A simple method for eliminating fixed‐region interference of aptamer binding during SELEX
Bibliographic record
Abstract
Standard libraries for systematic evolution of ligands by exponential enrichment (SELEX) typically utilize flanking regions that facilitate amplification of aptamers recovered from each selection round. Here, we show that these flanking sequences can bias the selection process, due in part to their ability to interfere with the fold or function of aptamers localized within the random region of the library sequence. We then address this problem by investigating the use of complementary oligonucleotides as a means to block aptamer interference by each flanking region. Isothermal titration calorimetry (ITC) studies are combined with fold predictions to both define the various interference mechanisms and assess the ability of added complementary oligonucleotides to ameliorate them. The proposed blocking strategy is thereby refined and then applied to standard library forms of benchmark aptamers against human α-thrombin, streptavidin, and vascular endothelial growth factor (VEGF). In each case, ITC data show that the new method effectively removes fixed-region mediated interference effects so that the natural binding affinity of the benchmark aptamer is completely restored. We further show that the binding affinities of properly functioning aptamers within a selection library are not affected by the blocking protocol, and that the method can be applied to various common library formats comprised of different flanking region sequences. Finally, we present a rapid and inexpensive qPCR-based method for determining the mean binding affinity of retained aptamer pools and use it to show that introduction of the pre-blocking method into the standard SELEX protocol results in retention of high-affinity aptamers that would otherwise be lost during the first round of selection. Significant enrichment of the available pool of high-affinity aptamers is thereby achieved in the first few rounds of selection. By eliminating single-strand (aptamer-like) structures within or involving the fixed regions, the technique is therefore shown to isolate aptamer sequence and function within the desired random region of the library members, and thereby provide a new selection method that is complementary to other available SELEX protocols.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".