Replication of DNA and synthesis of proteins are studied from the view-point of quantum database search. Identification of a base-pairing with a quantum query gives a natural (and first ever!) explanation of why living organisms have 4 nucleotide bases and 20 amino acids. It is amazing that these numbers arise as solutions to an optimisation problem. Components of the DNA structure which implement Grovers algorithm are identified, and a physical scenario is presented for the execution of the quantum algorithm. It is proposed that enzymes play a crucial role in maintaining quantum coherence of the process. Experimental tests that can verify this scenario are pointed out.
Replication of DNA and synthesis of proteins are studied from the view-point of quantum database search. Identification of a base-pairing with a quantum query gives a natural (and first ever!) explanation of why living organisms have 4 nucleotide bases and 20 amino acids. It is amazing that these numbers arise as solutions to an optimisation problem. Components of the DNA structure which implement Grovers algorithm are identified, and a physical scenario is presented for the execution of the quantum algorithm. It is proposed that enzymes play a crucial role in maintaining quantum coherence of the process. Experimental tests that can verify this scenario are pointed out.
The possible role of quantum effects in transfer of genetic information is studied. It's argued that the nucleotides selection during DNA replication is performed by means of proton tunneling between nucleotide and DNA-polimerase bound by hydrogen bonds. Such mechanism is sensitive to the structure of nucleotide hydrogen bonds, consequently only one nucleotide sort is captured by DNA-polimerase in each event.The algorithm of this multistep selection mechanism is also analysed from the point of its optimality. It's shown that it's equivalent to Grover algorithm of data base search.
• Development of the quantum algorithm 'QuBio.py' for searching and analyzing genetic information. • Successful detection of a 50-nucleotide target sequence within a 3,022-nucleotide database using a 127-qubit simulator on the IBM quantum platform. • Securing flexibility that allows up to a 30% mismatch rate... Heralding a new horizon for synthetic biology and new drug development. [Quantum Biology Society] A "quantum computing"-based gene search algorithm has emerged, capable of analyzing exponentially increasing biological data at ultra-high speeds, surpassing the limitations of conventional computers. A study titled "GENETIC ENGINEERING THROUGH QUANTUM CIRCUITS: CONSTRUCTION OF CODES AND ANALYSIS OF GENETIC ELEMENTS BIOBLOQU" was recently published on bioRxiv, a preprint repository for biological sciences. The research team, including Patrícia Verdugo Pascoal, presented an innovative model that explores and manipulates genetic information utilizing quantum mechanics. ■ Translating the Four DNA Bases into Quantum Language... The Evolution of 'Grover's Algorithm' Modern biology generates approximately 1 Gb of sequencing data per hour, but analyzing this data using classical computing methods faces significant limitations. Existing database search methods require computation time proportional to the data size (O(N)), but the quantum-based 'Grover's algorithm' applied by the researchers can significantly reduce this to the O(√N}) level. In particular, a key feature of this study is that it adapted the algorithm to process the four nucleotides (A, T, G, C) that make up DNA, rather than simple binary symbols, thereby enabling it to operate efficiently on more complex datasets. ■ Detecting the Cas9 Target Sequence with 127 Qubits... Creation of Synthetic Genome (BioBloQu) Based on the 127-qubit simulator of the IBM cloud platform, the research team developed its own quantum algorithm code named 'QuBio.py'. Through this algorithm, they succeeded in finding a specific 50-nucleotide target DNA sequence within a genetic database consisting of up to 3,022 nucleotides. A conserved functional domain of the Cas9-like nucleotide sequence found in Brazilian biomes was used as the target sequence. Notably, this quantum algorithm permits a mismatch rate of up to 30% during the sequence comparison process. This enables flexible and rapid analysis in situations where sequence variations are expected, such as homologous gene analysis or evolutionary studies. Furthermore, based on these search results, the team succeeded in constructing a synthetic structure called a 'Quantum Biological Block (BioBloQu)' inside minimal cells (JCVI-syn3.0). The researchers stated that this algorithm "constitutes a unique starting point for developing a more sophisticated model for the manipulation of data". They also predicted that "the integration of quantum computing with artificial intelligence represents an attractive avenue... By optimizing genetic algorithms and facilitating real-time data analyses, quantum computing can revolutionize trait discovery processes in agriculture and biotechnology". This achievement is evaluated as an important example demonstrating how quantum computing can contribute to next-generation synthetic biology technologies that analyze large-scale genetic big data and design genomes from the bottom up.
Most problems and limitations associated with classical computing are eliminated in quantum computing. Despite the current methods of quantum computing which have to deal with the non-secondary problem of decoherence induced by the coupling of the system with the environment, biological systems use quantum physics at high temperature and in highly noise environments. As a consequence, taking inspiration from how DNA, enzymes and other biomolecules exploit quantum properties could help us find methods of quantum computation that could bypass the problems encountered in non-biological systems. In this paper, we shortly review bio-inspired qubits systems and how endonuclease restriction enzymes exploit quantum physics to solve searching problem, i.e., the identification of small sequences (4-6 nucleotides bases) in DNA (approximately 1 million nucleotides bases) complexes and its implication in developing universal quantum gates. The possible implications for quantum computation of this restriction enzyme feature is then briefly described
• Developed quantum codes based on Grover's algorithm using an IBM 127-qubit quantum simulator for large-scale genetic sequence analysis and optimization. • Successfully searched a 3,022-nucleotide database for a 50-nucleotide target sequence at exponential speeds with high flexibility (allowing up to a 30% mismatch rate). • Successfully constructed a synthetic structure named "Quantum Biological Block (BioBloQu)," which combines components such as a promoter and an enzyme, within a minimal JCVI-syn3.0 cell. [Quantum Biology Society] To process the exponentially growing vast amounts of biological data, research results applying quantum algorithms to genomics in earnest have been released for the first time. Recently, a paper titled "GENETIC ENGINEERING THROUGH QUANTUM CIRCUITS: CONSTRUCTION OF CODES AND ANALYSIS OF GENETIC ELEMENTS BIOBLOQU" was published on bioRxiv, a preprint repository for biology. ■ Breaking Through the Limits of Genetic Analysis with a 127-Qubit Quantum Simulator To analyze and optimize large-scale genetic sequences, the research team newly developed two quantum codes applying Grover's algorithm based on IBM's 127-qubit quantum simulator. As a result of testing this quantum algorithm, they succeeded in finding a specific target sequence consisting of 50 nucleotides within a DNA database composed of up to 3,022 nucleotides. In particular, considering natural genetic variations, it demonstrated overwhelmingly fast and flexible search capabilities compared to existing classical computing exploration methods, even allowing a mismatch rate of up to 30%. ■ 'Quantum Biological Block (BioBloQu)' Planted Inside an Artificial Cell The team's achievements did not stop at simple quantum code development and sequence exploration. Based on these quantum computing-based search results, the researchers focused on the interior of 'JCVI-syn3.0', an artificial cell model that maintains life phenomena with only minimal genes. Here, they successfully constructed a synthetic structure named the 'Quantum Biological Block (BioBloQu)', composed of a promoter, a ribosome binding site (RBS), an enzyme, and a terminator. This achievement is highly significant in that it proved quantum computing technology is not merely at a theoretical level, but is a powerful tool capable of innovatively accelerating the speed of actual genetic exploration and manipulation.
DNA, deoxyribonucleic acid, carrying encoded genetic information at molecular level, is the most significant discovery in the history of genetics. Previous researches on DNA included topics of bases, base-pairing, hydrogen bonds, structure, base sequence, dynamics, replication and mutation. DNA must duplicate itself, and so DNA structure and DNA replication are the fundamental problems. Watson and Crick described the structure and the mechanism for replication of DNA. Other authors focused their studies on DNA replication. DNA molecules are micro-entities ruled by laws of quantum mechanics, but the mechanisms, found previously of DNA forming and replicating, were not explored by applying quantum mechanics. Here we show that controlled by quantum mechanics, the quantum state of DNA is a bio-quantum-entangled state, the mechanism of DNA forming and replicating is a process of bio-quantum entangling, de-entangling and re-entangling. This bio-quantum mechanical result is different from the conventional biochemical descriptions of DNA structure and replication. DNA genetics is bio-quantum genetics in nature. With this deep understanding, reform and progress should be expected for further development of genetics.