Efficient whole-cell biocatalytic synthesis of 2′-deoxy-2′-fluoroadenosine, a key building block for nucleic acid drugs
Bibliographic record
Abstract
2′-Deoxy-2′-fluoroadenosine (2′-F-dA) is a nucleoside analogue used as a key building block for oligonucleotide drugs. It can be biosynthesized from a low-cost 2′-deoxy-2′-fluorouridine via one-pot transglycosylation catalyzed by a thymidine phosphorylase (TP) and a purine nucleoside phosphorylase (PNP). However, reliance on purified enzymes and low space-time yields present challenges for industrial application of the process. Here, we develop a whole-cell-based biocatalytic system employing TP and PNP from Escherichia coli , which demonstrates high catalytic efficiency and operational simplicity in scaled-up reaction. In particular, a thermal pretreatment of TP- and PNP-expressing whole cells, determined as 50 °C for 3 h, effectively suppressed endogenous deamination side reaction while enhancing 2′-F-dA yield. Subsequent optimization of enzyme and substrate loadings and their relative ratios achieved an unprecedented space-time yield of 1.22 g/L/h with 88.1 g/L product titer in a 500 mL scaled-up reaction, manifesting a highest total conversion of 68.2 %. An integrated purification process yielded gram-scale solid powder of 2′-F-dA with 98.0 % chemical purity and 85.0 % recovery. This novel whole-cell biocatalytic process demonstrates significant industrial potential for the production of 2′-F-dA.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 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".