Computer Simulations of RNA Replication in Protocells
Bibliographic record
Abstract
The RNA world hypothesis posits that at some stage in the development of life, RNA functioned as both an informational polymer and a catalyst for important reactions. However, many questions remain as to how RNA molecules might have evolved into living organisms. This thesis uses computer simulations to model processes thought to be important to the development of an RNA world. First, a model is discussed which describes non-enzymatic polymerization of single-stranded RNA from different kinds of activated nucleotides, a necessary first step towards an RNA world. It was found that a system undergoing polymerization of RNA from 5′-activated triphosphates or imidazolides behaves differently from an equilibrium system undergoing reversible polymerization reactions from 2′,3′-cyclic monophosphates, for example. In the 5′-triphosphate case, the system is not in equilibrium but rather in a state of circular reaction flux that must be maintained by an external source of phosphates. This model is then adapted to investigate non-enzymatic template-directed replication of RNA strands. It is found that this process fulfills all the necessary requirements to function as a metabolism which maintains a difference between the outside non-living environment and the internal environment of the cell. Finally, byproducts arising from the template copying mechanism in this model are discussed, including the development of highly regular sequence patterns in the strand population due to selection for the ability to form duplexes with neighbouring strands. Altogether, this thesis illustrates new implications, potential pitfalls, and possibilities of the RNA world hypothesis for the origin of life. In particular, it emphasizes the fundamental link between the processes of replication and metabolism, both of which must have been crucial to the functioning of the earliest protocells. This link has been largely overlooked in scientific literature on the topic to date.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | high |
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) | 0.035 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".