重新调整PDB的时间
Florian Flachsenberg1, Christiane Ehrt1, Torben Gutermuth1
1Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany.
Journal of chemical information and modeling
|December 18, 2023
概括
我们开发了JAMDA,一个用于药物设计中的分子对接的自动化工作流. 它在高质量的蛋白质结构上取得了61.8%的成功率,与AutoDock Vina.相比.
科学领域:
- 计算化学是一种计算化学.
- 结构生物学是结构生物学.
- 药物发现 药物发现
背景情况:
- 分子对接对于基于结构的药物设计 (SBDD) 是至关重要的.
- 当前的对接方法通常需要多种工具和手动干预.
- 自动化对接过程可以提高效率并减少偏差.
研究的目的:
- 介绍JAMDA (JACS分子对接分析) 预处理和对接工作流程.
- 评估JAMDA的业绩,并确定影响其成功的因素.
- 为了提供一个现实的估计自动化重制性能.
主要方法:
- 开发了一个完全自动化的预处理和对接工作流程 (JAMDA).
- 从蛋白质数据库 (PDB) 中对绑定站点进行了JAMDA评估.
- 应用客观结构质量过器来创建PDBScan22-HQ数据集.
主要成果:
- 在PDBScan22数据集中,30.1%的结构中,JAMDA在2年RMSD内获得了排名第一的位置.
- 对于质量过的PDBScan22-HQ数据集,成功率增加到61.8%.
- 在过的数据集上,JAMDA的性能与AutoDock Vina相当.
结论:
- JAMDA 工作流提供了一个易于使用,完全自动化的分子对接解决方案.
- 自动化预处理和质量过显著提高了对接成功率.
- JAMDA为基于结构的药物设计提供了可靠和高效的工具.
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