Chemical space networks: a powerful new paradigm for the description of chemical space

Chemical space network (CSN). Shown is a CSN with asymmetric similarity relationships in which an optimization-relevant compound pathway is traced (red).

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Design of chemical space networks incorporating compound distance relationships

F1000Research ◽

10.12688/f1000research.10021.2 ◽

2016 ◽

Vol 5 ◽

pp. 2634 ◽

Cited By ~ 1

Author(s):

Antonio de la Vega de León ◽

Jürgen Bajorath

Keyword(s):

Chemical Space ◽

Similarity Measures ◽

Data Sets ◽

Threshold Values ◽

Similarity Threshold ◽

Space Networks ◽

Structural Relationships ◽

Chemical Space Networks ◽

Similarity Relationships ◽

Activity Information

Networks, in which nodes represent compounds and edges pairwise similarity relationships, are used as coordinate-free representations of chemical space. So-called chemical space networks (CSNs) provide intuitive access to structural relationships within compound data sets and can be annotated with activity information. However, in such similarity-based networks, distances between compounds are typically determined for layout purposes and clarity and have no chemical meaning. By contrast, inter-compound distances as a measure of dissimilarity can be directly obtained from coordinate-based representations of chemical space. Herein, we introduce a CSN variant that incorporates compound distance relationships and thus further increases the information content of compound networks. The design was facilitated by adapting the Kamada-Kawai algorithm. Kamada-Kawai networks are the first CSNs that are based on numerical similarity measures, but do not depend on chosen similarity threshold values.

Download Full-text

Design of chemical space networks incorporating compound distance relationships

F1000Research ◽

10.12688/f1000research.10021.1 ◽

2016 ◽

Vol 5 ◽

pp. 2634

Author(s):

Antonio de la Vega de León ◽

Jürgen Bajorath

Keyword(s):

Chemical Space ◽

Similarity Measures ◽

Data Sets ◽

Threshold Values ◽

Similarity Threshold ◽

Space Networks ◽

Structural Relationships ◽

Chemical Space Networks ◽

Similarity Relationships ◽

Activity Information

Networks, in which nodes represent compounds and edges pairwise similarity relationships, are used as coordinate-free representations of chemical space. So-called chemical space networks (CSNs) provide intuitive access to structural relationships within compound data sets and can be annotated with activity information. However, in such similarity-based networks, distances between compounds are typically determined for layout purposes and clarity and have no chemical meaning. By contrast, inter-compound distances as a measure of dissimilarity can be directly obtained from coordinate-based representations of chemical space. Herein, we introduce a CSN variant that incorporates compound distance relationships and thus further increases the information content of compound networks. The design was facilitated by adapting the Kamada-Kawai algorithm. Kamada-Kawai networks are the first CSNs that are based on numerical similarity measures, but do not depend on chosen similarity threshold values.

Download Full-text