OligoDesign
Oligo Design Evaluation
What is oligo design evaluation — and why do AI-generated oligo designs still need one?
Designing an oligo — a PCR primer, a hybridization probe, a molecular beacon — has gotten fast. A person or an AI model can propose a candidate sequence in seconds. Oligo design evaluation is the separate, harder step: judging whether that sequence will actually work once it's synthesized and run in a real assay. That judgment is what an oligo design evaluator exists to provide.
Design vs. evaluation
Generating a sequence and evaluating a sequence are different skills. Generation optimizes for length, GC content, and target coordinates. Evaluation asks the questions a bench scientist asks before ordering a synthesis: Will the two primers in this pair bind at compatible temperatures? Does the 3′ end have a clean clamp, or is it GC-heavy and dimer-prone? Will this stem-loop beacon actually close in solution? Does this oligo cross-react with anything else in the pool?
An AI design tool can miss all of these — not because it can't compute a Tm, but because judging a design well requires the same accumulated pattern-recognition an experienced assay-development scientist builds over years of failed and successful assays. That's the layer oligo design evaluation adds on top of any design step, AI-assisted or not.
OligoDesign's oligo design evaluators
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Single Oligo Judge
Role-aware evaluation of one primer or probe sequence: Tm, GC content, secondary structure, 3′ clamp quality.
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Primer Pair Judge
Template-aware evaluation of a forward/reverse primer pair: Tm balance, clamp quality, dimer risk, amplicon check.
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Molecular Beacon Judge
Evaluates stem-loop architecture, loop-target binding fit, and closed-state stability.
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Tm Mismatch Judge
Evaluates binding across mismatched or variant targets for inclusivity and specificity screening.
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Pool Compatibility Judge
Screens multiplex oligo pools for cross-dimer risk using pairwise thermodynamic free energy.
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ePCR Mapper
In-silico primer mapping across sequence databases, with a confidence score for each predicted amplicon.
Every evaluator returns the same structure: a verdict, the risk drivers behind it, recommended actions, and the assumptions it made — so the result is something you can act on, not just a number to interpret yourself. The underlying calculations are published, literature-cited nearest-neighbor thermodynamic models; see the full methodology and citations.
Frequently asked questions
- What is oligo design evaluation?
- Judging whether a proposed primer, probe, or beacon sequence will actually perform in an assay — combining Tm, GC content, secondary structure, dimer risk, and role-specific design windows into one verdict with rationale, rather than reporting raw metrics alone.
- What is an oligo design evaluator?
- A tool that performs oligo design evaluation automatically: it takes a sequence and returns a structured verdict, the risk drivers behind it, and recommended actions — the way an experienced assay-development scientist would review a design.
- Why does an AI-designed oligo still need human-expert-grade evaluation?
- AI tools are fast at proposing sequences but are not reliable judges of assay performance. They can miss secondary structure, cross-dimer risk in a pool, or subtle Tm imbalance in a primer pair. Oligo design evaluation applies expert-level rules — grounded in published thermodynamic literature — as an independent check on any design, whatever generated it.
- How does OligoDesign evaluate a primer pair?
- The Primer Pair Judge checks Tm balance between the forward and reverse primer, 3′ clamp quality, primer-primer and self-dimer risk, and amplicon specificity against the template, then returns one structured verdict.
- Is OligoDesign's evaluation based on published methods?
- Yes — nearest-neighbor thermodynamic models from SantaLucia (1998), Owczarzy et al. (2008), Allawi & SantaLucia, Peyret et al., and Watkins & SantaLucia. Full formulas and citations are on the methodology page.