2′-Fluoro-arabinonucleic Acid (FANA): A Versatile Tool for Probing Biomolecular Interactions
Bibliographic record
Abstract
This Account highlights the structural features that render 2'-deoxy-2'-fluoro-arabinonucleic acid (FANA) an ideal tool for mimicking DNA secondary structures and probing biomolecular interactions relevant to chemical biology.The high binding affinity of FANA to DNA and RNA has had implications in therapeutics. FANA can hybridize to complementary RNA, resulting in a predominant A-form helix stabilized by a network of 2'F-H8(purine) pseudohydrogen bonding interactions. We have shown that FANA/RNA hybrids are substrates of RNase H and Ago2, both implicated in the mechanism of action of antisense oligonucleotides (ASOs) and siRNA, respectvely. This knowledge has helped us study the conformational preferences of ASOs and siRNA as well as crRNA in CRISPR-associated Cas9, thereby revealing structural features crucial to biochemical activity.Additionally, FANA is of particular use in stabilizing noncanonical DNA structures. For instance, we have taken advantage of the anti N-glycosidic bond conformation of FANA monomers to induce a parallel topology in telomeric G-quadruplexes. Subsequent single-molecule FRET studies elucidated the mechanism by which these parallel G-quadruplexes are recognized and extended by telomerase. Similarly, we have utilized FANA to stabilize elusive telomeric i-motifs in the presence of concomitant parallel G-quadruplexes and under physiological conditions, thereby reinforcing their potential relevance to telomere biology. In another study, we adapted microarray technology and used FANA substitutions to enhance the binding affinity of the G-quadruplex thrombin-binding aptamer to its thrombin target.Finally, we discovered that DNA polymerases can synthesize FANA strands from DNA templates. On the basis of this property, other groups demonstrated that FANA, like DNA, can store hereditary information. They did so by engineering polymerases to efficiently transfer genetic information from DNA to FANA and retrieve it back into DNA. Subsequent studies showed that FANA could be evolved to acquire ribozyme-like endonuclease or ligase activity and to form high-affinity aptamers.Overall, the implications of these studies are remarkable because they promise a deeper understanding of human biochemistry for innovative therapeutic avenues. This Account summarizes past achievements and provides an outlook for inspiring the increased use of FANA in biological applications and fostering interdisciplinary collaborations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".