Specimen
Assay readout
Results will appear here once you run a prediction.
Submit a peptide sequence and a target organism. The model estimates the MIC needed to inhibit visible growth of that strain.
Results will appear here once you run a prediction.
Type or paste an amino-acid sequence into the
Peptide sequence box using the standard one-letter
codes (ACDEFGHIKLMNPQRSTVWY) — e.g.
GIGKFLHSAKKFGKAFVGEIMNS. Lowercase is fine, it’s
uppercased automatically. Sequences work best between roughly
5–60 residues; much shorter or longer ones still run but
come back with a reliability warning.
Choose the bacterial or fungal strain you want the MIC estimated against from the Target organism dropdown, then hit Run prediction. The model looks at that organism’s taxonomy and Gram status alongside the sequence — the same peptide can get very different MIC estimates against different organisms.
The big number is the predicted MIC in µg/mL
— the lowest peptide concentration expected to stop visible
growth of that organism. Lower means more potent.
Underneath it, log10(MIC) is the raw value the model
was trained to predict; the µg/mL figure is just
10 raised to that number, shown because it’s
the unit used in real susceptibility assays.
The colored chain below the MIC value shows each residue’s chemical class (basic, acidic, polar, hydrophobic, aromatic, structural) so you can eyeball the sequence’s composition. Any amber warnings mean the sequence falls outside the typical range of the training data — treat that prediction with more caution.
RWLRLNGRWLRL is a sequence from DBAASP’s
held-out test set — it never appears in the model’s
training data. Seven independent lab assays measured its MIC
against E. coli ATCC 25922 at between 7.7 and 31.1
µg/mL; the median of those measurements is
≈14.3 µg/mL (log10(MIC)
≈ 1.15). Run this same sequence and organism through
the model above and it predicts ≈14.1
µg/mL — within a couple percent of the real
assay result. In plain terms: a concentration of about 14
micrograms of peptide per milliliter of broth was the lowest dose
that stopped visible E. coli growth in these experiments,
and that’s what the model estimated too. A lower
number means the same thing but with less peptide needed —
e.g. a predicted log10(MIC) = 0.56 corresponds to
MIC ≈ 100.56 ≈ 3.6 µg/mL, a
more potent result than this peptide against the
same strain; log10(MIC) = 2.0 (MIC = 100
µg/mL) would be a weaker one. Predictions won’t always
land this close — see the
project journey page for the model’s
overall accuracy across the full test set.