Finding Key Members in Compound Libraries by Analyzing Networks of Molecules Assembled by Structural Similarity

Characterization of chemical libraries is an essential task in everyday chemoinformatics practice. This study describes some potential uses of network visualization and analysis methods to identify distinguished members of compound libraries. Molecules were ordered into networks by their structural similarity defined by molecular fingerprints. Various properties of such networks were examined. It was shown, that the correlation methods used to calculate the similarity between two structures radically determined the topology of networks. From the same set of molecules, the Russel−Rao and the Baroni−Urbani methods created sparser and denser networks, respectively, than using the Tanimoto method. Central nodes, corresponding to central compounds in the libraries, were determined for some example data sets. It was shown by the case of adenosine A1, A2, and dual antagonists that the methods used to identify central nodes could be divided into two groups: (1) centrality methods, exemplified by the centroid cent...