基于药物化学家直觉的详尽SAR分析工具

IF 0.4 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Chem-Bio Informatics Journal Pub Date : 2019-04-15 DOI:10.1273/CBIJ.19.19
H. Koga
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引用次数: 0

摘要

高通量筛选(HTS)是一种常见的药物发现方法。尽管化学信息学社区已经提出了各种HTS数据分析方法,但药物化学家仍然渴望直观的工具来分析HTS hit的构效关系(SAR)。在此,作者提出了SAR分析工具,旨在帮助药物化学家利用常规SAR表掌握感兴趣的化学空间。这些工具包括一个即时分析环境和一系列用于在交互分析之前进行数据处理的计算协议。该方案设计用于以下过程:i)基于简单规则的结构分类,以模拟药物化学家的目视检查;ii)利用药物片段(PHF),一个新的子结构概念,详尽地生成有前途的SAR表;iii)全面的类似物搜索,从手头的化合物中找出与SAR表中空白细胞对应的化合物。一个使用筛选核糖体蛋白S6磷酸化抑制剂数据的案例研究(PubChem AID:493208)表明,这些工具对于生成常规SAR表非常有用,可用于大规模数据(如HTS)的实际应用。
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Exhaustive SAR analysis tools for HTS hits based on intuition of medicinal chemists
High-throughput screening (HTS) is a common practice in drug discovery. Although the chemoinformatics community has proposed various approaches for HTS data analysis, medicinal chemists continue to long for intuitive tools for the structure-activity relationship (SAR) analysis of HTS hits. Here, the author propose SAR analysis tools that were designed to help medicinal chemists grasp the chemical space of interest with conventional SAR tables. These tools comprise an on-the-fly analysis environment and a series of computational protocols for data processing prior to the interactive analysis. The protocols are designed for the following processes: i) structural classification based on simple rules to mimic visual inspection by medicinal chemists; ii) exhaustive generation of promising SAR tables using Pharmacofragment (PHF), a novel substructure concept; and iii) comprehensive analogue search to identify compounds that correspond to blank cells in SAR tables from compounds at hand. A case study using data from a screen for ribosomal protein S6 phosphorylation inhibitors (PubChem AID:493208) suggests that these tools are useful for generating conventional SAR tables for practical application to large-scale data such as HTS.
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来源期刊
Chem-Bio Informatics Journal
Chem-Bio Informatics Journal BIOCHEMISTRY & MOLECULAR BIOLOGY-
CiteScore
0.60
自引率
0.00%
发文量
8
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