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首页> 外文期刊>Journal of Biomolecular Structure and Dynamics >A novel and efficient ligand-based virtual screening approach using the HWZ scoring function and an enhanced shape-density model
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A novel and efficient ligand-based virtual screening approach using the HWZ scoring function and an enhanced shape-density model

机译:一种新颖且有效的基于配体的虚拟筛选方法,使用HWZ评分函数和增强形状密度模型

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摘要

In this work, we extend our previous ligand shape-based virtual screening approach by using the scoring function Hamza-Wei-Zhan (HWZ) score and an enhanced molecular shape-density model for the ligands. The performance of the method has been tested against the 40 targets in the Database of Useful Decoys and compared with the performance of our previous HWZ score method. The virtual screening results using the novel ligand shape-based approach demonstrated a favorable improvement (area under the receiver operator characteristics curve AUC =.89 ±.02) and effectiveness (hit rate HR1% = 53.0% ± 6.3 and HR10% = 71.1% ± 4.9). The comparison of the overall performance of our ligand shape-based method with the highest ligand shape-based virtual screening approach using the data fusion of multi queries showed that our strategy takes into account deeper the chemical information of the set of active ligands. Furthermore, the results indicated that our method are suitable for virtual screening and yields superior prediction accuracy than the other study derived from the data fusion using five queries. Therefore, our novel ligand shape-based screening method constitutes a robust and efficient approach to the 3D similarity screening of small compounds and open the door to a whole new approach to drug design by implementing the method in the structure-based virtual screening.
机译:在这项工作中,我们通过使用Scucation函数Hamza-Wei-Zhan(HWZ)得分以及用于配体的增强的分子形状密度模型来扩展基于配体的虚拟筛选方法。该方法的性能已经针对有用诱饵数据库中的40个目标测试,并与我们之前的HWZ评分方法的性能相比。使用新型配体形状的方法的虚拟筛选结果证明了有利的改进(接收器操作员特性曲线AUC = .89±0.02的区域)和有效性(命中率HR1%= 53.0%±6.3和HR10%= 71.1% ±4.9)。使用多查询数据融合的基于最高配体形状的虚拟筛选方法的基于配体形状的虚拟筛选方法的整体性能的比较表明,我们的策略考虑了该组活性配体的化学信息。此外,结果表明,我们的方法适用于虚拟筛选,并产生优于使用五个查询的数据融合的其他研究的卓越的预测精度。因此,我们的新型配体形状的筛选方法构成了对小型化合物的3D相似性筛选的稳健和有效的方法,并通过在基于结构的虚拟筛选中实施方法,将大门用于全新的药物设计方法。

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