3D QSAR Model: Predictor

Category Paths

Follow one of these paths in the Orion user interface, to find the floe.

  • Models

Description

The 3D QSAR Model: Predictor Floe is a tool for making potency predictions based on a model that was built previously.

Making model predictions using this floe requires two datasets: (1) a dataset of a model with stored receptors and reference molecules, if any, obtained from using the 3D QSAR Model: Builder Floe and (2) a dataset of molecules to make predictions for.

Output from this floe is a single dataset containing the model predictions, along with 3D conformers.

Note: If the training set is relatively large (e.g., greater than 300), consider increasing cube memory under “Cube Memory Parameters” section to avoid cube memory error. An eightfold increase is usually sufficient for a training set up to 1000 molecules.

Promoted Parameters

Title in user interface (promoted name)

Cube Memory Parameters

Cube Memory (memory): Minimum amount of memory in MiBs (1048576 B).

  • Type: decimal

  • Default: 1800

3D Conformer Parameters

Use Input 3D (use_input_3d): Whether to use 3D input structures. Flag will be ignored for molecules without 3D input structures.

  • Type: boolean

  • Default: True

  • Choices: [True, False]

Charge Method Parameters

Use Input Charges (use_input_charges): Use input charges.

  • Type: boolean

  • Default: False

  • Choices: [True, False]

Charge type (method_type): Charge assignment method.

  • Type: string

  • Default: am1bcc

  • Choices: [‘am1bcc’, ‘mmff’]