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USRCAT: real-time ultrafast shape recognition with pharmacophoric constraints

机译:USRCAT:具有药效学约束的实时超快速形状识别

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摘要

BackgroundLigand-based virtual screening using molecular shape is an important tool for researchers who wish to find novel chemical scaffolds in compound libraries. The Ultrafast Shape Recognition (USR) algorithm is capable of screening millions of compounds and is therefore suitable for usage in a web service. The algorithm however is agnostic of atom types and cannot discriminate compounds with similar shape but distinct pharmacophoric features. To solve this problem, an extension of USR called USRCAT, has been developed that includes pharmacophoric information whilst retaining the performance benefits of the original method.
机译:背景技术对于希望在化合物库中发现新型化学支架的研究人员而言,使用分子形状进行基于配体的虚拟筛选是一种重要的工具。超快速形状识别(USR)算法能够筛选数百万种化合物,因此适合在Web服务中使用。但是,该算法与原子类型无关,无法区分形状相似但具有药效学特征的化合物。为了解决这个问题,已经开发了一种名为USRCAT的USR扩展,其中包括药效学信息,同时保留了原始方法的性能优势。

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