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二维指纹和三维形状相似性方法在虚拟筛选中的性能评估。

Performance evaluation of 2D fingerprint and 3D shape similarity methods in virtual screening.

机构信息

Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.

出版信息

J Chem Inf Model. 2012 May 25;52(5):1103-13. doi: 10.1021/ci300030u. Epub 2012 May 11.

Abstract

Virtual screening (VS) can be accomplished in either ligand- or structure-based methods. In recent times, an increasing number of 2D fingerprint and 3D shape similarity methods have been used in ligand-based VS. To evaluate the performance of these ligand-based methods, retrospective VS was performed on a tailored directory of useful decoys (DUD). The VS performances of 14 2D fingerprints and four 3D shape similarity methods were compared. The results revealed that 2D fingerprints ECFP_2 and FCFP_4 yielded better performance than the 3D Phase Shape methods. These ligand-based methods were also compared with structure-based methods, such as Glide docking and Prime molecular mechanics generalized Born surface area rescoring, which demonstrated that both 2D fingerprint and 3D shape similarity methods could yield higher enrichment during early retrieval of active compounds. The results demonstrated the superiority of ligand-based methods over the docking-based screening in terms of both speed and hit enrichment. Therefore, considering ligand-based methods first in any VS workflow would be a wise option.

摘要

虚拟筛选 (VS) 可以通过配体或基于结构的方法来实现。最近,越来越多的基于配体的 2D 指纹和 3D 形状相似性方法被用于 VS。为了评估这些基于配体的方法的性能,我们对一个经过精心挑选的有用虚拟化合物目录 (DUD) 进行了回顾性 VS。比较了 14 种 2D 指纹和 4 种 3D 形状相似性方法的 VS 性能。结果表明,2D 指纹 ECFP_2 和 FCFP_4 的性能优于 3D PhaseShape 方法。这些基于配体的方法也与基于结构的方法(如 Glide 对接和 Prime 分子力学广义 Born 表面面积再评分)进行了比较,结果表明,在早期检索活性化合物时,2D 指纹和 3D 形状相似性方法都可以产生更高的富集度。结果表明,基于配体的方法在速度和命中富集方面都优于基于对接的筛选。因此,在任何 VS 工作流程中首先考虑基于配体的方法将是明智的选择。

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