目前的计算方法用于蛋白质-化合物复杂结构预测
Chao Yang1, Xianjin Xu2, Changcheng Xiang3
1Department of Chemistry, New York University, New York 10003, United States.
Current medicinal chemistry
|October 27, 2023
概括
计算方法加快了对蛋白相互作用 (PPI) 的研究,这对于开发特定和低毒性基药物至关重要. 本综述涵盖了最近的蛋白质对接技术和评估策略.
科学领域:
- 计算生物学是一种计算生物学.
- 药物发现 药物发现
- 结构生物信息学 结构生物信息学
背景情况:
- 介导的蛋白质与蛋白质相互作用 (PPI) 在生物过程中至关重要.
- 基于的药物为调节PPI提供高特异性和低毒性.
- 准确预测蛋白质-相互作用对于药物开发至关重要.
研究的目的:
- 审查最近开发的蛋白质对接的计算方法.
- 为对接性能提供基准测试数据集和评估指标.
- 讨论复杂预测的先进技术,如分子动力学和深度学习.
主要方法:
- 蛋白质接方法的分类:以模板为基础的,无模板的和混合的方法.
- 编制可用于绩效评估的可用基准测试集.
- 讨论分子动力学模拟和深度学习用于复杂的预测.
主要成果:
- 目前的蛋白质接策略的分类.
- 识别关键数据集和指标,以评估对接的准确性.
- 探索新兴的计算技术,以提高预测.
结论:
- 计算对接方法为研究蛋白质-相互作用的实验方法提供了具有成本效益的替代方案.
- 标准化的基准测试和评估对于评估和改进对接工具至关重要.
- 分子动力学和深度学习的整合有望实现更准确的蛋白质-化合物复合体预测.
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