High-Performance Liquid Chromatography–Electrospray Ionization-Mass Spectrometry Ligand Fishing Assay: A Method for Screening Triplex DNA Binders from Natural Plant Extracts
Bibliographic record
Abstract
A novel ligand fishing assay was established to screen triplex DNA binders from complicated samples by a combination of immobilization of triplex DNA on agarose beads and high-performance liquid chromatography-electrospray ionization-mass spectrometry (HPLC-ESI-MS). The biotinylated oligodeoxynucleotides were first bound to the streptavidin agarose beads and then incubated with the duplex DNA as the baits for ligand fishing. This assay was validated by the testing ligand library consisting of coralyne, ethidium bromide, vitexin, and formononetin. The binding affinities of ligands to target DNA were also obtained based on the calibration curves of ligands. Two components (berberine and palmatine) in the extract of Phellodendron chinense Schneid cortexes were fished out as triplex DNA binders by this assay, which indicated its feasibility for screening triplex DNA binders from complicated samples. This preliminary assay can be used for not only screening binders of triplex DNA from natural products extracts but also can obtain their binding affinity information.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".