Ligand A → sequence → ligand B. Pick a receptor, supply two or more compounds, and the model orders them for that receptor.
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 the probability that ligand A is the more potent of the two. Every pair of the compounds you supply is put to it that way, in both ligand orders, and the two answers are averaged.
CCN1CCC[C@H]1CNC(=O)c1cc(Br)cc(OC)c1OCCOc1cccc(CCc2ccccc2OCCN2CCc3ccccc3C2)c1Receptors the model was fitted on are grouped first, with their held-out accuracy and comparison count. Names below that group are recognised but were not in the training set, and a result for one of them is unvalidated.
A sequence the model was not trained on is scored and flagged. It is not covered by any accuracy figure on this site.
Two at minimum, 2 at most per run, drawn and pasted combined. Every pair is scored, so n compounds is n(n−1)/2 comparisons.
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.
Prediction strength is the larger of the two output probabilities, so it runs from 0.5, a coin flip, to 1.0. These are the accuracies measured for each band on the held-out set, and they are what the colours in the result mean.
| Strength | Right this often | Share of comparisons |
|---|---|---|
| 0.80 and above | 89.2% | 1.3% |
| 0.70 to 0.80 | 86.1% | 5.3% |
| 0.60 to 0.70 | 76.7% | 19.6% |
| 0.50 to 0.60 | 58.5% | 73.5% |
Do not read past 0.80. The curve turns over there, falling from 0.887 to 0.869 on 1,537 comparisons, so this page does not offer a higher cutoff.
The cutoff does not change the order. Every comparison counts toward the ranking; the cutoff decides which ones are reported as firm.
Accuracy on this page is measured over comparisons between receptors the model was fitted on, 182 of them with a held-out score. It says nothing about a receptor the model has never seen.