AutoDock-SS:用于多元信息化的基于基的虚拟选的AutoDock.
Boyang Ni1, Haoying Wang1, Huda Kadhim Salem Khalaf1
1Institute for Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh EH9 3BF, U.K.
Journal of chemical information and modeling
|April 16, 2024
概括
AutoDock-SS通过调整对接以用于基于联体的虚拟选 (LBVS) 来增强药物领先发现. 这种方法准确地考虑了连接体的灵活性,优于现有的3D LBVS方法.
科学领域:
- 计算化学是一种计算化学.
- 药物发现 药物发现
- 化学信息学 化学信息学
背景情况:
- 基于连接体的虚拟查 (LBVS) 对于在蛋白质结构不可用时识别药物线索至关重要.
- 现有的LBVS方法往往无法充分考虑连接体的结构灵活性,从而限制了它们的有效性.
研究的目的:
- 介绍AutoDock-SS (相似性搜索),一个新的3D LBVS工作流程,集成基于联体的网格地图和AutoDock-GPU.
- 通过结合动态形态搜索来解决当前LBVS方法的局限性.
主要方法:
- 开发了AutoDock-SS,这是一个适用于LBVS的蛋白质-连接体对接的工作流.
- 集成了基于联体的新型网格地图和AutoDock-GPU.
- 实现了内置的构造性搜索,用于对连接体构造的动态优化.
- 支持单个和多个连接体查询模式.
主要成果:
- 在单一参考模式下,AutoDock-SS在DUD-E数据集上实现了0.775的平均AUROC和25.72的EF1%的平均EF1%.
- 在DUD-E+的多引用模式下,AutoDock-SS表现出卓越的准确性,平均AUROC为0.843和EF1%的34.59.
- 在两种测试模式中,超越了替代的3D LBVS方法.
结论:
- AutoDock-SS 通过将连接体作为形状灵活的处理,显著增强了 LBVS.
- 该方法准确考虑了连接体形状,药和静电电位.
- AutoDock-SS扩展了LBVS在药物发现中的功能和潜在应用.
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