Pick a kinase, supply two or more compounds, and the model orders them for that kinase. Nothing is scored on its own and then subtracted: the forest is handed the whole comparison as one row: ligand A, the sequence, ligand B, in that precise order, and returns which ligand is the more potent of the two, with the strength of that call. Every pair of the compounds you supply is put to it that way, and the ranking below is a summary of those answers.
Two at minimum, 5 at most per run, drawn and pasted combined. Every pair is scored, so n compounds is n(n − 1)/2 comparisons, 10 compounds is 45.
Drawing structures never needs an email. Pasting or uploading a list of compounds does, and the full report is emailed back to you.
Unlocks the paste box and the file upload below ↓
We send the full results there, and let you know when the models change.
This model's prediction strength runs from 0.5, a coin flip, to 1.0. These are the accuracies measured for each band on the ChEMBL test set, and they are what the colors below mean. The selectivity tool defines strength the same way, but its accuracies were measured on a different test set, so the same strength does not buy the same accuracy on both.
What these bands mean in practice, and where the model is weakest: potency limitations.
The cutoff does not change the order, every comparison counts toward the score. It reports how many comparisons were too close to call, which is the honest measure of how firm the ranking is: the more of them, the more the neighboring rows should be read as roughly equivalent.
Method, training set, test set and every figure quoted here: LigASeqLigB potency report.