Structural Studies of <i>Trypanosoma brucei</i> RNA Editing Ligases and Their Binding Partner Proteins
Bibliographic record
Abstract
To study the mechanism of ligating nicked RNA strands, we conducted molecular dynamics simulations of Trypanosoma brucei RNA editing ligases L1 and L2 complexed with double-stranded RNA (dsRNA) fragments. In each resulting model, a Mg(2+) ion coordinates the 5'-PO4 of the nicked nucleotide and the 3'-OH of the terminal nucleotide for a nucleophilic reaction consistent with the postulated step 3 chemistry of the ligation mechanism. Moreover, coordination of the 3'-OH to the Mg(2+) ion may lower its pKa, thereby rendering it a more effective nucleophile as an oxyanion. Thus, Mg(2+) may play a twofold role: bringing the reactants into the proximity of each other and activating the nucleophile. We also conducted solvated interaction energy calculations to explore whether ligation specificities can be correlated to ligase-dsRNA binding affinity changes. The calculated dsRNA binding affinities are stronger for both L1 and L2 when the terminal nucleotide is changed from cytosine to guanine, in line with their experimentally measured ligation specificities. Because the ligation mechanism is also influenced by interactions of the ligase with partner proteins from the editosome subcomplex, we also modeled the structure of the RNA-bound L2 in complex with the oligonucleotide binding (OB) domain of largest editosome interacting protein A1. The resulting L2-dsRNA-A1 model, which is consistent with mutagenesis and binding data recorded to date, provides the first atomic-level glimpse of plausible interactions around the RNA ligation site in the presence of an OB domain presented in-trans to a nucleic acid ligase.
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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".