Phase 2 — Protein Synthesis
If abiogenesis is the “Phase 3” claim, translation is the “Phase 2” mechanism: how one-dimensional code becomes three-dimensional catalytic structure—reliably, repeatably, and fast enough to outrun equilibrium.
Choose your level
This section is written in layers. Pick your preferred depth and reading style. (Nothing is tracked; this only changes what your browser shows.)
1) The core claim
Translation is not “data processing.” It’s a physical system that enforces a rule: codons (triplets) must be matched to amino acids consistently, across the whole cell, under noise, drift, and damage.
The difficulty isn’t that a mapping exists. The difficulty is that the mapping must be implemented in molecules: tRNA identity, synthetase specificity, ribosomal reading-frame control, and enough error tolerance to avoid collapse.
What this connects to
- Origins: why “code” and “enzymes” form a causality loop (chicken/egg).
- Evolution: what cumulative selection can and cannot do without a working translation pipeline.
- Your simulation: how quickly random edits drift into “single-step selection” territory.
2) The Phase 2 modules
These are the sub-pages that will make Phase 2 “walkable.” We can build them one at a time.
Translation machinery
Ribosome, tRNA, aminoacyl-tRNA synthetases (AARS), initiation/elongation factors—what each contributes and why the whole is coupled.
Next page: translation-machinery.html
Error control & fidelity
Why one wrong charge in ~10,000 can still be catastrophic at scale, and how editing sites and kinetic proofreading act like “logic constraints.”
Next page: error-correction.html
Bootstrapping dilemma
The circular dependency: translation requires enzymes; enzymes require translation. What “urzyme” / ribozyme hybrids claim, and what they must still explain.
Next page: bootstrapping.html
3) Expandable layers
These are designed to mirror your book’s structure while staying web-friendly.
Intro layer: what “Phase 2” means
“Phase 2” is the missing mechanism between chemistry and biology: a system that can read a sequence and build a corresponding catalyst repeatedly inside a bounded environment.
A useful shorthand: the genetic code is the mapping; translation is the enforcement.
Standard layer: the minimum moving parts
At minimum, translation needs:
- mRNA (or equivalent template) exposing codons
- tRNAs that “interpret” codons via anticodons
- AARS enzymes that correctly charge tRNAs with amino acids
- Ribosomal machinery that maintains reading frame and catalyzes peptide bond formation
- Energy (ATP/GTP or a plausible predecessor)
You can simplify any one element only if you explain how the system avoids fatal hybrids.
Advanced layer: why the “dilemma” is causal, not just statistical
The deep problem is a coupled constraint system: code is useless without translation, but translation is unstable without code-backed repair and reproduction. In other words, even if a rare helpful molecule appears, the question is whether the system can hold its gains.
That’s why this section bridges directly into your simulation results and into the discussion of cumulative selection.
Next
Recommended next build
Build translation-machinery.html first, then link it from this page. It’s the most “anchoring” explainer for Phase 2.
Or keep it interactive
Expand the demo page to show: a) the codon-to-amino map, b) drift tracking, and c) “abort” logic visualization.