Quantum mechanics has an important role in photosynthesis, magnetoreception, and evolution. There were many attempts in an effort to explain the structure of genetic code and transfer of information from DNA to protein by using the concepts of quantum mechanics. The existing biological quantum channel models are not sufficiently general to incorporate all relevant contributions responsible for imperfect protein synthesis. Moreover, the problem of determination of quantum biological channel capacity is still an open problem. To solve these problems, we construct the operator-sum representation of biological channel based on codon basekets (basis vectors), and determine the quantum channel model suitable for study of the quantum biological channel capacity and beyond. The transcription process, DNA point mutations, insertions, deletions, and translation are interpreted as the quantum noise processes. The various types of quantum errors are classified into several broad categories: (i) storage errors that occur in DNA itself as it represents an imperfect storage of genetic information, (ii) replication errors introduced during DNA replication process, (iii) transcription errors introduced during DNA to mRNA transcription, and (iv) translation errors introduced during the translation process. By using this model, we determine the biological quantum channel capacity and compare it against corresponding classical biological channel capacity. We demonstrate that the quantum biological channel capacity is higher than the classical one, for a coherent quantum channel model, suggesting that quantum effects have an important role in biological systems. The proposed model is of crucial importance towards future study of quantum DNA error correction, developing quantum mechanical model of aging, developing the quantum mechanical models for tumors/cancer, and study of intracellular dynamics in general.
Quantum mechanics has an important role in photosynthesis, magnetoreception, and evolution. There were many attempts in an effort to explain the structure of genetic code and transfer of information from DNA to protein by using the concepts of quantum mechanics. The existing biological quantum channel models are not sufficiently general to incorporate all relevant contributions responsible for imperfect protein synthesis. Moreover, the problem of determination of quantum biological channel capacity is still an open problem. To solve these problems, we construct the operator-sum representation of biological channel based on codon basekets (basis vectors), and determine the quantum channel model suitable for study of the quantum biological channel capacity and beyond. The transcription process, DNA point mutations, insertions, deletions, and translation are interpreted as the quantum noise processes. The various types of quantum errors are classified into several broad categories: (i) storage errors that occur in DNA itself as it represents an imperfect storage of genetic information, (ii) replication errors introduced during DNA replication process, (iii) transcription errors introduced during DNA to mRNA transcription, and (iv) translation errors introduced during the translation process. By using this model, we determine the biological quantum channel capacity and compare it against corresponding classical biological channel capacity. We demonstrate that the quantum biological channel capacity is higher than the classical one, for a coherent quantum channel model, suggesting that quantum effects have an important role in biological systems. The proposed model is of crucial importance towards future study of quantum DNA error correction, developing quantum mechanical model of aging, developing the quantum mechanical models for tumors/cancer, and study of intracellular dynamics in general.
Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled.
This study explores the potential of quantum computing as an alternative information processing approach, utilizing quantum bits (qubits), superposition, and entanglement to significantly expand computational capabilities in the healthcare domain. It is evident that quantum mechanics has become a foundational component in the construction of our contemporary physical reality. This scientific field is distinguished by its rapid advancement and the potential to transform various aspects of our daily lives. In this era, quantum biology is of significant importance and has the potential to act as a transformative force, particularly in the field of medicine, specifically in addressing the challenges posed by cancer. Cancer is defined as a complex and abnormal alteration of cells, orchestrated through intricate signaling pathways. This transformation is characterized by the accumulation of deleterious mutations. The concept of phenocopy, representing genetic mutations influenced by the environment, challenges the linear process line of molecular biology involving DNA, RNA, and proteins. Notwithstanding the augmented focus on quantum biology in recent decades, a plethora of unresolved issues persist within the domain of cancer biology, thereby giving rise to unexplored avenues. Quantum theory has demonstrated its ability to explain models related to biological and biochemical processes, encompassing the effects of carcinogens on genes, the mechanism of interactions between chemotherapy drugs and DNA, and the understanding of DNA mutations and defective protein synthesis. Recent skepticism among quantum physicists regarding the fundamental role of quantum effects in biology has emerged, particularly with regard to open quantum systems and the impact of decoherence on the destruction of coherence necessary for significant quantum effects. The document under scrutiny herein undertakes an investigation of recent studies that are rooted in the principles of quantum physics, with a particular focus on the manner in which these principles apply to the domains of cancer biology and metabolism.
DNA replication upholds genomic integrity with remarkable precision, rectifying inaccuracies that emerge from quantum-level phenomena. This paper introduces a novel framework that models this biological process using the formalism of quantum error correction .We propose that genetic information encoded in DNA base pairs can be represented as the codespace of a Biological Stabilizer Code , where cellular proofreading and mismatch repair mechanisms function as an active error correction protocol.We provide comprehensive proofs that illustrate the code’s capacity to preferentially rectify the most likely types of mutations, thereby guaranteeing elevated logical fidelity. We establish a biological equivalent of the quantum threshold theorem, demonstrating that high-fidelity replication can be achieved if the inherent mutation rate falls below a critical threshold. The performance of the BSC is corroborated through simulations conducted in Qiskit, which reveal its superior efficacy compared to symmetric codes under biologically plausible noise conditions. This research establishes a quantitative relationship between the principles of fault-tolerant quantum computation and the mechanisms that uphold the stability of life’s genetic code.
Molecules are the basis of life. They can consider as a quantum system. So it is necessary to enter quantum mechanics in biological discussion. Specifically, we should expect the quantum to be the basis for heredity, genetic, biology and DNA. In this paper we consider the DNA molecules as a quantum system. We discuss about the relation between the heredity, biology and DNA and quantum systems. We also claim that there is a relation between the quantum information and some biologicaly-process such as cell division, cloning so that we think that the root of all problems in cloning may be in the quantum effects.
This research investigates the potential role of quantum entanglement in biological information processing. We explore the feasibility of simulating quantum effects within biological molecules and examining the influence of entanglement on fundamental processes such as DNA sequence recognition and protein folding. The core claim centers on demonstrating how entanglement could provide a mechanism for enhanced computational capabilities within biological systems. This work contributes to the emerging field of quantum biology by proposing a novel framework for understanding biological phenomena through the lens of quantum mechanics, specifically focusing on the emergent properties of entanglement. The theoretical analysis presented here lays the groundwork for future experimental investigations and offers a new perspective on the complexities of life.
This work presents a rigorous, cross-domain review of mechanisms in living systems that exhibit mathematical parallels with quantum error correction (QEC). Rather than relying on metaphor or loose analogy, the paper traces concrete isomorphisms between stabilizer codes, decoherence-free subspaces, dynamical decoupling, and the specific molecular architectures that sustain high-fidelity biological information. The review synthesizes evidence across three domains—genomic stability, neural information processing, and metabolic coherence—and examines proton tunneling, tautomer suppression, nuclear spin protection, microtubule lattice codes, excitonic transport, ENAQT, vibronic stabilizers, and the radical-pair magnetoreception model. By comparing these biological processes to formal properties of QEC (Knill–Laflamme conditions, threshold theorems, syndrome extraction, and topological protection), the work argues that biological robustness can be understood as an evolved form of error-correcting architecture. The conclusion highlights the role of noise-structured environments, energetic cost constraints, and threshold behavior, and proposes that QEC-style mechanisms may be universal to life operating near the quantum–classical boundary.