Canvas Similarity and Clustering Panel

Canvas Similarity and Clustering Panel Features

• Similarity tab
• Clustering tab

Similarity tab

In this tab, you set up the fingerprint calculation and calculate the similarity of the selected entries in the Project Table to the entries included in the Workspace.

• Precision options
• Fingerprint type option menu
• Atom typing scheme option menu
• Similarity metric option menu
• Tversky alpha and Tversky beta text boxes
• Sort selected entries by similarity option
• Calculate Similarity button
• Next button

Precision options

Choose the fingerprint precision. A higher number of bits reduces the chance of collisions; with 64-bit fingerprints, collisions should be extremely rare. A higher number of bits also means that the calculation takes longer to run.

Fingerprint type option menu

Choose the type of fingerprint to calculate. Radial, dendritic, or MolPrint2D often give the best results.

Atom typing scheme option menu

Choose an atom typing scheme for the fingerprint calculation. If you choose a more specific atom typing scheme, the fingerprints for each molecule will be more distinct, and the similarities between molecules will be smaller.

Similarity metric option menu

Choose the metric that is used for calculating similarities. See canvasFPMatrix for a list of metrics and their definitions.

Tversky alpha and Tversky beta text boxes

Specify the alpha and beta parameters if the Tversky metric is chosen from the Similarity metric option menu.

Sort selected entries by similarity option

Sort the selected entries in the Project Table by the similarity values, from highest to lowest. If you have more than one ligand in the Workspace, the maximum similarity is used for sorting.

Calculate Similarity button

Calculate the similarities. The similarities are reported as properties in the Project Table for the selected entries. If only one entry is included in the Workspace, the property name is Canvas metric Similarity. If more than one entry is included in the Workspace, five properties are added:

• Canvas Mean metric Similarity—Average of similarities to all included entries
• Canvas Max metric Similarity—Similarity of the most similar included entry
• Canvas Min metric Similarity—Similarity of the least similar included entry
• Canvas Max metric Similarity ID—the entry ID of the most similar included entry
• Canvas Min metric Similarity ID—the entry ID of the least similar included entry

Next button

Go to the Clustering tab. Only available after similarities have been calculated.

Clustering tab

In this tab, you can cluster the selected entries by their similarity values, using the fingerprints and the settings in the Similarity tab. Hierarchical agglomerative clustering is used. Once clustering is done, you can examine the clustering statistics, a dendrogram of the clustering, and the distance matrix, and you can apply the clustering to the selected entries, to create groups or create index and size properties.

• Linkage method option menu
• Calculate Clustering button
• Review clustering section
• Statistics button
• Dendrogram button
• Distance Matrix button
• Apply Clustering section
• Create option menu
• Number of clusters text box
• Apply Clustering button

Linkage method option menu

Specify the linkage method. These are the methods used by Canvas for hierarchical clustering.

Calculate Clustering button

Perform the hierarchical clustering calculation.

Review clustering section

This section gives access to the results of the clustering. The cluster strain is reported. Detailed results can be viewed by clicking the buttons, described below.

Statistics button

Display a plot of various statistics of the clustering as a function of the number of clusters, in the Clustering Statistics panel. The statistics are: Kelley penalty, R-squared, Semipartial R-squared, Merge distance, Separation ratio. You can click in the plot to set the number of clusters in the Number of clusters text box.

Dendrogram button

Display a dendrogram of the hierarchy of clusters, in the Dendrogram panel. The x-axis labels show structure titles. Hover over a label or a structure's vertical line to display the full title in a tooltip. If a structure is no longer in the Project Table, the entry ID is shown instead. You can click in the plot to set the number of clusters in the Number of clusters text box.

Click the Color by property link in the Dendrogram panel to open a popup for selecting a property to color the dendrogram branches by. When colored by a property, a circle appears at the base of each structure's vertical line to indicate its color. The popup contains the following settings:

• Property text box—Displays the property used to color the dendrogram. Click Select to open the property selector and choose a property. Only properties that have real values for all the clustered entries, and that take at least two distinct values, are listed. You can filter the properties by name and restrict the list to a property family. For details on these tools, see the Property Selection topic.
• Range text boxes—Set the minimum and maximum values of the property range for the color mapping. These values are set automatically when a property is selected.
• Use log scale option—Select this option to use a logarithmic scale for mapping property values to colors.
• Color map option menu—Select the color scheme to use for mapping property values to colors.
• Display color scale option—Select this option to display a color scale bar on the plot.
• Apply button—Click to apply the selected color settings to the dendrogram.
• Close button—Click to close the popup.

Distance Matrix button

Display the distance matrix used for clustering graphically, with values represented by a color map, in the Distance Matrix panel. You can display the matrix in cluster order (as shown in the Dendrogram panel) or in the original (input) order. You can click in the plot to display the 2D structures in the panel, and optionally in the Workspace.

Apply Clustering section

In this section, you can apply the clustering to the selected entries in the Project Table for a particular number of clusters.

Create option menu

Select the action to be taken when applying the clustering.

• Duplicate entries to a new group for each cluster—Create new groups for each cluster, with titles set to Cluster N (or N_M if clustering has been applied M times), duplicate all the selected entries, and put the duplicates into these new groups.
• Move entries to a new group for each cluster—Create new groups for each cluster with titles set to Cluster N (or N_M if clustering has been applied M times), and move the entries from their current location into the new groups.
• A group containing the structures nearest the centroid in each cluster—Create a new group, entitled Representative Entries (with a suffix M if clustering has been applied M times), and move the structure that is nearest the centroid in each cluster to this group.
• Cluster index and size properties for each entry—Create two new properties for each entry that record which cluster the entry belongs to (the index) and how big the cluster is.

Number of clusters text box

Specify the number of clusters to use when applying the clustering results to the selected entries. The optimal number of clusters is shown next to this text box.

Apply Clustering button

Apply the clustering to the selected entries in the Project Table using the option chosen from the Create option menu.