The standard explanation for proton–electron separation at the entry point of the mitochondrial electron transport chain (ETC) invokes reduction potential: iron–sulfur clusters at Complex I possess a higher electrochemical affinity for electrons than NADH, and this differential drives the split. While operationally correct, this account is descriptive rather than mechanistic. It names the energetic gradient but does not explain why the electron moves through a protein structure while the proton cannot follow, nor does it specify the physical process by which the transition occurs. This paper proposes a three-mechanism framework — state transition, directed energy flow, and quantum tunnelling — that provides a more complete mechanistic account. The framework also offers a more precise formulation of the relationship between ETC congestion and reactive oxygen species (ROS) overproduction, replacing the imprecise notion of extended electron “dwell time” with the more accurate concept of increased tunnelling-event frequency per unit time.
The standard explanation for proton–electron separation at the entry point of the mitochondrial electron transport chain (ETC) invokes reduction potential: iron–sulfur clusters at Complex I possess a higher electrochemical affinity for electrons than NADH, and this differential drives the split. While operationally correct, this account is descriptive rather than mechanistic. It names the energetic gradient but does not explain why the electron moves through a protein structure while the proton cannot follow, nor does it specify the physical process by which the transition occurs. This paper proposes a three-mechanism framework — state transition, directed energy flow, and quantum tunnelling — that provides a more complete mechanistic account. The framework also offers a more precise formulation of the relationship between ETC congestion and reactive oxygen species (ROS) overproduction, replacing the imprecise notion of extended electron “dwell time” with the more accurate concept of increased tunnelling-event frequency per unit time.
Mitochondria are the major cellular organelles responsible for ATP production. They produce ATP through the process of oxidative phosphorylation, in which the proton motive force (pmf) is the driving force by which protons pass through ATPase. The pmf is generated by the pumping activity of the electron transport chain ETC, particularly complexes I, III, and IV. As the proton can be physically described as a quantum wave, it is important to explore the role of the quantum behavior in its transport through the ETC proteins, particularly the respiratory complex I. In the present study, the potential functions of three subunits of complex I were identified, and the Schrödinger equation was solved numerically by the finite difference method using MATLAB to obtain the eigenstates and their corresponding eigenvalues. In addition, quantum tunneling probability and quantum conductance values were calculated using WKB approximation for the eigenenergies of the proton in each potential barrier. Moreover, entropic tunneling delay time and tunneling currents were calculated. Our results indicate that quantum tunneling transport yields significant values of quantum conductance that can contribute significantly to the pmf while utilizing less than 45 % of the required energy to overcome the barriers of the subunits in respiratory complex I.
Intramolecular electron transport in biological systems is typically described as a diffusive hopping process, according to the semi-classical rate theories of Marcus and Hopfield combined with classical Pauli-type master equations. However, the possibility that non-trivial quantum mechanical effects could play a functional role in the transport dynamics in certain biomolecular processes has attracted increasing attention. Here, we extend the quantum mechanical model of open system dynamics by the Lindblad equation to a key biological component, the long chains of redox centers based on iron-sulfur clusters or heme groups that are widespread in many biological organisms, where they realize the cellular respiration. This approach allows to explore a wide range of physical parameters, showing key features of electron transport in these multi-domain protein structures. We pay particular attention to heat and entropy transfer between the electrons and the protein bath, which constitutes a benchmark of physical realism for the models. Electron currents, average transfer times and relative efficiency of the transport process are also explicitly characterized.
In traditional quantum mechanics, electron tunneling is described as a quantum penetration effect through a potential barrier. This paper proposes a new physical framework based on the Energy Gradient Model 2.0 (EGM 2.0), which reinterprets the tunneling phenomenon from the perspective of electron cloud deformation and energy gradient driving. Experiments show that when an external potential is applied to a stable electronic system, the electron cloud distribution is reconstructed without destroying the basic electronic structure. A clear energy threshold exists: below the threshold, only electron cloud deformation and spatial rearrangement occur, which corresponds to the tunneling effect; above the threshold, the original quantum state is destroyed, leading to quantum transition. The EGM 2.0 model unifies the mechanism of electron tunneling and quantum transition, providing a consistent classical-quantum physical explanation.
This paper proposes a classical alternative explanation for the tunneling effect in quantum mechanics. Standard quantum theory describes tunneling as a particle "penetrating" a potential barrier whose energy exceeds the particle's own kinetic energy with a certain probability. However, this explanation focuses only on the mathematical initial and final states, completely ignoring any dynamical process the electron may undergo before the barrier, and lacks a physical picture. This paper argues that tunneling is not an intrinsic quantum property of a single electron, but rather a collective statistical fluctuation event involving multiple electrons: electrons near the barrier, through a series of random collisions in the correct direction, gradually transfer and concentrate kinetic energy onto the electron closest to the barrier, enabling it to instantaneously acquire kinetic energy exceeding the barrier threshold and thus classically fly over the barrier. During the crossing, the electron must do work against the barrier, converting kinetic energy into potential energy; therefore, after crossing, its kinetic energy is reduced and it cannot cross the same barrier again. Tunneling probability is reinterpreted as the success probability of such a "directed energy relay" event. This model is fully self-consistent within the framework of classical electromagnetism and statistical mechanics, requiring no wave functions or probability waves, with a clear physical picture and explicit causal chain. This paper further points out that under strictly single-electron conditions, this model predicts that tunneling will completely disappear, a prediction that stands in fundamental opposition to the standard quantum model and can serve as a decisive experiment to test the two theories.
This work introduces a novel theoretical framework in which enzymatic tunnels are reinterpreted as quantum-fluid coherence channels rather than simple geometric pathways. Guided by π-field hydrodynamics, these tunnels support coherent, directed energy transport at the nanoscale, providing a unified explanation for ultrafast proton movement, long-range communication between protein sites, low-dissipation energy flow, and the remarkable sensitivity of catalytic efficiency to single-point mutations. In this article, I develop a quantum-hydrodynamic model incorporating coherence density, phase-field dynamics, and the π-induced quantum potential 𝑄𝜋. The resulting framework predicts: ballistic-like transport within enzymatic tunnels, π-gradient–driven directionality, coherence-supported reduction of effective energy barriers, mutation-induced π-defects disrupting transport, and the emergence of nanoscale quantum-fluid vortices. To the best of my knowledge, this is the first scientific work to formally characterize enzymatic tunnels as quantum-fluid conduits governed by π-field dynamics. This establishes a new research direction at the intersection of quantum biology, enzymology, and nanophysical modeling, which I refer to as Quantum Fluid Enzymology (QFE). The deposition includes conceptual figures, theoretical equations, and a computational π-fluid simulation approach for tunnel transport
Abstract This study introduces a geometric framework to explain how quantum particles, specifically protons, move through energy barriers in biological molecules like DNA. Rather than viewing this tunneling as a purely random event, we propose that it is governed by the structural complexity of the surrounding molecular environment. By treating the energy landscape as a geometric shape, we demonstrate that the environment acts as a regulator that either facilitates or hinders the movement of protons between genetic base pairs. We applied this model to compare the two primary building blocks of the DNA ladder: the Guanine-Cytosine (G-C) and Adenine-Thymine (A-T) pairs. Our findings reveal that the G-C pair possesses a structural configuration that makes proton movement significantly more likely compared to the A-T pair. This difference provides a clear physical explanation for why certain parts of our genetic code are more prone to spontaneous changes, or tautomeric shifts, which can lead to mutations. Furthermore, the research explores how the DNA molecule interacts with its surrounding cellular noise (e.g. water molecules and proteins). We find that the proton behaves in a hybrid manner (at times acting like a coherent wave that exists in multiple places at once), and at other times like a solid particle trapped by its environment. This dual behavior suggests that life operates at a delicate balance between quantum mechanical effects and classical stability.