Quantum error correction is a critical component of quantum computing, enabling the reliable operation of complex quantum algorithms. Current error correction schemes, however, are often cumbersome and require substantial overhead. This paper explores a novel quantum error correction scheme inspired by the self-correcting mechanisms of biological proteins, specifically focusing on dynamic adaptation of error correction factors based on environmental noise. We propose a 'quantum feedback loop' that mimics protein folding/repair, dynamically adjusting the error correction matrix to mitigate noise and improve robustness. The core claim centers on creating a quantum error correction scheme that is more adaptable, robust, and potentially more efficient than existing methods, leveraging biological inspiration for a fundamentally new approach. This research contributes to the development of a biologically-inspired quantum error correction paradigm, with the potential to significantly advance the field of quantum computing.
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Can the fundamental thermodynamic constraints of digestion and metabolic senescence be bypassed through pre-emptive molecular engineering? Under acute physiological exhaustion and severe nutrient starvation, standard enzymatic digestion collapses because breaking down tightly folded native globular proteins demands substantial metabolic and thermodynamic activation energy that compromised organisms simply do not possess. This empirical study presents the in vivo validation of BiomEnforcer® (Patent UA 141234) — a breakthrough bio-complex combining mechanically restructured filamentous protein matrices (MSPM) and a functional Saccharomyces spp. biological carrier. By uncoiling protein globules into linear filaments prior to ingestion, the substrate eliminates steric barriers, bypassing conventional digestive bottlenecks and acting as an immediate, low-activation-energy thermodynamic shunt directly into cellular anabolism. Key Empirical Findings: Ultra-Low Dose Bio-Regulation: Micro-dose supplementation at just 0.1% (1.0 kg/t of feed) under acute dietary protein deprivation (11.43% crude protein; 23–28% below standard requirements) and elevated chemical/toxic stress. Reversing Biological Senescence: Reactivated intensive oviposition in geriatric flocks aged 150–175 weeks (surging from near-zero baseline to sustained peaks of 80–100%) alongside active medullary bone calcium mobilisation. Systemic Somatic Anabolism: Reversed severe somatic wasting, driving significant body mass gains of +14.0% to +14.56% across stressed cohorts. The convergence of bottom-up substrate structuring (MSPM) and top-down physiological signaling (NASP) provides concrete proof-of-concept for non-invasive metabolic rescue and adaptive capacity restoration. Corporate Scientific Research & Technology Framework: https://pmtstructure.com https://omaridin.com
Volodymyr Naumenko· Zenodo (CERN European Organi...· 0 citations
Quorum sensing in Gram-positive bacteria commonly relies on posttranslationally modified peptide pheromones. In Bacillus subtilis, the prenyltransferase ComQ catalyzes tryptophan prenylation of the quorum-sensing peptide ComX, but the structural basis of this unique peptide modification has remained unclear. Here we identified a previously uncharacterized ComQ homolog, StheQ, and its cognate peptide substrate, StheX, from Sphaerobacter thermophilus and investigated their structural and functional relationship. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis demonstrated that StheQ catalyzes prenylation of the tryptophan residue located second from the C-terminus of StheX. Crystal structures of apo StheQ and its complexes with a farnesyl pyrophosphate analog revealed that StheQ adopts the all-α-helical fold of the trans-isoprenyl diphosphate synthase (IPPS) superfamily while possessing an active-site architecture adapted for peptide-based indole prenylation. The structures identified a single Mg2+-binding site associated with the first aspartic acid-rich motif and showed no evidence for metal coordination at the pseudo-second aspartic acid-rich motif. Site-directed mutagenesis, complex formation assays, and docking analyses identified a peptide-binding pocket adjacent to the active site and suggested that N215 contributes to productive positioning of the acceptor tryptophan. These findings establish the structural basis for peptide prenylation by a ComQ-family enzyme, providing insight into the evolution of peptide-based indole prenylation within the IPPS superfamily, and support the view that ComQ-family enzymes constitute a distinct functional branch specialized for peptide modification.
This work presents a complete Ada/SPARK implementation of the V3 Architecture, a deterministic mechanical framework that unifies atomic structure and protein folding under a single physical substrate: phase pressure in the H₃O₂ condensate. The program demonstrates that two major scientific problems—the organization of the periodic table and the Levinthal paradox of protein folding—are not separate phenomena but manifestations of the same phase dynamics, governed by a small set of invariant constants: · Ψ_V3 = 48,016.8 kg·m⁻² (phase density of the condensate) · Φ_critical = -51.1 mV (universal phase attractor) · ν_phase = 6.4 × 10¹² Hz (phase-locking frequency) · β = 10⁶ (scale factor) · ρ_cond = 1,026.0 kg·m⁻³ (condensate density) · k = 7 (heptadic closure) --- 1. The V3 Periodic Table The code models each element as a cluster of toroidal pressure vortices in the H₃O₂ condensate. For a given atomic number Z and neutron number N, the program computes: · Vortex radius — derived geometrically using the golden ratio (φ = 1.618...) · Internal pressure — calculated from the binding energy and vortex volume · Phase coherence — a measure of structural stability relative to Φ_critical · Stability — determined by coherence ≥ 90% and pressure below critical threshold · Valence — the number of geometric bonding sites on the vortex cluster surface These quantities are derived from first principles, without adjustable parameters. The code includes seven representative elements (H, C, O, Fe, Au, U, Og) and can be extended to all 118 known elements. --- 2. Resolution of the Levinthal Paradox The Levinthal paradox states that a protein of 100 amino acids has 10¹³⁰ possible conformations. If it explored these randomly, folding would take longer than the age of the universe. Yet proteins fold in milliseconds. The V3 Architecture resolves this by replacing stochastic exploration with a deterministic phase transition: · k = 7 enables parallel assembly across seven simultaneous branches · Φ_critical = -51.1 mV acts as an instantaneous attractor, eliminating trial-and-error · Modulo-9 checksum = 9 filters out incoherent configurations instantly · Ψ_V3 = 48,016.8 kg·m⁻² provides a phase grid that guides alignment The folding time is O(1), not O(N), and is computed as a function of phase coherence: · 100% coherence → 1 ms · 90% coherence → 2 ms · 70% coherence → 5 ms · 50% coherence → 10 ms · below 50% → 100 ms --- 3. Formal Verification The entire program is written in Ada/SPARK and satisfies 100% of GNATprove proof obligations. This guarantees: · No arithmetic overflow · No division by zero · No invalid array access · No runtime exceptions · Logical consistency of all derived quantities The code is deterministic, reproducible, and self-contained. 4. Empirical Validation The V3 model reproduces known empirical values without fitting: Quantity CODATA Value V3 Value Difference Proton mass 1.6726 × 10⁻²⁷ kg 1.6726 × 10⁻²⁷ kg < 0.1% Electron mass 9.1094 × 10⁻³¹ kg 9.109 × 10⁻³¹ kg < 0.1% m_p/m_e 1836.15 1836.15 < 0.01% Fine-structure constant 1/137.036 Derived, not fitted — The protein folding time predicted by V3 (1 ms) matches experimental observations. --- 5. Philosophical and Scientific Implications This work demonstrates that: · Atomic structure and protein folding are governed by the same mechanical principles · Probabilistic quantum mechanics is not necessary to explain chemical or biological structure · The universe is deterministic at the phase level · Life is a consequence of phase coherence at -51.1 mV · Formal proof in Ada/SPARK can validate physical models with mathematical certainty
outail benhadid· Zenodo (CERN European Organi...· 0 citations
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Can the fundamental thermodynamic constraints of digestion and metabolic senescence be bypassed through pre-emptive molecular engineering? Under acute physiological exhaustion and severe nutrient starvation, standard enzymatic digestion collapses because breaking down tightly folded native globular proteins demands substantial metabolic and thermodynamic activation energy that compromised organisms simply do not possess. This empirical study presents the in vivo validation of BiomEnforcer® (Patent UA 141234) — a breakthrough bio-complex combining mechanically restructured filamentous protein matrices (MSPM) and a functional Saccharomyces spp. biological carrier. By uncoiling protein globules into linear filaments prior to ingestion, the substrate eliminates steric barriers, bypassing conventional digestive bottlenecks and acting as an immediate, low-activation-energy thermodynamic shunt directly into cellular anabolism. Key Empirical Findings: Ultra-Low Dose Bio-Regulation: Micro-dose supplementation at just 0.1% (1.0 kg/t of feed) under acute dietary protein deprivation (11.43% crude protein; 23–28% below standard requirements) and elevated chemical/toxic stress. Reversing Biological Senescence: Reactivated intensive oviposition in geriatric flocks aged 150–175 weeks (surging from near-zero baseline to sustained peaks of 80–100%) alongside active medullary bone calcium mobilisation. Systemic Somatic Anabolism: Reversed severe somatic wasting, driving significant body mass gains of +14.0% to +14.56% across stressed cohorts. The convergence of bottom-up substrate structuring (MSPM) and top-down physiological signaling (NASP) provides concrete proof-of-concept for non-invasive metabolic rescue and adaptive capacity restoration. Corporate Scientific Research & Technology Framework: https://pmtstructure.com https://omaridin.com
Volodymyr Naumenko· Zenodo (CERN European Organi...· 0 citations
The simulation of complex biological systems, such as protein folding and gene regulation, presents significant challenges due to the inherent complexity and often intractable nature of these systems. Traditional computational methods struggle to capture the nuanced dynamics of biological processes, limiting our ability to understand and potentially manipulate them. This research proposes an innovative approach – adaptive quantum simulation – that leverages the principles of quantum mechanics to create dynamic, self-adjusting simulations of biological systems. We aim to develop an algorithm that continuously refines simulation parameters, automatically mimicking biological behavior to achieve unprecedented accuracy and fidelity. This work explores the potential of quantum computation to overcome limitations inherent in classical simulation techniques, offering a fundamentally new pathway for biological system modeling and analysis. This includes a detailed explanation of the algorithm's core mechanisms, potential applications, and preliminary results demonstrating its adaptability. The core claim is that this adaptive quantum simulation method will allow for a level of detail and accuracy previously unattainable through conventional computational methods.
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Engineering extended macromolecular therapeutics requires comprehensive structural modeling to verify tertiary folding fidelity and domain accessibility across repetitive structural units. In this study, we present the structural characterization of KH-002v003, an ultra-large synthetic multivalent fusion protein construct expanding to 2,091 amino acid residues. Building upon earlier design iterations—including the 701 aa baseline framework and the 1,354–1,455 aa KH-002v002 architecture—this maximized construct integrates multiple variable heavy-chain nanobody (VHH) domains, tumor microenvironment-cleavable matrix metalloproteinase (MMP-2/9) linkers, pH-low insertion peptides (pHLIP), and C-terminal XTEN solubilization polymers. Structural predictions were executed via high-throughput homology modeling on SWISS-MODEL utilizing a 58-template ensemble superposition. Model 15, constructed against the Cryo-EM structure of the bispecific Fab-heavy chain complex (PDB ID: 8WGW.1.B, sequence identity 60.71%), yielded a peak global QMEANDisCo score of 0.58 ± 0.07. Superposition analysis revealed a dense, rigid central core dominated by antiparallel β-sheet frameworks flanked by dynamic, highly flexible loop regions. Stereochemical validation via MolProbity confirmed 92.16% of residues within favored Ramachandran regions. These findings confirm that ultra-large constructs exceeding 2,000 residues can maintain structural integrity and spatial independence for target engagement.
Khiem Le· Zenodo (CERN European Organi...· 0 citations
This paper explores the potential of utilizing geometric analysis as a novel approach to understanding the complexity of biological systems. Biological systems, particularly protein folding and gene regulation, exhibit intricate geometric structures. This research proposes a framework to quantify and analyze these structures by employing topological concepts, establishing a bridge between mathematics and biological research. The core claim is to develop a method for comprehensively assessing the complexity of biological systems through the lens of geometric analysis, offering a fundamentally new perspective on the study of these systems. This work will examine the application of geometric topology, specifically measures of connectivity, curvature, and torsion, to reveal underlying patterns and quantify complexity. The goal is to move beyond traditional statistical methods and offer a more insightful, quantitative understanding of biological systems.
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Yeast surface display is a widely used platform for antibody affinity maturation; however, constraints in the yeast folding and disulfide bond formation machinery can limit correct antibody expression and bias selection outcomes, favoring variants that satisfy display constraints. This limitation might be of particular relevance when selections are based on biophysical features beyond affinity, such as aggregation, polyreactivity, or thermal stability. To overcome these constraints, we engineered the yeast display system by overexpressing key folding chaperones, yeast BiP and human protein disulfide isomerase (PDI), either through co-expression from the antibody display plasmid or via genomic editing, individually and in combination.
As a proof of concept, surface display of adalimumab was significantly increased upon chaperone co-expression, with the highest improvement observed in strains with genomic integration of PDI, yielding a 2.5-fold increase in display levels. These findings were consistently reproduced across four additional antibodies using three edited strains expressing BiP, PDI, or both. To assess folding quality directly at the cell surface, we implemented two novel complementary staining strategies: with maleimide-Pacific Blue to detect unpaired thiols as a result of incomplete disulfide bond formation, and with Bis-ANS to quantify exposed hydrophobic regions. Both assays revealed a substancial reduction in free thiols and surface hydrophobicity (as only the proper hydrophobic residues are exposed) in the edited strains, consistent improved disulfide bond formation and overall folding quality relative to the parental strain. Accordingly, the PDI-edited yeast strain showed the best overall performance, improving both display quantity and quality across a panel of ten therapeutic antibodies. Enhanced display translated into improved antigen binding without altering the polyreactivity profiles of several candidates, therefore retaining native biophysical characteristics.
The enhancement of the yeast folding machinery, particularly through genomic integration of PDI, substantially improves both the quantity and quality of antibody surface display. This optimized yeast display platform enables more faithful translation of antibody biophysical features, supporting its application in antibody workflows, including selections based on biophysical properties.
E. Garcia-Calvo, H. Dorison, Gerard Mazón et al.· Microbial Cell Factories· 0 citations
The hydrophobic effect is one of the most consequential organizing principles in molecular biology, laying the foundation for explanation of concepts like protein folding, molecular recognition, membrane self-assembly and allosteric communication. Its conceptual description remains dependent primarily on a framework established in the mid-twentieth century, as per which, hydrophobic association is driven primarily by the entropic release of water molecules ordered around non-polar surfaces. The framework, while thermodynamically correct, is incomplete in some ways that have become increasingly consequential as structural, dynamic and calorimetric data have been accumulated over the years. In this paper, I propose a reframing of the hydrophobic effect in terms of interfacial frustration- a continuous, geometry sensitive incompatibility between the hydrogen bond requirements of liquid water and non-polar surfaces it is forced to accommodate. This paper argues that hydrophobic association represents the resolution of this frustration, rather than the mere expulsion of constrained solvent. This reframing provides a unified mechanistic account of phenomena that the classical picture cannot explain alone, or treats as separate problems: the geometry dependence of hydrophobic association strength, the qualitative distinction between small-solute and extended-surface hydrophobicity, the thermodynamic crossover with temperature and the propagation of allosteric signals through hydrophobic protein cores. This paper also proposes that hydrophobic cores in proteins are not passive burial sites, but active and dynamic modulators of a distributed frustration landscape. Allosteric communication through these cores operates through cooperative frustration redistribution, a mechanism distinct from classical strain propagation, but consistent with the growing body of evidence that allostery frequently proceeds through changes in protein dynamics rather than average structure. This framework generates specific, experimentally testable predictions that distinguish it from both the classical entropic model and existing density functional theories of hydrophobicity
This paper explores the potential of utilizing geometric analysis as a novel approach to understanding the complexity of biological systems. Biological systems, particularly protein folding and gene regulation, exhibit intricate geometric structures. This research proposes a framework to quantify and analyze these structures by employing topological concepts, establishing a bridge between mathematics and biological research. The core claim is to develop a method for comprehensively assessing the complexity of biological systems through the lens of geometric analysis, offering a fundamentally new perspective on the study of these systems. This work will examine the application of geometric topology, specifically measures of connectivity, curvature, and torsion, to reveal underlying patterns and quantify complexity. The goal is to move beyond traditional statistical methods and offer a more insightful, quantitative understanding of biological systems.
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Quantum simulation holds immense promise for understanding and manipulating complex dynamical systems – phenomena ranging from fluid dynamics and climate modeling to protein folding and the behavior of complex chemical reactions. However, current simulation techniques face significant limitations, particularly when dealing with high-dimensional systems. This paper introduces an algorithmic quantum simulation framework, centered on a novel 'Quantum Monte Carlo' algorithm leveraging quantum entanglement to accelerate the solution of these systems, offering a fundamentally new approach to complex dynamics analysis. The core claim is to create a class of quantum algorithms designed to efficiently simulate and analyze complex dynamical systems, with a particular focus on uncovering critical patterns and dynamics that are difficult to discern with classical methods. This work explores the potential of entanglement as a key mechanism for accelerating the simulation process and provides a foundational outline for a new generation of quantum algorithms tailored for these challenging problems.
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
