tVtriVax AI
PROTEIN DESIGN / ATF3 bZIP

Design for
selectivity.

Explore the balance between self-association and partner binding. Screen bZIP charge substitutions, inspect every contact, and compare the structural evidence.

Live browser calculationsNo sequence uploadResearch use only
What runs nowRegister detection → charge-contact scoring → constrained mutation screening. This is an explainable rule-based model, not trained ML. Structural predictions are precomputed; no AlphaFold job is launched.
01 / DEFINE THE QUESTION

Sequence & constraints

Canonical amino acids; single-sequence FASTA accepted. Positions are 1-based in this input. Maximum 2,000 residues.
Substitutions at detected e/g positions only. Leave blank for wild type.
Partners to preserve
A hypothetical sensitivity model only. Does not change the charge-count ranking.

Ready to analyze. Results are computed from the sequence and selected partners on this device.
04 / REVIEW INDEPENDENT EVIDENCE

Structure, with its limitations visible.

Precomputed AlphaFold2-Multimer
● Chain A   ● Chain B · Cα trace · drag / arrow keys

Mean pLDDT from this PDB · not affinity

Download full PDB ↗

Changing the live sequence does not generate or update these structures. The WT homodimer file uses a longer construct than the zipper-only confidence table.

Do not rank binding strength by ipTM.

In the supplied zipper-only set, six of eight homodimer models are antiparallel. ATF3–JUN ipTM varies only from 0.72 to 0.73. Neither result establishes mutant affinity or therapeutic activity.

Inspect all 16 zipper-only prediction summaries
Supplied model confidence and available topology annotations
ModelpLDDTpTMipTMTopology
Confidence CSV · Topology CSV
MODEL BOUNDARIES

Explainable, not all-knowing.

¹ Ten same-heptad g↔e′ contacts assume a parallel dimer and five complete heptads. Core packing, helix propensity, solvent, DNA cooperativity and cellular context are not modeled.

² The sensitivity readout assigns Q/N a hypothetical partial charge. It is a stress test, not a physical charge assignment or a calibrated energy calculation.

The supplied literature-peptide check concerns ATF3W variants, not experimental validation of m3 or m8. A shortlist still needs binding, selectivity and functional assays.

Literature-peptide reference table ↗
AI / ML ROADMAP · NOT RUNNING

Learn from measured selectivity.

Today: transparent contact rules plus stored AF2 model outputs. Next: collect matched Kd/Tm and partner-panel measurements; compare protein embeddings and structure features against this baseline.

Use held-out sequence families, calibrated uncertainty and active learning to choose informative experiments. Combine scores only after independent validation; no learned ATF3 selectivity model is deployed here.

Explore the existing vaccine ML workflow ↗