Novartis Institutes for BioMedical Research, Novartis Pharma AG, Novartis Campus, 4002 Basel, Switzerland.
T5 Informatics GmbH, Spalenring 11, 4055 Basel, Switzerland.
J Chem Inf Model. 2020 Jul 27;60(7):3331-3335. doi: 10.1021/acs.jcim.0c00296. Epub 2020 Jul 7.
We present an implementation of the scaffold network in the open source cheminformatics toolkit RDKit. Scaffold networks have been introduced in the literature as a powerful method to navigate and analyze large screening data sets in medicinal chemistry. Such a network can be created by iteratively applying predefined fragmentation rules to the investigated set of small molecules and by linking the produced fragments according to their descendence. This procedure results in a network graph, where the nodes correspond to the fragments and the edges correspond to the operations producing one fragment from another. In extension to the scaffold network implementations suggested in the literature, the presented implementation in RDKit allows an enhanced flexibility in terms of customizing the fragmentation rules and enables the inclusion of atom- and bond-generic scaffolds into the network. The output, providing node and edge information on the network, enables a simple and elegant navigation through the network, laying the basis to organize and better understand the data set being investigated.
我们在开源化学信息学工具 RDKit 中实现了支架网络。支架网络作为一种强大的方法，已在文献中被引入，用于在药物化学中导航和分析大型筛选数据集。可以通过迭代应用预定义的片段规则来创建这样的网络，对研究的小分子集进行处理，并根据它们的衍生关系连接生成的片段。该过程会生成一个网络图，其中节点对应于片段，边对应于从一个片段生成另一个片段的操作。除了文献中建议的支架网络实现之外，RDKit 中提出的实现还允许在自定义片段规则方面具有更高的灵活性，并能够将原子和键通用支架纳入网络。输出提供有关网络的节点和边信息，支持通过网络进行简单而优雅的导航，为组织和更好地理解所研究的数据集奠定基础。
