Preparing an SD File for a Predictive Model

Before you build a predictive model, prepare an SD file with molecules and properties to define the model.

See Also
Building a Model
  1. Create the SD file:

    • Compounds can consist of fragments with no counter-ions. If there are multiple fragments, GTD uses the largest.
    • Provide a value for the response property you plan to model for each compound.
    • For a classification model (bayesian, random forest, or pharmacophore), the response property must be categorical. When you build the model, specify a “preferred” value of the property, which corresponds to a positive category. For example, for an activity model, the categories might be “active” and “inactive,” with “active” being the positive case. For a toxicity model, the categories might be “toxic” and “nontoxic,” with “toxic” being the positive case.
    • For a regression model (random forest regression), the response property must be numeric. For XC50-type data, the preferred form of the response is pXC50 (the negative base-10 logarithm of the XC50 value) so that greater values correspond to increased potency. For example, for an activity model, the name of the response property might be pIC50.

  2. Copy the SD file to your 3DDrive.