Ultra Model Sets 01 39
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For this iteration, the set of morgan_1024_predictions (obtained from Step 25) contains only validated predictions. The set of negative predictions can be regenerated as explained previously with a different molecular sample size, but this time a conventional docking library must be used. Running the same set of input molecules through the system produces a new set of positives and negatives that can be reused in future iterations.
Because it is impossible to visually inspect 10,000 hits before docking, we turn to the open source software DBD_available_hits.html, and the output is then parsed by a Python script that generates a new morgan_1024_predictions file (Step 26).
(Recommended) For both evaluation purposes, reload the best_model_stats.txt file after Step 26. The first value represents the percentage of predicted molecules. The second value should be compared to the Total Left value to ensure that previous model generalizability was verified. d2c66b5586