Robust Synthesis of Prebiotic Precursors in Drying Reactions of Amino Acids and Keto Acids
Bibliographic record
Abstract
Abstract One of the many intriguing mysteries surrounding origins‐of‐life research is understanding how biopolymers and metabolism co‐evolved from the very beginning through a process of chemical evolution. In biology, metabolism and polymerization of keto acids and amino acids are highly intertwined, yet the interplay between these two processes, utilizing these two simple building blocks under mild prebiotic conditions and in the absence of catalysts, has not been explored. Previously, dried reactions have been shown to promote the formation of protopolymers via condensation‐dehydration reactions. However, drying reactions of biological metabolites have not been explored, despite the fact that dehydration reactions are also crucial in current metabolism. Here, we uncover a robust reaction between keto acids and amino acids under mild drying conditions, yielding a diverse array of products. These reactions occur under a broad range of conditions and in some cases result in the formation of macromolecular assemblies. These findings expand the known inventory of prebiotically plausible compounds that can be considered in the context of prebiotic chemistry and exemplify how metabolism‐first and polymer‐first models can be reconciled.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".