Selection, Characterization, and CDR Shuffling of Naive Llama Single-Domain Antibodies Selected against Auxin and Their Cross-Reactivity with Auxinic Herbicides from Four Chemical Families
Bibliographic record
Abstract
Indoleacetic acid (IAA)-binding single-domain antibodies (sdAbs) were isolated from a naive phage-display library constructed from the heavy chain antibody repertoire of a Ilama. The highest-affinity sdAb isolated (CSF2A) had a K(D) of 5-20 microM for two IAA-protein conjugates and a K(D) of 20 microM for free IAA. This sdAb also bound to a synthetic auxin analogue, 1-naphthaleneacetic acid (NAA), and to six auxinic herbicides (K(D) values of 0.5-2 mM), but not to serotonin and tryptophan, which are structurally similar to IAA but have no auxinic activity. To understand how sdAb CSF2A binds IAA and to determine which complementary-determining region(s) (CDR) participate(s) most in binding IAA, CSF2A was shuffled with four other sdAb clones by staggered extension process (StEP). After panning against IAA, two shuffled sdAbs were found: sdAb CSB1A, which originated from three different parental clones, and sdAb CSE8A, derived from two parental clones. These shuffled sdAbs and CSF2A were each fused to the B subunit of the Escherichia coli verotoxin, resulting in the formation of the pentamerized sdAbs V2NCSB1A, V2NCSE8A, and V2NCSF2A, which were analyzed by surface plasmon resonance (SPR) along with the sdAbs previously isolated. The shuffled clones had affinity for IAA (20 microM) similar to that of the highest affinity parental clone CSF2A, but much lower affinity for the auxinic herbicides. CDR2 was instrumental in binding IAA, whereas hydrophobic CDR3 was important for binding the auxinic herbicides. A novel SPR methodology is also described for specific immobilization of pentamerized sdAbs, allowing determination of K(D) values of Ab interaction with underivatized, low molecular weight haptens.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".