Part 2 · Chapter 2.3

The Electron Transport Chain

Four membrane complexes plus two mobile carriers move electrons from NADH/FADH₂ to molecular oxygen, releasing 220 kJ/mol per pair. The released free energy is captured as a proton gradient across the inner mitochondrial membrane—the proton-motive force that drives ATP synthesis.

Learning Objectives

▸Trace electrons from NADH through Complexes I–IV to O₂
▸State Mitchell’s chemiosmotic hypothesis and the proton-motive force equation
▸Explain the Q-cycle and how it doubles H⁺ translocation per electron pair
▸Derive P/O ratios from proton stoichiometry and ATP synthase efficiency
▸Identify classical inhibitors and uncouplers and their pharmacology

◆Mitchell’s Chemiosmotic Hypothesis

In 1961 Peter Mitchell proposed—against entrenched opinion—that oxidative phosphorylation is driven by an electrochemical proton gradient across the inner mitochondrial membrane rather than by a chemical high-energy intermediate. The gradient has two components: the membrane potential \(\Delta\psi\) (positive outside) and the pH difference \(\Delta\text{pH}\) (acidic outside). Mitchell received the Nobel Prize in Chemistry in 1978.

\[ \Delta p \;=\; \Delta\psi \;-\; \frac{2.303\,RT}{F}\,\Delta\text{pH} \;\approx\; \Delta\psi - 59\,\Delta\text{pH}\;\;\text{(mV, 37}^\circ\text{C)} \]

In respiring mitochondria \(\Delta\psi \approx 160\text{-}180\) mV and \(\Delta\text{pH} \approx 0.5\) (matrix alkaline by ~0.5 pH units), giving \(\Delta p \approx 200\) mV. The energy stored per proton is \(\Delta G_{H^+} = F\,\Delta p \approx 19\) kJ/mol. The free energy available to drive ATP synthesis is thus \(n\,F\,\Delta p\), where \(n\) is the number of protons translocated per ATP (typically 8/3 or ~2.67 in mammals, more detail in Chapter 2.4).

◆Architecture of the ETC

◆Complex I: NADH:Ubiquinone Oxidoreductase

An L-shaped 45-subunit, ~1 MDa machine. One arm lies in the matrix, the other embedded in the membrane. Electrons enter via FMN (flavin mononucleotide), which accepts a hydride from NADH. Seven or eight iron–sulfur clusters relay the electrons over ~100 \(\text{\AA}\) to a terminal cluster (N2), which reduces ubiquinone.

\[ \text{NADH} + \text{Q} + 5\,\text{H}^+_{\text{matrix}} \longrightarrow \text{NAD}^+ + \text{QH}_2 + 4\,\text{H}^+_{\text{IMS}} \]

Reduction of Q in the Q-cycle chamber drives conformational changes in the membrane arm that push 4 H⁺ across the membrane per two electrons—indirect coupling via long-range conformational transmission (no direct thermodynamic coupling to chemistry at the active site). Blocked by rotenone, piericidin A, and the Parkinson’s-inducing toxin MPP⁺.

◆Complex II: Succinate:Ubiquinone Oxidoreductase

Identical to succinate dehydrogenase of the TCA cycle. Uniquely embedded in the inner membrane, feeds electrons from FADH₂ into the Q pool but pumps no protons—the redox drop across Complex II (\(E^{\circ\prime}\) of succinate/fumarate 0.03 V and of Q/QH\(_2\) 0.045 V) is too small to energize pumping. FADH₂-linked substrates consequently yield fewer ATP (P/O ≈ 1.5) than NADH-linked ones (P/O ≈ 2.5).

\[ \text{Succinate} + \text{Q} \longrightarrow \text{Fumarate} + \text{QH}_2 \]

◆Complex III: Cytochrome bc₁ and the Q-Cycle

Complex III oxidizes QH₂ and reduces cytochrome c. But one QH₂ carries 2 electrons while cytochrome c accepts only 1—so the enzyme bifurcates electrons via the Q-cycle, elegantly pumping 4 H⁺ across the membrane for every 2 electrons transferred.

Q-Cycle Round 1

QH₂ docks at the Qᵢ site (IMS side). Releases 2 H⁺ to IMS. One electron goes via Rieske [2Fe–2S] → cyt c₁ → cyt c. The other electron traverses cyt b₅₆₆ → cyt b₅₆₂ to the Qₒ site (matrix side), where it produces a semiquinone (SQ).

Q-Cycle Round 2

A second QH₂ at Qᵢ repeats the process; the semiquinone now accepts the second electron and 2 H⁺ from the matrix, regenerating QH₂. Net result:
2 QH₂ + 2 cyt c₊₃ + 2 H⁺ₙₐₜ → Q + QH₂ + 2 cyt c₊₂ + 4 H⁺ᵤₓ.

Blocked by antimycin A (Qₒ site) and myxothiazol (Qᵢ site). Loss-of-function mutations cause paragangliomas. The Q-cycle is one of the most beautiful examples of molecular vectoriality in biology.

◆Complex IV: Cytochrome c Oxidase

A multimetallic ~230 kDa enzyme containing two hemes (a and a₃) and two copper centers (Cuₐ, Cuᵇ). It collects 4 electrons one at a time from cytochrome c and reduces O₂ to 2 H₂O—the most thermodynamically critical step of aerobic respiration. A binuclear heme a₃–Cuᵇ active site binds O₂ and stabilizes peroxide and ferryl intermediates, avoiding release of reactive oxygen species.

\[ 4\,\text{cyt}\,c_{\text{red}} + \text{O}_2 + 8\,\text{H}^+_{\text{mat}} \longrightarrow 4\,\text{cyt}\,c_{\text{ox}} + 2\,\text{H}_2\text{O} + 4\,\text{H}^+_{\text{IMS}} \]

For every 4 electrons (1 O₂), 4 H⁺ are used for chemistry (combining with O₂) and 4 H⁺ are pumped to the IMS. Inhibited by cyanide (CN⁻), azide, carbon monoxide, and H₂S, all of which bind to the heme a₃-Cuᵇsite. Cytochrome c, the mobile carrier between III and IV, is also a classic apoptosis-triggering molecule when released into the cytosol.

◆Simulation 1: Proton-Motive Force Buildup

Two-compartment model of a mitochondrion: ETC pumping, passive leak, ATP synthase consumption, and a chemical uncoupler pulse (like DNP) dropping the gradient. Tracks \(\Delta\psi\), \(\Delta\text{pH}\), and total \(\Delta p\) over 60 s.

Python

script.py152 lines

import numpy as np
import matplotlib.pyplot as plt

# Build-up of the proton-motive force during ETC activity
# Simple 2-compartment model:
#   pumps: Complex I (4 H+/NADH), III (4 H+/NADH via Q-cycle), IV (2 H+/NADH)
#   leak: passive proton re-entry through the inner membrane
#   ATP synthase: consumes protons

# Model parameters
F = 96485.0    # C/mol
R = 8.314      # J/mol/K
T = 310.0      # K
V_matrix = 1.0e-15   # L (mitochondrial matrix volume)
V_ims    = 0.2e-15   # L (intermembrane space)
C_m      = 1.0e-11   # F  (membrane capacitance; approximate)

# Initial state
t_max = 60.0
dt = 0.002
N = int(t_max/dt)
t = np.linspace(0, t_max, N)

# Protons in IMS (high) and matrix (low)
pH_matrix_init = 7.8
pH_ims_init    = 7.8   # start equilibrated (no PMF)
H_matrix = np.zeros(N); H_ims = np.zeros(N)
H_matrix[0] = 10**(-pH_matrix_init) * V_matrix * 6.022e23
H_ims[0]    = 10**(-pH_ims_init)    * V_ims    * 6.022e23
V_mem = np.zeros(N)  # mV; positive outside (IMS positive)

# Pumping rate (protons/s) - switched on at t = 5 s
k_I   = 2.0e6  # Complex I per NADH oxidized; here interpreted as total pump rate
k_III = 2.0e6
k_IV  = 1.0e6
k_leak = 5e4   # voltage-dependent leak
k_atp  = 0.0   # ATP synthase initially off

for i in range(1, N):
    ti = t[i]
    # Turn on ETC at 5 s, ATP synthase at 25 s, add uncoupler pulse at 45 s
    etc_on = 1.0 if ti > 5.0 else 0.0
    atp_on = 1.0 if ti > 25.0 else 0.0
    uncoupler = 5.0 if 45 < ti < 50 else 1.0

# Leak proportional to PMF (simplified)
    V = V_mem[i-1]
    delta_pH = -np.log10(H_ims[i-1]/V_ims/(H_matrix[i-1]/V_matrix)+1e-30)
    pmf = V - 59*delta_pH   # mV (Mitchell convention, neg sign outside)

j_pump = etc_on * (k_I + k_III + k_IV)
    j_leak = k_leak * uncoupler * (V/50.0 if V > 0 else 0)
    j_atp  = atp_on * 4e5 * (V/80.0 if V > 30 else 0)   # 4H+/ATP through F0

# Update proton counts
    dH = (j_pump - j_leak - j_atp) * dt
    H_matrix[i] = max(H_matrix[i-1] - dH, 1e6)
    H_ims[i]    = H_ims[i-1]    + dH

# Membrane potential: capacitive accumulation of charge
    q = (j_pump - j_leak - j_atp) * dt * 1.6e-19
    V_mem[i] = V_mem[i-1] + q/C_m * 1000   # mV
    V_mem[i] = min(V_mem[i], 180)  # cap

pH_m = -np.log10(H_matrix/V_matrix/6.022e23)
pH_i = -np.log10(H_ims/V_ims/6.022e23)
delta_pH = pH_m - pH_i
pmf = V_mem - 59.0*delta_pH  # RT/F*ln10 ~ 59 mV at 37 C

fig, axes = plt.subplots(2, 2, figsize=(14, 9))

ax = axes[0,0]
ax.plot(t, V_mem, color='#fbbf24', lw=2.3, label='\u0394\u03C8 (mV)')
ax.axvspan(5, 25, alpha=0.1, color='#67e8f9', label='ETC only')
ax.axvspan(25, 45, alpha=0.15, color='#86efac', label='ETC + ATP synth.')
ax.axvspan(45, 50, alpha=0.2, color='#f87171', label='Uncoupler (DNP)')
ax.set_xlabel('Time (s)', color='white'); ax.set_ylabel('\u0394\u03C8 (mV)', color='white')
ax.set_title('Electrochemical potential buildup',
             color='white', fontsize=12, fontweight='bold')
ax.legend(facecolor='#0a0a1a', edgecolor='#fbbf24', labelcolor='white')
ax.set_facecolor('#0a0a1a'); ax.tick_params(colors='white')
ax.grid(alpha=0.2, color='#fbbf24')
for s in ax.spines.values(): s.set_color('#fbbf24')

ax = axes[0,1]
ax.plot(t, pH_m, color='#86efac', lw=2, label='pH matrix')
ax.plot(t, pH_i, color='#f87171', lw=2, label='pH IMS')
ax.set_xlabel('Time (s)', color='white'); ax.set_ylabel('pH', color='white')
ax.set_title('pH gradient \u0394pH = pH(matrix) \u2212 pH(IMS)',
             color='white', fontsize=12, fontweight='bold')
ax.legend(facecolor='#0a0a1a', edgecolor='#86efac', labelcolor='white')
ax.set_facecolor('#0a0a1a'); ax.tick_params(colors='white')
ax.grid(alpha=0.2, color='#86efac')
for s in ax.spines.values(): s.set_color('#86efac')

ax = axes[1,0]
ax.plot(t, pmf, color='#60a5fa', lw=2.5)
ax.axhline(y=200, color='white', ls=':', alpha=0.4, label='Physiological PMF')
ax.set_xlabel('Time (s)', color='white'); ax.set_ylabel('PMF \u0394p (mV)', color='white')
ax.set_title('Total proton-motive force \u0394p = \u0394\u03C8 \u2212 (RT/F)\u0394pH',
             color='white', fontsize=12, fontweight='bold')
ax.legend(facecolor='#0a0a1a', edgecolor='#60a5fa', labelcolor='white')
ax.set_facecolor('#0a0a1a'); ax.tick_params(colors='white')
ax.grid(alpha=0.2, color='#60a5fa')
for s in ax.spines.values(): s.set_color('#60a5fa')

# P/O ratio diagnostic for NADH- and FADH2-linked substrates
ax = axes[1,1]
cats = ['NADH\n(Complex I)', 'FADH2\n(Complex II)']
po = [2.5, 1.5]
h_per = [10, 6]
colors_b = ['#67e8f9', '#fbbf24']
x = np.arange(len(cats))
w = 0.35
ax.bar(x-w/2, po, w, color=colors_b, label='P/O ratio (ATP/\u00BD O2)')
ax.bar(x+w/2, [h/4 for h in h_per], w, color='#a78bfa', alpha=0.7,
       label='H+ pumped/e-pair (\u00F74)')
ax.set_xticks(x); ax.set_xticklabels(cats, color='white')
ax.set_ylabel('Value', color='white')
ax.set_title('P/O ratios per reducing equivalent',
             color='white', fontsize=12, fontweight='bold')
ax.legend(facecolor='#0a0a1a', edgecolor='#67e8f9', labelcolor='white')
ax.set_facecolor('#0a0a1a'); ax.tick_params(colors='white')
ax.grid(alpha=0.2, color='#67e8f9', axis='y')
for s in ax.spines.values(): s.set_color('#67e8f9')
for i,v in enumerate(po):
    ax.text(x[i]-w/2, v+0.05, f'{v}', ha='center', color='white', fontweight='bold')
for i,v in enumerate(h_per):
    ax.text(x[i]+w/2, v/4+0.05, f'{v}H+', ha='center', color='white', fontweight='bold')

fig.suptitle('Electron transport chain: PMF build-up & energy coupling',
             color='white', fontsize=15, fontweight='bold')
fig.patch.set_facecolor('#0a0a1a')
plt.tight_layout()
plt.savefig('output.png', dpi=120, bbox_inches='tight', facecolor='#0a0a1a')

# Integrated work done by PMF over the steady-state window
ss = (t > 30) & (t < 45)
work = np.trapezoid(pmf[ss], t[ss])
print(f"Steady-state PMF = {pmf[ss].mean():.1f} mV (\u0394\u03C8 = {V_mem[ss].mean():.1f} mV,"
      f" \u0394pH = {delta_pH[ss].mean():.2f})")
print(f"Integrated PMF work over 15 s SS = {work:.1f} mV\u00B7s")
print()
print("Mitchell (1961) chemiosmotic hypothesis:")
print("  Electron transport pumps protons, creating electrochemical gradient.")
print("  ATP synthase harnesses proton backflow to make ATP.")
print()
print("P/O ratios (ATP per 1/2 O2 consumed):")
print("  NADH-linked substrate: ~2.5 (10 H+ pumped / 4 H+ per ATP)")
print("  FADH2-linked substrate: ~1.5 (6  H+ pumped / 4 H+ per ATP)")

Click Run to execute the Python code

Code will be executed with Python 3 on the server

◆Simulation 2: Redox Ladder and Free Energy Cascade

Each carrier has a standard redox potential \(E^{\circ\prime}\). Electrons flow thermodynamically downhill, with \(\Delta G^{\circ\prime} = -nF\Delta E^{\circ\prime}\). This code plots the cascade and annotates the three proton-pumping sites.

Python

script.py86 lines

import numpy as np
import matplotlib.pyplot as plt

# Redox potentials (V) of ETC components at pH 7
components = [
    ('NADH/NAD+',        -0.320, 'start'),
    ('FMN',              -0.300, 'I'),
    ('Fe-S (N1a)',       -0.370, 'I'),
    ('Fe-S (N2)',        -0.150, 'I'),
    ('Q/QH2',             0.045, 'Q-pool'),
    ('Cyt b562',          0.030, 'III'),
    ('Cyt b566',         -0.100, 'III'),
    ('Cyt c1',            0.215, 'III'),
    ('Cyt c',             0.235, 'carrier'),
    ('Cyt a',             0.210, 'IV'),
    ('Cyt a3/CuB',        0.380, 'IV'),
    ('1/2 O2 \u2192 H2O',  0.816, 'end'),
]
names = [c[0] for c in components]
Es    = np.array([c[1] for c in components])
groups = [c[2] for c in components]
color_map = {'start':'#f87171','I':'#67e8f9','Q-pool':'#fde047',
             'III':'#c084fc','carrier':'#a78bfa','IV':'#fbbf24','end':'#86efac'}
colors = [color_map[g] for g in groups]

fig, axes = plt.subplots(1, 2, figsize=(15, 6))

# Left: redox ladder
ax = axes[0]
y = np.arange(len(names))[::-1]
ax.hlines(y, xmin=-0.4, xmax=0.9, color='#444', lw=0.5, alpha=0.4)
ax.scatter(Es, y, s=180, c=colors, edgecolors='white', linewidths=1.5, zorder=3)
for yi, n, E in zip(y, names, Es):
    ax.text(E+0.02, yi, f'{n}  (E\u00B0\u02B9 = {E:+.2f} V)',
            color='white', fontsize=10, va='center')
# Draw transfer arrows
for i in range(len(Es)-1):
    ax.annotate('', xy=(Es[i+1], y[i+1]), xytext=(Es[i], y[i]),
                arrowprops=dict(arrowstyle='->', color='#67e8f9', lw=1.5, alpha=0.6))
ax.set_yticks([])
ax.set_xlabel("Standard redox potential E\u00B0\u02B9 (V)", color='white')
ax.set_title('Redox Ladder of the Electron Transport Chain',
             color='white', fontsize=13, fontweight='bold')
ax.set_facecolor('#0a0a1a'); ax.tick_params(colors='white')
ax.grid(alpha=0.2, color='#67e8f9', axis='x')
for s in ax.spines.values(): s.set_color('#67e8f9')

# Right: free energy drop
F = 96485  # C/mol
dE_steps = np.diff(Es)          # V per step
dG_steps = -2 * F * dE_steps / 1000  # kJ/mol (assuming 2e- per step)
cum_dG = np.concatenate(([0], np.cumsum(dG_steps)))

ax = axes[1]
ax.plot(range(len(names)), cum_dG, 'o-', color='#fbbf24', lw=2.5, markersize=8)
ax.fill_between(range(len(names)), cum_dG, 0, color='#fbbf24', alpha=0.15)
# Mark proton-pumping sites
ax.axvspan(0.5, 3.5, alpha=0.12, color='#67e8f9', label='Complex I (4H+)')
ax.axvspan(4.5, 7.5, alpha=0.12, color='#c084fc', label='Complex III (4H+)')
ax.axvspan(8.5, 10.5, alpha=0.12, color='#86efac', label='Complex IV (2H+)')
ax.set_xticks(range(len(names)))
ax.set_xticklabels([n.split(' ')[0] for n in names], rotation=45, ha='right',
                   color='white', fontsize=8)
ax.set_ylabel('Cumulative \u0394G (kJ/mol, 2e\u207B basis)', color='white')
ax.set_title('Free Energy Cascade NADH \u2192 O\u2082',
             color='white', fontsize=13, fontweight='bold')
ax.axhline(y=0, color='white', lw=0.5)
ax.legend(facecolor='#0a0a1a', edgecolor='#fbbf24', labelcolor='white')
ax.set_facecolor('#0a0a1a'); ax.tick_params(colors='white')
ax.grid(alpha=0.2, color='#fbbf24')
for s in ax.spines.values(): s.set_color('#fbbf24')

fig.patch.set_facecolor('#0a0a1a')
plt.tight_layout()
plt.savefig('output.png', dpi=120, bbox_inches='tight', facecolor='#0a0a1a')

total_dE = Es[-1]-Es[0]
total_dG = -2*F*total_dE/1000
print(f"Total redox drop: \u0394E\u00B0\u02B9 = {total_dE:.3f} V ({Es[0]:+.3f} \u2192 {Es[-1]:+.3f} V)")
print(f"Free energy released per 2 electrons (= per NADH): \u0394G\u00B0\u02B9 = {total_dG:.1f} kJ/mol")
print()
print(f"Energy partitioned to H+ pumping:")
print(f"  10 H+ per NADH \u00D7 ~20 kJ/mol per H+ = ~200 kJ/mol captured in PMF")
print(f"  Efficiency ~= {200/abs(total_dG)*100:.0f}% of redox free energy stored as PMF")

Click Run to execute the Python code

Code will be executed with Python 3 on the server

◆Inhibitors and Uncouplers

Complex I

Rotenone (pesticide), piericidin A, MPP⁺ (Parkinson toxin), metformin (weak)

Complex III

Antimycin A (Qₒ site), myxothiazol (Qᵢ site), atovaquone (anti-malarial)

Complex IV

Cyanide (CN⁻), carbon monoxide (CO), azide (N₃⁻), hydrogen sulfide (H₂S)

Uncouplers

2,4-dinitrophenol (DNP, weight-loss drug, fatal), FCCP, UCP1 in brown adipose tissue (non-shivering thermogenesis)

◆The Electron Carriers: Redox Chemistry

Three classes of cofactors move electrons through the ETC:

Flavins (FMN, FAD)

Can accept 1 or 2 electrons through a semiquinone intermediate. Bridge between 2-electron donors (NADH, succinate) and 1-electron carriers (Fe-S clusters, cytochromes).

Iron-sulfur clusters

[2Fe–2S] and [4Fe–4S] clusters ligated by cysteine residues. One-electron carriers; tune their midpoint potentials by local protein environment. Complex I has 8 Fe-S clusters; Rieske [2Fe–2S] in Complex III is distinctive (two His + two Cys).

Cytochromes (hemes)

Protein-bound iron-porphyrin prosthetic groups. Types a, b, c (and o, d in bacteria) differ by side chains. Cytochrome c is water-soluble (IMS); others are membrane-embedded. All are 1-electron carriers.

◆Ubiquinone (Coenzyme Q) and the Q-Pool

Ubiquinone (CoQ, Q, Q₁₀ in humans) is a hydrophobic quinone with a 50-carbon (10 isoprenoid) tail. It diffuses freely within the inner membrane and can carry 1 or 2 electrons via semiquinone (Q\(^{-\bullet}\)) or full reduction (QH₂). Its pool size (≈10 mM in the membrane) is sufficient for thousands of turnovers per second per complex. Q is the only electron carrier that is not protein-bound—this mobility is crucial for collecting electrons from Complexes I, II, and alternative sources (e.g., glycerol-3-P shuttle) and delivering them to Complex III.

CoQ supplementation is used clinically in some mitochondrial diseases and statin-induced myopathy (statins inhibit HMG-CoA reductase, reducing isoprenoid synthesis and CoQ levels).

◆Reactive Oxygen Species: Leaks in the Chain

About 0.1–1% of all electrons flowing through the ETC escape to directly reduce molecular oxygen, forming superoxide (O₂⁻•). The major production sites are Complex I (at its flavin and Q-binding site, especially under reverse electron flow) and Complex III (during the brief semiquinone at the Qₒ site). Superoxide is quickly dismutated by matrix Mn-SOD (SOD2) or cytosolic Cu/Zn-SOD (SOD1) into H₂O₂, which is reduced to water by catalase, glutathione peroxidases, or peroxiredoxins.

\[ \text{O}_2 + e^- \longrightarrow \text{O}_2^{-\cdot}\quad \xrightarrow{\text{SOD}}\quad \text{H}_2\text{O}_2\quad \xrightarrow{\text{catalase/GPx}}\quad \text{H}_2\text{O} \]

At low levels ROS are signaling molecules: mtROS from Complex III regulate HIF-1\(\alpha\), innate immune responses (inflammasome), and hypoxia adaptation. At high levels (e.g., reperfusion injury, hyperglycemia, mitochondrial uncoupling) ROS damage lipids (peroxidation), proteins (carbonylation, 3-nitrotyrosine), and DNA (8-oxoguanine), contributing to aging, neurodegeneration, and cancer.

◆Respiratory Supercomplexes

Classical biochemistry taught that Complexes I, III, and IV diffuse independently in the inner membrane, connected only by mobile Q and cytochrome c. Cryo-EM data of the last decade have revealed that in most tissues they assemble into supercomplexes (respirasomes): stoichiometrically defined I₁III₂IV₁ and larger oligomers. These higher-order assemblies are proposed to enhance efficiency by channeling electrons (reducing diffusion time), minimizing ROS production, and stabilizing individual complexes. The SCAFI/SCAF1 protein mediates much of this organization.

◆Shuttles for Cytosolic NADH

Because the inner membrane is impermeable to NADH itself, cytosolic NADH (produced by glycolytic GAPDH) must be “shuttled” across to reach the ETC. Two mechanisms dominate:

Malate-Aspartate Shuttle (heart, liver)

NADH → OAA → malate (by cytosolic MDH); malate crosses into matrix; matrix MDH regenerates NADH + OAA. OAA is transaminated to aspartate for return. Net: cytosolic NADH equivalent to matrix NADH → ~2.5 ATP per NADH.

Glycerol-3-P Shuttle (muscle, brain)

NADH reduces DHAP to glycerol-3-P (cytosolic); glycerol-3-P is re-oxidized at the outer face of the inner membrane by a FAD-linked enzyme, delivering electrons as FADH₂ directly to the Q pool. Net: only ~1.5 ATP per NADH, but faster and not limited by mitochondrial solute import.

Clinical Relevance

Leber Hereditary Optic Neuropathy

Complex I mutations (mtDNA) cause optic nerve degeneration due to chronic ATP deficit and oxidative stress.

Cyanide Poisoning

Inhibits Complex IV; cells cannot use O₂ despite adequate delivery. Treatment: hydroxocobalamin, nitrites (form methemoglobin-CN).

Brown Adipose Thermogenesis

UCP1 dissipates PMF as heat without ATP synthesis. Key for newborn warmth, hibernation, cold adaptation.

Reperfusion Injury

Succinate accumulates during ischemia; reperfusion drives reverse electron flow at Complex I, generating superoxide and damaging tissue.

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