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Contents
 
Introduction
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Reference Guide
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Protein Structure
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Virtual Screening
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 Make APF/SAR Model
 Predict Metabolic Oxidation
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14.5 Results Table
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The results table will contain the columns from the chemical table that you screened plus the following results columns: Depending on your selection you might have two tables Model Pairwise and Target Pairwise

  • mol - your query chemical
  • target - the target model you screened against
  • pPValue - kcc/hybrid4D+2D models only: -Log(probability) relative to approved drug decoys capped at 5: 1: Top 10 percent 2: Top 1 percent 3: Top 0.1 percent
  • MolpKd - kcc/hybrid4D+2D models only: Prediction of pKd, pKi, pIC50, pEC50, etc >6. indicates submicromolar value, >9. indicates nanomolar, ND indicates disimilarity to known binders
  • MolpKd Error - kcc/hybrid4D+2D models only: Estimated total uncertainty/error for pKd prediction, including experimental error of ~1. pKd unit
  • MolClass - kcc/hybrid4D+2D models only: Classification Score: for kcc models: nProbability of being a positive, assume 0.5% hitrate for others: 1. Median value of actives 2.Median value of inactives
  • TANIsim - kcc models only: Tanimoto distance from model nearest compound
  • modelnearestCpd - kcc models only: nearest compound to the query in the model
  • MolZScore - apf models only: Z-Score 3. indicates 3 standard deviation above approved drugs decoy
  • predictType - model type
  • modelAUC - Area Under Curve (AUC) for model
  • modelpKdAUC - kcc models only: AUC for pKd model
  • modelRMSE - kcc models only: RMSE for model
  • modelQ2 - kcc models only: Q2 for model
  • MolDockScore hybrid docking only - ICM docking score, Score < -32. are in general significant, but may vary from structure to structure.

Fold Columns to Original Table

In the Tools panel of the table there is a convenient way of packaging your results into your original query table.


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