Ribosome Traffic Jam Simulator

Translation Controls

Initiation rate k_init 0.35 /s

Baseline elongation rate k_el 2.0 sites/s

Simulation speed 1.0×

Live Readouts

Ribosomes on mRNA

Proteins made

Throughput

0.0 /min

Jam length

0 sites

How it works

An mRNA is translated by many ribosomes at once, each covering roughly 10 codons (a "footprint") and unable to pass the ribosome ahead of it. This is the extended-particle TASEP (Totally Asymmetric Simple Exclusion Process) — first used by MacDonald, Gibbs & Pipkin (1968) specifically to model ribosome traffic, and still the standard framework for interpreting ribosome-profiling data.

Hop probability per frame:
P(i → i+1) = k_i · dt
  allowed only if sites [i+1, i+1+w) are empty (w = footprint)

Local rate k_i ∝ [charged cognate tRNA] for codon i
  common codon  → high k_i  → fast hop
  rare codon    → low k_i   → slow hop, ribosomes queue behind it

Steady-state protein output ≈ min(k_init, min_i k_i)

k_init — the rate new ribosomes load onto the start codon (controlled by initiation factors and 5′-UTR structure in real cells).
k_el — baseline elongation speed; scales every codon's hop rate together.
Rare-codon cluster — inserts a stretch of low-abundance-tRNA codons (red) mid-transcript; because ribosomes can't overtake, slower codons there create a visible traffic jam (queue) upstream, exactly as seen in real ribosome-profiling footprint density.

Real-world relevance: this queueing behaviour is why codon-optimizing a gene (swapping rare codons for common synonymous ones) is standard practice in recombinant protein production — it raises k_i at the bottleneck and increases whole-mRNA protein yield without changing the amino acid sequence.

Fast codon Rare / slow codon Ribosome

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