Alpha-carboxy nucleoside phosphonates as universal nucleoside triphosphate mimics
Bibliographic record
Abstract
Polymerases have a structurally highly conserved negatively charged amino acid motif that is strictly required for Mg(2+) cation-dependent catalytic incorporation of (d)NTP nucleotides into nucleic acids. Based on these characteristics, a nucleoside monophosphonate scaffold, α-carboxy nucleoside phosphonate (α-CNP), was designed that is recognized by a variety of polymerases. Kinetic, biochemical, and crystallographic studies with HIV-1 reverse transcriptase revealed that α-CNPs mimic the dNTP binding through a carboxylate oxygen, two phosphonate oxygens, and base-pairing with the template. In particular, the carboxyl oxygen of the α-CNP acts as the potential equivalent of the α-phosphate oxygen of dNTPs and two oxygens of the phosphonate group of the α-CNP chelate Mg(2+), mimicking the chelation by the β- and γ-phosphate oxygens of dNTPs. α-CNPs (i) do not require metabolic activation (phosphorylation), (ii) bind directly to the substrate-binding site, (iii) chelate one of the two active site Mg(2+) ions, and (iv) reversibly inhibit the polymerase catalytic activity without being incorporated into nucleic acids. In addition, α-CNPs were also found to selectively interact with regulatory (i.e., allosteric) Mg(2+)-dNTP-binding sites of nucleos(t)ide-metabolizing enzymes susceptible to metabolic regulation. α-CNPs represent an entirely novel and broad technological platform for the development of specific substrate active- or regulatory-site inhibitors with therapeutic potential.
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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) | 0.000 | 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 | 0.001 |
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".