An In-Silico Pipeline for Rapid Screening of DNA Aptamers against Mycotoxins: The Case-Study of Fumonisin B1, Aflatoxin B1 and Ochratoxin A
Bibliographic record
Abstract
Aptamers are single-stranded oligonucleotides selected by SELEX (Systematic Evolution of Ligands by EXponential Enrichment) able to discriminate target molecules with high affinity and specificity, even in the case of very closely related structures. Aptamers have been produced for several targets including small molecules like mycotoxins; however, the high affinity for their respective target molecules is a critical requirement. In the last decade, the screening through computational methods of aptamers for their affinity against specific targets has greatly increased and is becoming a commonly used procedure due to its convenience and low costs. This paper describes an in-silico approach for rapid screening of ten ssDNA aptamer sequences against fumonisin B1 (FB1, n = 3), aflatoxin B1 (AFB1, n = 2) and ochratoxin A (OTA, n = 5). Theoretical results were compared with those obtained by testing the same aptamers by fluorescent microscale thermophoresis and by magnetic beads assay for their binding affinity (KD) revealing a good agreement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".