Taxol interaction with DNA and RNA Stability and structural features
Bibliographic record
Abstract
Taxol (paclitaxel) is an anticancer drug that interacts with microtubule proteins in a manner that catalyzes their formation from tubulin and stabilizes the resulting structures. However, in the human lung tumor cell, the concentration of paclitaxel is highest in the nucleus. Therefore, it was of interest to examine the interaction of taxol with DNA and RNA in aqueous solution at physiological pH. Capillary electrophoresis and Fourier transform infrared (FTIR) difference spectroscopic methods were used to characterize the nature of drugDNA and drugRNA interactions and to determine the taxol binding site, the binding constant, the sequence selectivity, the helix stability, and the biopolymer secondary structure in the taxolpolynucleotide complexes in vitro. The FTIR spectroscopic studies were conducted with taxol/polynucleotide (phosphate) ratios of 1/80, 1/40, 1/20, 1/10, 1/4, and 1/2 with a final DNA(P) or RNA(P) concentration of 12.5 mmol/L, and capillary electrophoresis was performed after incubation of taxol with polynucleotides at ratios of 1/200 to 1/12 with a final polynucleotide concentration of 1.25 mmol/L. Taxol was shown to bind to DNA and RNA at GC, AT, or AU bases and the backbone PO 2 group. Two types of binding were observed for taxolDNA with K 1 = 1.3 × 10 4 L mol 1 and K 2 = 3.5 × 10 3 L mol 1 , whereas taxolRNA complexes showed one type of binding with K = 1.3 × 10 4 L mol 1 . The taxolpolynucleotide complexation is associated with a partial helix stabilization and no major alterations of B-DNA or A-RNA structure. Key words: DNA, RNA, taxol, binding site, binding constant, conformation, helix stability, electrophoresis, FTIR spectroscopy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".