• Published on bioRxiv, presenting a biophysical hypothesis that models triosephosphate isomerase (TIM), an enzyme essential for cellular glucose metabolism, as a quantum logic gate. • Predicted through a quantum mechanical model that SGLT2 inhibitors (SGLT2i), a diabetes treatment, reduce the probability of quantum decoherence in the TIM enzyme reaction. • Pioneering a new research frontier of quantum pharmacology by preventing the production of methylglyoxal, a cytotoxic byproduct, through the suppression of decoherence. [Quantum Biology Society] Groundbreaking biophysical research has been published revealing that an enzyme essential for cellular glucose metabolism (glycolysis) virtually operates like a quantum logic gate, the computational unit of a quantum computer. Going beyond classical biochemistry, this is a milestone achievement interpreting the human protective mechanisms of metabolic disease treatments from the perspective of subatomic quantum information processing. A paper titled "Triosephosphate Isomerase as a Quantum Logic Gate: Could quantum decoherence be toxic?" was released on the preprint repository bioRxiv. A joint research team of Daniele Romanello, a physician in Internal Medicine at Ospedale San Pietro Fatebenefratelli in Rome, Italy, and Andrea Romanello from the Department of Information Engineering at Sapienza University of Rome proposed this innovative quantum medical model. ■ Enzyme Catalysis Interpreted as Quantum Computation The researchers focused on the catalytic process of triosephosphate isomerase (TIM), a key enzyme in glycolysis, converting dihydroxyacetone phosphate (DHAP) to glyceraldehyde-3-phosphate (G3P). Instead of viewing this process merely as a classical "lock-and-key" model where specific molecular structures fit together, they remodeled it as a highly advanced quantum computational workflow involving precise proton transfer. This implies that enzymes in vivo act as logic circuits that autonomously control quantum states to derive specific biochemical outcomes. ■ SGLT2 Inhibitors Protect Cells by Preventing Quantum Decoherence What is even more interesting is that this quantum model interpreted the hidden human protective effects of sodium-glucose co-transporter 2 inhibitors (SGLT2i), which are widely prescribed as treatments for heart failure and diabetes. According to the model's predictions, if quantum decoherence occurs—where the enzyme loses its quantum state due to interference from the external environment during the metabolic process—it produces methylglyoxal, a toxic byproduct that destroys cells and strongly accelerates aging. As a result of the researchers' analysis, SGLT2i drugs were found to significantly reduce the probability of quantum decoherence in this TIM enzyme reaction. In other words, by suppressing the noise in the intracellular quantum computation process, the drug dramatically lowers the accumulation of the highly toxic substance methylglyoxal, ultimately exerting a powerful organ-protective effect. ■ The Prelude to the Era of Quantum Pharmacology This study holds great significance in that it reinterprets the pathogenesis of diseases and the mechanism of drug action beyond molecular chemical bonds, from the perspective of quantum coherence and dynamics. Experts anticipate that this approach will serve as an excellent starting point for quantum pharmacology, bringing a fundamental paradigm shift to the design of next-generation drugs for treating metabolic syndrome and degenerative diseases.
• Published on bioRxiv, presenting a biophysical hypothesis that models triosephosphate isomerase (TIM), an enzyme essential for cellular glucose metabolism, as a quantum logic gate. • Predicted through a quantum mechanical model that SGLT2 inhibitors (SGLT2i), a diabetes treatment, reduce the probability of quantum decoherence in the TIM enzyme reaction. • Pioneering a new research frontier of quantum pharmacology by preventing the production of methylglyoxal, a cytotoxic byproduct, through the suppression of decoherence. [Quantum Biology Society] Groundbreaking biophysical research has been published revealing that an enzyme essential for cellular glucose metabolism (glycolysis) virtually operates like a quantum logic gate, the computational unit of a quantum computer. Going beyond classical biochemistry, this is a milestone achievement interpreting the human protective mechanisms of metabolic disease treatments from the perspective of subatomic quantum information processing. A paper titled "Triosephosphate Isomerase as a Quantum Logic Gate: Could quantum decoherence be toxic?" was released on the preprint repository bioRxiv. A joint research team of Daniele Romanello, a physician in Internal Medicine at Ospedale San Pietro Fatebenefratelli in Rome, Italy, and Andrea Romanello from the Department of Information Engineering at Sapienza University of Rome proposed this innovative quantum medical model. ■ Enzyme Catalysis Interpreted as Quantum Computation The researchers focused on the catalytic process of triosephosphate isomerase (TIM), a key enzyme in glycolysis, converting dihydroxyacetone phosphate (DHAP) to glyceraldehyde-3-phosphate (G3P). Instead of viewing this process merely as a classical "lock-and-key" model where specific molecular structures fit together, they remodeled it as a highly advanced quantum computational workflow involving precise proton transfer. This implies that enzymes in vivo act as logic circuits that autonomously control quantum states to derive specific biochemical outcomes. ■ SGLT2 Inhibitors Protect Cells by Preventing Quantum Decoherence What is even more interesting is that this quantum model interpreted the hidden human protective effects of sodium-glucose co-transporter 2 inhibitors (SGLT2i), which are widely prescribed as treatments for heart failure and diabetes. According to the model's predictions, if quantum decoherence occurs—where the enzyme loses its quantum state due to interference from the external environment during the metabolic process—it produces methylglyoxal, a toxic byproduct that destroys cells and strongly accelerates aging. As a result of the researchers' analysis, SGLT2i drugs were found to significantly reduce the probability of quantum decoherence in this TIM enzyme reaction. In other words, by suppressing the noise in the intracellular quantum computation process, the drug dramatically lowers the accumulation of the highly toxic substance methylglyoxal, ultimately exerting a powerful organ-protective effect. ■ The Prelude to the Era of Quantum Pharmacology This study holds great significance in that it reinterprets the pathogenesis of diseases and the mechanism of drug action beyond molecular chemical bonds, from the perspective of quantum coherence and dynamics. Experts anticipate that this approach will serve as an excellent starting point for quantum pharmacology, bringing a fundamental paradigm shift to the design of next-generation drugs for treating metabolic syndrome and degenerative diseases.
• Raised the hypothesis that 'TIM', a pivotal enzyme in cellular glycolysis, functions as a 'quantum logic gate' beyond a simple chemical catalyst. • Elucidated that upon the occurrence of quantum decoherence, methylglyoxal, a toxic substance causing diabetic complications, is produced. • Reinterpreted the root cause of metabolic diseases as a 'failure of quantum interference', and demonstrated the protective effects of SGLT2 inhibitors through a quantum model. [Quantum Biology Society] Groundbreaking research results have emerged suggesting that metabolic enzymes, which generate energy in our bodies, operate not merely as simple chemicals, but like 'quantum logic gates', the computational units of quantum computers. Recently, a paper titled "Triosephosphate Isomerase as a Quantum Logic Gate: Could quantum decoherence be toxic?" was published on bioRxiv, a preprint repository for biology. This study is drawing extraordinary attention from the medical community by reinterpreting the pathogenesis of diseases from a quantum mechanical perspective, going beyond classical biochemistry. ■ A Key Enzyme in Life Phenomena Operates as a 'Quantum Logic Gate' The research team focused on the operational mechanism of 'triosephosphate isomerase (TIM)', a pivotal enzyme in cellular glycolysis that breaks down glucose into energy. The researchers modeled the precise proton transfer process occurring within the enzyme as a 'quantum tunneling' action rather than a simple chemical catalytic reaction. This is an unconventional hypothesis that the TIM enzyme functions like a 'quantum logic gate', the fundamental unit of a quantum computer, to control the conversion of substances with extreme precision. ■ Quantum Errors (Decoherence) Create 'Toxicity' The most surprising discovery is what happens when inefficiencies arise due to the so-called 'quantum decoherence' phenomenon during this quantum tunneling process. The study showed that when an error occurs in the computation (catalysis) as the quantum state breaks down, a fatal toxic byproduct called 'methylglyoxal' is produced instead of normal metabolites, inducing the formation of advanced glycation end products (AGEs) that cause diabetic complications. In other words, a 'quantum mechanical malfunction' (failure of quantum tunneling) of metabolic enzymes in cells can be the direct cause of metabolic disease complications. ■ The Efficacy of the Diabetes Drug 'SGLT2 Inhibitors' Proven by a Quantum Model... A New Paradigm in Drug Development Furthermore, the research team developed a mathematical quantum model of how 'SGLT2 inhibitors', a widely used diabetes treatment, protect the body. As a result of simulation analysis through a Python script, it was confirmed that this drug exerts a protective effect on vascular and renal cells by lowering the probability of the formation of the toxic intermediate (methylglyoxal). This approach is highly significant in that it reinterpreted the root cause of metabolic diseases, including diabetes, as a problem at the level of 'quantum interference' rather than a simple chemical imbalance. This research, which identified the causes of diseases from a quantum mechanical perspective and theoretically proved the efficacy of drugs, is expected to provide a strong foundation for the development of new metabolic disease drugs with novel mechanisms that fundamentally block the generation of toxic byproducts in the future.
Abstract This study presents the hypothesis that triosephosphate isomerase (TIM), a pivotal enzyme in glycolysis, functions as a quantum logic gate. Utilizing quantum mechanics, we model TIM’s catalytic conversion of dihydroxyacetone phosphate (DHAP) to glyceraldehyde-3-phosphate (G3P) as a quantum operation involving precise proton transfer. To explore the broader implications of this quantum behavior, we developed a quantum model to assess the impact of Sodium-glucose co-transporter 2 inhibitors (SGLT2i) on methylglyoxal formation, a toxic byproduct linked to advanced glycation end products (AGEs). Our model predicts that SGLT2i could reduce methylglyoxal by decreasing the likelihood of intermediate formation, providing a potential mechanism for their protective effects observed in clinical contexts, including vascular and renal protection in diabetes, nephropathy, and heart failure. By reframing TIM as a quantum logic gate, this study not only challenges traditional views of enzymatic function but also opens new avenues for quantum biology, offering profound implications for the future of metabolic disease research and drug development. Moreover considering methylglyoxal as a result of a quantum tunnel inefficiency, it’s possible to hypothesize a new “noxa patogena” explicating it’s action as quantum interference.
A study published on bioRxiv demonstrated that quantum tunneling plays a key role in in vitro hydrolytic enzyme reactions by analyzing kinetic isotope effects (KIE) through deuterium substitution. The involvement of the quantum tunneling effect was confirmed through temperature dependence experiments in major biochemical reactions such as SIRT3-mediated deacetylation, I-SceI-mediated DNA cleavage, and caspase-3-mediated protein cleavage. By observing that DNA homologous recombinational (HR) repair in living cells is almost completely inhibited in a deuterium environment that lowers the probability of quantum tunneling, it was demonstrated that quantum effects dominate cell survival itself. [Quantum Biology Society] Behind life phenomena lies a strange quantum world that cannot be explained by classical mechanics. A prime example is quantum tunneling, where particles pass through reaction energy barriers as if by magic. While it has been known that quantum tunneling contributes to speeding up some enzyme reactions inside proteins , there has been a lack of concrete empirical evidence as to whether this is an essential physical requirement directly linked to actual cell survival. Recently, a groundbreaking study was published showing that if the quantum tunneling effect is inhibited, the cell's life support system itself completely halts. The paper titled "Cell viability is dominated by quantum effects," published on the preprint repository bioRxiv, strongly supports this. A multi-institutional joint research team, including Takeshi Yasuda from the National Institutes for Quantum and Radiological Sciences and Technology (QST) and Kobe University in Japan, led this innovative research. ■ The Link Between Enzyme Hydrolysis and Quantum Tunneling The research team utilized deuterium, an isotope of hydrogen, to track how quantum tunneling is involved in enzymatic chemical reactions. In a heavy deuterium environment, the probability of quantum tunneling is significantly lower compared to light hydrogen, and the research team precisely measured the resulting kinetic isotope effects (KIE) and their temperature dependence. Experimental results proved that the quantum tunneling effect is deeply involved in in vitro hydrolysis reactions essential for cellular metabolism, such as SIRT3-mediated deacetylation, I-SceI-mediated DNA cleavage, and caspase-3-mediated protein cleavage, as evidenced by the disappearance of the isotope effect above specific temperatures. ■ A Halted DNA Repair System Furthermore, the research team directly investigated the impact of the quantum characteristics of these enzyme reactions on living cells. When human cells were exposed to a deuterium-substituted (D₂O) medium environment that artificially lowered the probability of quantum tunneling, it was observed that DNA homologous recombinational (HR) repair, one of the core survival mechanisms of cells, was almost completely inhibited. This means that the most important biochemical repair process protecting and maintaining the genetic information of organisms undergoes a chain reaction of several enzymes and cannot function normally without quantum tunneling phenomena. ■ Quantum Effects Dominating Cell Viability This study empirically demonstrates that core biochemical reactions in living organisms do not simply rely on thermodynamic energy but are fundamentally indebted to quantum mechanical tunneling phenomena. The discovery that numerous hydrolysis and repair reactions performed by enzymes within cells are ultimately strictly dominated by quantum effects serves as crucial evidence that rewrites life phenomena from a purely quantum physics perspective. https://www.biorxiv.org/content/10.1101/2023.07.18.549596v1
• Published on bioRxiv, presenting the first quantum algorithm to dramatically accelerate Flux Balance Analysis (FBA), a core technique in cellular metabolism research. • Overcomes the computational limits of existing classical computing by introducing the Quantum Interior Point Method (QIPM) utilizing Quantum Singular Value Transformation (QSVT) technology. • Proves computational advantage by demonstrating accurate convergence to optimal metabolic fluxes through simulations of the glycolysis and TCA cycle networks. [Quantum Biology Society] Biological systems in living organisms, such as cellular metabolism, are intricately entangled with thousands of biochemical reactions. Modeling and analyzing this network, which determines how a cell grows, responds to its environment, and produces energy, requires massive mathematical computations. As the scale increases, existing classical computers easily hit computational limits. Recently, an innovative study solving the optimization problem of such complex metabolic networks at high speed using quantum computing technology has been published, drawing the academic community's attention. A paper titled "Quantum Algorithm for Metabolic Network Analysis" was released on the preprint repository bioRxiv. Through this paper, a research team comprising Ashish Joshi and Takahiko Koyama from Keio University in Japan presented the first instance of reconfiguring Flux Balance Analysis (FBA)—considered a core and standard technique in cellular metabolism research—to be processed on quantum hardware. ■ Overcoming the Wall of Massive Matrices with Quantum Singular Value Transformation (QSVT) Flux Balance Analysis (FBA) is equivalent to the process of solving a massive Linear Programming problem. To overcome the vast matrix inversions occurring in this process, the researchers newly introduced the Quantum Interior Point Method (QIPM) consisting of quantum subroutines. In particular, by utilizing Quantum Singular Value Transformation (QSVT) technology, a state-of-the-art quantum algorithmic technique, they succeeded in transforming the metabolic optimization problem to run efficiently on a quantum computer. Through this, they designed it to dramatically reduce the bottleneck of classical algorithms, where computation time increases exponentially as the network scale grows and constraints become more complex. ■ Successful Simulation of Glycolysis and the TCA Cycle... Proving Computational Advantage This quantum approach provides a firm computational advantage over the existing classical interior point methods in computing large-scale and highly constrained biological networks. Not stopping at a theoretical proposal, the researchers directly demonstrated the practical applicability of this quantum algorithm by conducting numerical simulations on the glycolysis and TCA cycle networks, the core energy metabolic pathways of cells. As a result of the analysis, it was mathematically proven that the quantum solution accurately converges to the optimal metabolic flux, the correct biological target, without error. This study is evaluated as a significant milestone showing that quantum computing technology can be utilized as a practical and powerful tool to solve challenges in complex systems biology and metabolic engineering, going beyond the realms of physics or chemistry. If this algorithm is advanced and applied to actual large-scale quantum hardware in the future, it is expected to revolutionarily accelerate the production of useful substances using microbial engineering or the discovery of therapeutic targets for intractable metabolic diseases.
BACKGROUND: Key biological processes underlying health and disease-including electron transfer, redox regulation, and radical-mediated signaling-are fundamentally governed by quantum-mechanical principles. These processes are central to mitochondrial function, metabolism, and cellular signaling, yet their biomedical implications have remained difficult to address using classical computational approaches. RATIONALE: Recent advances in quantum computing, quantum sensing, and quantum machine learning enable direct simulation and measurement of quantum phenomena in biologically relevant systems. Hybrid quantum-classical algorithms, such as the Variational Quantum Eigensolver and Quantum Phase Estimation, now provide first-principles access to redox potentials, electronic couplings, and spin-dependent reactions that are directly linked to disease mechanisms. These developments establish the foundation for quantum biomedicine as a translational framework bridging molecular physics and clinical medicine. CONTENT: This review synthesizes current progress in the application of quantum technologies to biomedicine, emphasizing translational relevance. We discuss quantum-informed modeling of cancer metabolism and redox rewiring, protein misfolding in neurodegenerative diseases, immune and inflammatory signaling, infectious disease mechanisms, and drug discovery. We further propose a Quantum-Experimental-Clinical (QEC) pipeline that integrates quantum simulations with experimental validation and multi-omics clinical data, enabling mechanistic interpretation of disease phenotypes and identification of redox- and spin-sensitive therapeutic targets. CONCLUSION: Quantum biomedicine introduces a new mechanistic layer that links electronic-scale processes to clinical phenotypes. While current implementations are constrained by NISQ-era hardware, rapid advances in quantum algorithms and sensing technologies position quantum approaches as emerging tools in precision and translational medicine. Strategic integration of quantum methods with experimental and clinical workflows may accelerate biomarker discovery and therapeutic development. KEY POINTS: Quantum biomedicine redefines life as a dynamic equilibrium sustained by quantum coherence, tunnelling and redox resonance. Hybrid quantum-classical algorithms, such as VQE and QPE, enable first-principles modelling of redox and spin-dependent reactions with near-experimental accuracy. NISQ-era hardware supports proof-of-concept simulations of electron tunnelling and radical-pair dynamics, bridging computation with measurable biophysics. Integration of quantum simulations with spectroscopy and cryo-EM establishes a quantum-experimental-clinical (QEC) pipeline linking theory, experiment and medicine. Ethical, educational and governance frameworks are essential for equitable, transparent and sustainable implementation of quantum health technologies.