Takeuchi Kosuke, Kunimoto Ryo, Bajorath Jürgen
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Friedrich-Hirzebruch-Allee 6, Bonn D-53115, Germany.
Data Brief. 2021 Oct 8;39:107456. doi: 10.1016/j.dib.2021.107456. eCollection 2021 Dec.
In compound optimization, analogue series (ASs) are generated by introducing different R-groups (substituents, functional groups) at specific substitution sites. Systematic investigations of R-groups in medicinal chemistry have so far been rare. We have carried out a large-scale computational analysis of R-groups on the basis of ASs covering currently available bioactive compounds (Takeuchi et al., 2021). With the aid of a network data structure, frequently used R-groups and preferred replacements were identified. On the basis of these data, R-group replacement hierarchies were derived and organized in a searchable database that is made freely available. This contribution complements our systematic analysis (Takeuchi et al., 2021) by specifying the data we have generated and detailing their open access deposition.
在化合物优化中，通过在特定取代位点引入不同的R基团（取代基、官能团）来生成类似物系列（ASs）。迄今为止，药物化学中对R基团的系统研究很少。我们基于涵盖当前可用生物活性化合物的类似物系列（Takeuchi等人，2021年）对R基团进行了大规模计算分析。借助网络数据结构，确定了常用的R基团和优选的替代基团。基于这些数据，推导了R基团替代层次结构并将其组织在一个可搜索的数据库中，该数据库可免费获取。本文通过指定我们生成的数据并详细说明其开放获取存档，对我们的系统分析（Takeuchi等人，2021年）进行了补充。
