Module 2 · The Cycle

Elongation Cycle

Each amino-acid addition is a three-step cycle: aminoacyl-tRNA loading at the A site, peptidyl transfer, and translocation. Each cycle consumes two GTP (one for EF-Tu, one for EF-G) and extends the peptide by one residue. A bacterial ribosome runs this cycle 20 times per second; a eukaryotic ribosome ~5–6 times per second. This module traces the mechanism.

1. tRNA Loading (EF-Tu · aminoacyl-tRNA)

EF-Tu (bacterial; eEF1A eukaryotic) binds aminoacyl-tRNAs with GTP. The EF-Tu · GTP · aa-tRNA ternary complex enters the A-site mRNA codon. If Watson-Crick pairing is correct:

The 16S rRNA adenines A1492/A1493 and ribose 2′-OH sensors check codon-anticodon helix geometry (Ramakrishnan 2000).
Correct geometry activates EF-Tu’s GTPase; GTP → GDP; conformational change releases aa-tRNA into the A site.
EF-Tu-GDP dissociates; EF-Ts recycles it to EF-Tu-GTP.

Non-cognate tRNAs fail the geometric check, EF-Tu does not hydrolyse GTP, and the ternary complex dissociates. This is the initial selection step.

2. Kinetic Proofreading

Even perfect initial selection cannot achieve the ~10⁻³ error rate observed (a single binding-affinity decision has 10⁻² discrimination at best). The ribosome adds a second selection step: after EF-Tu dissociation but before peptidyl transfer, a proofreading stage allows non-cognate tRNAs a second chance to dissociate before being irreversibly incorporated. This two-step architecture — initial selection + proofreading — is the Hopfield/Ninio kinetic proofreading(1974) mechanism, and explains how the ribosome achieves 10⁻³–10⁻⁴ error rates from single-step discrimination of 10⁻².

Streptomycin and aminoglycosides (Module 4) interfere with this proofreading, raising the error rate dramatically — the mechanistic basis of aminoglycoside lethality to bacteria.

Simulation: Kinetic Proofreading & Error Rate

Python

script.py47 lines

import numpy as np, matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt

# Ribosome fidelity: decoding vs proofreading
# Initial selection + proofreading
# Combined error probability ~ 1e-3 per codon

# Kinetic proofreading: cognate tRNA has low k_off, non-cognate has high k_off
# Two selection steps each amplify discrimination

k_off_cognate = 1
k_off_noncognate = 1000
k_chem = 10    # chemistry rate

# Branching probability = k_chem / (k_chem + k_off)
p_pass_cognate = k_chem / (k_chem + k_off_cognate)
p_pass_nc = k_chem / (k_chem + k_off_noncognate)

# Single step fidelity
single = p_pass_nc / p_pass_cognate
# Double step (initial + proofread): ratio squared
double = single**2

# Plot: accuracy as a function of number of selection steps
n_steps = np.arange(1, 5)
errors_single = single**n_steps

fig, ax = plt.subplots(figsize=(11, 6), facecolor='#0a0a1a')
ax.set_facecolor('#111827'); ax.tick_params(colors='#cbd5e1')
for s in ax.spines.values(): s.set_color('#334155')
ax.grid(True, color='#334155', alpha=0.3, which='both')

ax.semilogy(n_steps, errors_single, 'o-', color='#a78bfa', lw=2.6, markersize=12)
ax.axhline(1e-3, color='#fbbf24', ls='--', label='Observed ribosome error rate 1e-3')
ax.axhline(1e-6, color='#f87171', ls='--', label='DNA replication 1e-6')
ax.set_xlabel('Number of kinetic selection steps', color='#cbd5e1')
ax.set_ylabel('Error probability per codon', color='#cbd5e1')
ax.set_title('Kinetic proofreading: fidelity grows exponentially with steps',
             color='#c4b5fd', fontweight='bold')
ax.legend(facecolor='#1e293b', edgecolor='#334155', labelcolor='#cbd5e1')
ax.set_xticks(n_steps)

plt.tight_layout()
plt.savefig('output.png', dpi=120, bbox_inches='tight', facecolor='#0a0a1a')
print('Hopfield/Ninio kinetic proofreading: ribosome has initial selection + proofreading')
print('Ribosome ~1e-3 error rate; tolerable because errors are per-codon, not per-genome')

Click Run to execute the Python code

Code will be executed with Python 3 on the server

3. Peptidyl Transfer (the Ribozyme Reaction)

With A-site aa-tRNA and P-site peptidyl-tRNA in place, the α-amino group of the A-site amino acid attacks the ester carbonyl of the P-site peptidyl-tRNA. The transition state is tetrahedral; the P-site tRNA acts as the leaving group. Nuclear acceleration is ~10⁷ over uncatalysed reaction.

The catalytic machinery is entirely RNA. Steitz’s 2000 structure showed no protein side chain is within 18 Å of the attacking carbonyl; A2451 of the 23S rRNA is the key contact. Catalysis is achieved primarily by substrate positioning— holding the attacking amine and the ester oxygen in near-attack geometry — rather than by traditional enzymatic catalysis. The 2′-OH of the P-site tRNA A76 is also critical, contributing proton shuttling.

4. Translocation (EF-G)

After peptidyl transfer, the deacylated tRNA occupies the P site and the peptidyl-tRNA is in the A site. EF-G (eEF2 eukaryotic) · GTP binds; ratchet-like rotation of the 30S relative to the 50S is triggered; EF-G hydrolyses GTP; the mRNA and tRNAs move by one codon; tRNAs shift from A→P (peptidyl) and P→E (deacylated). The E-site tRNA then dissociates. One full cycle.

EF-G/eEF2 mimics tRNA in shape — the elongated domain IV of EF-G occupies the A-site after GTP hydrolysis, preventing premature aminoacyl-tRNA entry during translocation. Molecular mimicry is a recurring theme in ribosome factor biology.

5. Energy Budget & Rate

Per amino acid:

1 ATP for tRNA charging by aminoacyl-tRNA synthetase (ATP → AMP + PP_i, net 2 high-energy phosphate bonds).
1 GTP for EF-Tu delivery.
1 GTP for EF-G translocation.
Total: ~4 high-energy phosphate bonds per peptide bond, or ~120 kJ/mol.

An E. coli ribosome operates at 20 aa/s, or 20 peptide bonds per second per ribosome. At ~10⁴ ribosomes per cell and 4 GTP/ATP per bond, a growing bacterium spends ~10⁶ phosphate bonds per second on translation alone, approximately half its total ATP flux.

6. Regulatory Variation in Elongation Rate

Elongation rate is not uniform across a transcript. Codon optimality (tRNA abundance per codon), mRNA secondary structure, and nascent-chain interactions with the exit tunnel all modulate local elongation speed. Rare-codon regions slow the ribosome, and this controlled slowing can be exploited biologically — promoting proper folding of multi-domain proteins (pauses allow domain-by-domain folding) or regulating mRNA half-life via the NMD pathway. Stress-induced eEF2 phosphorylation (via eEF2K and p38/MK2 signalling) slows elongation under nutrient or oxidative stress.

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