Usually I use python for analyse, visualize chemical space. Because, I love coding. 😉
I know, work flow tool is useful solution to do that.
So, I tried to plot chemical space using Knime. Knime is one of famous work flow tool and lots of nodes are developed.
At first, the flow read smiles strings from excel file. And convert smies to RDKit molecule.
Then calculate morgan FP using RDKit Finger printer. You know, the node can also calculate various FP like MACCS, topological etc.
Next, extend bit vector to 1024 bit columns.
And do PCA and make scatter plot. The plotting node is implemented in Erlwood chemoinformatics node.
When I call view scatter plot, I got following dynamic scatter plot.
The node can select each columns easily and user can set color or size own criteria. And visualize structure as label. Wow cool!
And I set activity cliff viewer.
The node needs two parameter, one of smiles and another is distance matrix of similarity.
N x N distance matrix is generated using distance matrix calculate node.
Finally run the flow, I got network view of activity cliffs.
Edges that are colored green are indicated activity cliffs. ( in my case delta pIC50 >= 1.0 and similarity >= 0.5 )
Hmm but the image seems to difficult to understand SAR. Cytoscape is suitable tool to visualize network.
Activity cliffs table seems good.
Knime is powerful tool for medchem.