物的发现和开发.
- 病毒学和传染病学.
背景情况:
- 计算机模拟对于识别针对SARS-CoV-2的药物至关重要.
- 有大量关于分子建模的文献,用于预测针对SARS-CoV-2标蛋白的抑制剂.
- 本综述侧重于使用计算方法寻找抑制剂并实验性测试它们的研究.
研究的目的:
- 审查用于识别SARS-CoV-2抑制剂的计算方法.
- 要突出结合计算预测与实验验证的研究.
- 提供模拟技术和相关化合物数据库的概述.
主要方法:
- 对SARS-CoV-2的计算药物发现研究的文献综述.
- 分析各种分子建模技术:对接,分子动力学,量子力学,机器学习.
- 包括经过实验验证的研究 (蛋白质试验,细胞培养) 和显著的计算工作.
主要成果:
- 对接是最常见的计算方法,通常由其他模拟进行改进.
- 用各种分子建模方法来预测潜在的抗病毒化合物.
- 还讨论了用于有机化合物的虚拟选的数据库.
结论:
- 计算方法,特别是对接,在寻找SARS-CoV-2抑制剂的过程中至关重要.
- 将计算预测与实验验证相结合,可以加速药物发现.
- 该综述提供了针对抗病毒药物开发的当前计算策略和资源的结构化概述.
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