Structure-Activity Relationship (SAR) is a process by which the activity of a molecule is related to its molecular structure. If a significant ammount of structural and activity data is available a model can be made which can be used to predict the activity of a molecule or series of molecules.

In ICM SAR is undertaken using the Learn and Predict tools in a Molecular Table.

Learn

Step 1: Select the column you wish to predict and then Tools/Table/Learn or use the right click option shown below.

Step 2: Fill in the Learn options as shown below.

• Enter the name of table with which you want to perform the predictions. You may locate your table from the drop down arrow menu.
• Select the column from which you wish to learn. Use the drop down arrow to select.

NOTE If the table does not contain any numeric (integer or real) columns, there is nothing to predict, so the "Learn" button will be disabled.

• Enter a name for the learn model.
• Select which regression method you wish to use from the drop down menu. See the theory section to determine which method and parameters to use.
• Select which columns (descriptors) of your table you wish to use to 'learn'.
• If you are using chemical descriptors to produce your model select the maximal chain length.
• Select the number of cross-validation groups you wish to use or selected rows can be used for cross validation. The number of iterations will impact the speed of the calculation. 5 is the default number of groups but 2 would be the least rigorous and selecting the 'Leave-1-out' would be the most rigorous calculation.
• Click on the learn button and a table summarizing your model will be displayed as shown below.