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Protein Confidence-Map Audit
x402
Protein Confidence-Map Audit is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.035014/call, status unknown (last checked 2026-10-15).
Summarizes per-residue pLDDT scores into explicit confidence bins, categorizing structural confidence across up to 4000 residues
Price / call$0.035014
Success—
StatusUnknown
How this service works
Summarize supplied per-residue pLDDT scores into explicit confidence bins. Does not assess missing residues, folding correctness, function or clinical suitability. New modular adapter: retained result recovery for 24 hours, minimal receipt metadata for 90 days. Existing live route unchanged.
Output
Returns a structured summary of the supplied pLDDT scores organized into explicit confidence bins (e.g. very high, confident, low, very low), with per-bin residue counts or ranges. Results are retained for 24 hours; minimal receipt metadata is stored for 90 days. Does not assess missing residues, folding correctness, function, or clinical suitability.
Example use cases
AlphaFold output confidence review
“I've got 820 pLDDT scores from an AlphaFold prediction for a public protein — can you summarize them into confidence bins so I know which regions are reliably modeled?”
Synthetic protein QC pipeline
“Run a confidence-map audit on these 1200 per-residue pLDDT values from our synthetic protein dataset — I need a breakdown by confidence bin before we move to the next analysis step.”
Identifying low-confidence structural regions
“Here are 450 pLDDT scores from a public structure prediction — can you bin them by confidence level so I can see which residues fall into the low-confidence range?”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/compute/biology/protein-confidence-audit?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw per-residue pLDDT scores from any structure prediction model (e.g. AlphaFold, ESMFold) and need a fast, auditable confidence-bin summary without any broader structural or functional analysis. Ideal for QC pipelines, preprocessing steps, or compliance checks where you need an explicit, reproducible binning of confidence values rather than a qualitative interpretation.
Side effects
- Array length below 1 or above 4000 residues returns validation error
- Invalid dataClass value (not 'public' or 'synthetic') returns schema error
- Malformed or non-numeric pLDDT values trigger input rejection
- Missing required fields (plddt array or dataClass) return 400-level error
- x402 payment failure or insufficient USDC balance blocks request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| plddt | array | |
| dataClass | string |
Tags
x402
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