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.
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.
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.
The penetration of quantum concepts into biological science, which began shortly after the creation of quantum mechanics, over the past two decades has taken shape in a new interdisciplinary scientific discipline quantum biology. One of the key questions of quantum biology has been formulated as follows: are there biological systems that use quantum effects to perform a task that cannot be done classically? More broadly, do some kinds of organisms adapt efficient quantum mechanisms in the process of their evolutionary development in order to gain an advantage over their competitors? The range of topical problems of the new discipline discussed in this brief review includes questions of a general, historical and methodological character, and generalizes some theoretical models aimed at describing quantum processes, including bacterialphotosynthesis, bird magnetoreception, and the mechanism of olfactory sense in living organisms.
Abstract The lines separating Biology and Physics have started to blur in recent decades, leading to the emergence of the interdisciplinary field known as quantum Biology. This field looks into the possibility that basic quantum mechanical phenomena such as coherence, entanglement, tunneling, and superposition play crucial roles in biological processes that are beyond the scope of classical Physics. Biology has traditionally worked within the parameters of classical mechanics, presuming that delicate quantum effects cannot endure in the warm, humid, and cacophonous environments of living systems. But new findings in fields like photosynthesis, olfaction, avian magnetoreception, and enzyme catalysis indicate otherwise, suggesting that living things intentionally and possibly advantageously use quantum principles. From the earliest speculative theories to the most recent experimental confirmations, this book chapter methodically examines the evolution of quantum Biology. We investigate how the exceptionally high energy transfer efficiency in photosynthetic complexes particularly in the light-harvesting proteins of green sulfur bacteria and plants is supported by quantum coherence. The remarkable speed of proton transfers and enzymatic reactions during DNA replication is also investigated in relation to quantum tunneling. The chapter explores magnetoreception in migratory birds and suggests models in which sensitivity to Earth's geomagnetic field is made possible by radical pair mechanisms influenced by quantum entanglement. We also discuss the intriguing but controversial idea that quantum vibrations improve the human olfactory system's capacity for discrimination. In addition to examining particular occurrences, this research challenges more general theoretical models that seek to balance quantum mechanics with the decoherence commonly observed in biological settings. Recent developments in quantum information theory, biomimetic quantum technologies, and ultrafast spectroscopy are highlighted as essential instruments advancing empirical research. We also critically evaluate the field's methodological difficulties, the skepticism of overly optimistic interpretations, and the significant philosophical ramifications of acknowledging life as a quantum phenomenon. In conclusion, quantum Biology suggests that quantum effects are not uncommon aberrations but rather are an essential part of life, offering not only a fresh perspective for reinterpreting well-known biological processes but also the potential for a fundamental paradigm shift. Quantum biology has the potential to completely transform biotechnology, medicine, and our comprehension of consciousness and the origin of life as experimental methods advance. This chapter highlights the significance of interdisciplinary cooperation in order to completely comprehend the latest discoveries and possible future paths of quantum Biology, highlighting its revolutionary influence on our comprehension of life at the most basic levels. Key words: Quantum Biology, tunneling, avian magnetoreception, enzyme catalysis
Introduction Key features of quantum mechanics are the uncertainty principle, wave–particle duality, quantization of energies and the modification of classical probability laws. Biology is concerned with how natural systems function – from understanding how genetically coded information is replicated, to attaining a mechanistic model for complex multistep reactions. Recently researchers have been asking whether quantum mechanics, normally the domain of physics, is also needed to understand some biological processes. This field includes fascinating developments in theory and experiment, as well as multidisciplinary discussion, and the state-of-the-art is documented in this book. Erwin Schrödinger, in his famous book What is Life ? (Schrödinger, 1944), noted that quantum mechanics accounts for the stability of living things and their cellular processes because of our understanding, via quantum mechanics, of the stability and structure of molecules. The fact that quantum effects create, sometimes large, energy gaps between different states of a chemical system is also important. Such energy gaps, between electronic energy levels, enable living organisms to capture and store the energy carried from the sun by photons, and to visualize the world around them via optically induced chemical reactions. Davydov's view in Biology and Quantum Mechanics (Davydov, 1982) was that quantum mechanics is most relevant for isolated systems in pure states and therefore is of little importance for biological systems that are in statistical states at thermal equilibrium.
Abstract Quantum biology has emerged as a frontier discipline, revealing that phenomena such as coherence, entanglement, and tunneling are not merely theoretical curiosities but functional components of living systems. This volume, Quantum Biology under ICQER, presents a unified framework for understanding these phenomena through the lens of the ICQER (Informational Constraints, Quantum Events, and Emergent Realities) paradigm. We propose that biological systems are fundamentally networks of informational constraints that channel, filter, and stabilize quantum events, enabling their propagation from molecular scales to emergent organismal behaviors. The work systematically examines how these constraint networks govern key biological processes, including photosynthetic energy transfer, enzymatic catalysis, magnetoreception, and neural cognition. Furthermore, we explore the evolutionary implications of quantum-informed constraints, demonstrating that natural selection acts not only on classical phenotypes but on the very architectures that harness quantum effects. By integrating molecular quantum dynamics with complex systems theory, this volume establishes ICQER as a predictive and unifying model for quantum biology. It redefines life as a quantum-constrained informational system and provides a roadmap for future research, with far-reaching implications for synthetic biology, bio-inspired technologies, and the fundamental understanding of life's informational architecture.
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.