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Compound Similarity Networks from Iain
Communitymalaria research community
More fantastic work from Iain Wallace of ChEMBL, below. These are maps of active antimalarials and predicted targets, expressed as similarity maps, i.e. with an extra level of analysis added on top. This provides a very intuitive way of walking through related compounds to compare structures. How best do we use this kind of analysis - as a target guide, or as a "prediction of what to make next" guide?
I have now predicted targets for all the anti-malarial active compounds in Chembl-NTD (~20,000). I have a full report for all these compounds, but it is quite large (~90mbs and 1200 pages) so I have displayed the results as a compound similarity network (posted here). In this network, compounds are represented as nodes and very similar compounds are connected by edges. Nodes are coloured by their predicted top scoring target. The names of the compounds can be viewed by zooming in very far and opening the file in Illustrator.
A similar map for compounds similar to zyh-72 [and one of the starting "Near Neighbour" set TCMDC 123563] in this dataset is posted here.
Also [on the two pages linked above] are two original networks that were generated using cytoscape (http://www.cytoscape.org/). If you install the cytoscape plugin "ChemViz", (http://www.cgl.ucsf.edu/cytoscape/chemViz/), you can right click a node and view the compound structure. You can also view the target of the compound.
I think networks are useful way of visualizing/integrating different types of information (for example http://www.ncbi.nlm.nih.gov/pubmed/21877291) and I would be interested to hear if you had any thoughts of how to make this type of visualization more useful. For example the similarity measure I am using may not be finding molecules that you would expect to find.