ONIOM and ab-initio calculations on the mechanism of uncatalyzed peptide bond formation
Bibliographic record
Abstract
Finding a proper transition structure for the peptide bond formation process can lead one to a better understanding of the role of ribosome in catalyzing this reaction. Using computer simulations, we performed the potential energy surface scan on the ester bond dissociation of P-site aminoacyl-tRNA and the peptide bond formation of P-site and A-site amino acids. The full fragments of initiator tRNA(i)(met) and elongator tRNA(phe) are attached to both cognate and non-cognate amino acids as the P-site substrate. The A-site amino acid for all four calculations is methionine. We used ONIOM calculations to reduce the computational cost. Our study illustrates the reduced rate of peptide bond formation for misacylated tRNA(i)(met) in the absence of ribosomal bases. The misacylated elongator tRNA(phe), however, did not show any difference in its PES compared with that for the phe-tRNA(phe). This demonstrates the structural specification of initiator tRNA(i)(met) for the amino acids side chain.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".