Representing clusters using a maximum common edge substructure algorithm applied to reduced graphs and molecular graphs
Representing clusters using a maximum common edge substructure algorithm applied to reduced graphs and molecular graphs
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DOI：
10.1021/ci600444g
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发表时间：
2007-03-01
影响因子：
5.6
通讯作者：
Cosgrove, David A.
中科院分区：
文献类型：
--
作者：
Gardiner, Eleanor J.;Gillet, Valerie J.;Cosgrove, David A.
化学数据库通常是集群的，目的是将具有相似结构特征的分子分组。理想情况下，药物化学家能够浏览集群的几个代表，以便解释集群成员的共同活动。然而，当分子使用指纹聚集时，可能很难破译存在的结构共性。这里，我们寻求通过基于集群成员的共享功能的最大公共子结构来表示集群。以前，我们已经使用简化图作为虚拟筛选的拓扑分子描述符，其中每个节点对应于一个广义官能团。在这项工作中，我们使用任何聚类方法对数据库进行预聚类。然后，我们将簇中的分子表示为简化的图形。通过重复应用最大公共边子结构(MCES)算法，我们得到一个或多个约简图簇代表。简化图的稀疏性意味着MCES计算可以实时执行。简化的图形团簇代表很容易根据功能活性进行解释，并且可以直接映射回它们对应的分子，为化学家提供了一种快速评估簇内包含的潜在活性的方法。然后对感兴趣的簇进行详细的R基团分析，使用适用于分子图的相同迭代MCES算法。
Chemical databases are routinely clustered, with the aim of grouping molecules which share similar structural features. Ideally, medicinal chemists are then able to browse a few representatives of the cluster in order to interpret the shared activity of the cluster members. However, when molecules are clustered using fingerprints, it may be difficult to decipher the structural commonalities which are present. Here, we seek to represent a cluster by means of a maximum common substructure based on the shared functionality of the cluster members. Previously, we have used reduced graphs, where each node corresponds to a generalized functional group, as topological molecular descriptors for virtual screening. In this work, we precluster a database using any clustering method. We then represent the molecules in a cluster as reduced graphs. By repeated application of a maximum common edge substructure (MCES) algorithm, we obtain one or more reduced graph cluster representatives. The sparsity of the reduced graphs means that the MCES calculations can be performed in real time. The reduced graph cluster representatives are readily interpretable in terms of functional activity and can be mapped directly back to the molecules to which they correspond, giving the chemist a rapid means of assessing potential activities contained within the cluster. Clusters of interest are then subject to a detailed R-group analysis using the same iterated MCES algorithm applied to the molecular graphs.