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Quantum π in Biomolecular Dynamics: Proteins as Nano-Quantum Fluids

Ndenga, Barack

Published Dec 2, 2025• 0 citations
Publisher

Abstract

I propose a theoretical framework in which proteins are treated as nano-scale quantum fluids, whose internal dynamics are described by a Quantum π-field defined on their three-dimensional structure. Building on the hydrodynamic formulation of quantum mechanics (Madelung quantum hydrodynamics), I introduce a π-field that encodes local quantum coherence, phase topology, and energy flow within the protein, with particular emphasis on aromatic networks and electron/proton transfer channels. In this picture, proteins are not merely static folded structures or classical particles diffusing on an energy landscape; instead, they become quantum-coherent, fluid-like entities, with internal flows, vortices, and topological defects. Mutations and ligand binding are modeled as perturbations of the π-field, modifying local coherence, transport efficiency, and long-range allosteric communication. This approach unifies concepts from quantum hydrodynamics, protein energy landscapes, and bio-inspired quantum information flows, and it suggests a new class of computational tools for predicting mutation effects, functional hotspots, and dynamical pathways. To my knowledge, no existing biomolecular theory explicitly treats proteins as nano-quantum fluids governed by a π-field. I therefore present this framework as a novel conceptual and mathematical model for biomolecular dynamics.

DOI
10.60763/africarxiv/10336

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I propose a theoretical framework in which proteins are treated as nano-scale quantum fluids, whose internal dynamics are described by a Quantum π-field defined on their three-dimensional structure. Building on the hydrodynamic formulation of quantum mechanics (Madelung quantum hydrodynamics), I introduce a π-field that encodes local quantum coherence, phase topology, and energy flow within the protein, with particular emphasis on aromatic networks and electron/proton transfer channels. In this picture, proteins are not merely static folded structures or classical particles diffusing on an energy landscape; instead, they become quantum-coherent, fluid-like entities, with internal flows, vortices, and topological defects. Mutations and ligand binding are modeled as perturbations of the π-field, modifying local coherence, transport efficiency, and long-range allosteric communication. This approach unifies concepts from quantum hydrodynamics, protein energy landscapes, and bio-inspired quantum information flows, and it suggests a new class of computational tools for predicting mutation effects, functional hotspots, and dynamical pathways. To my knowledge, no existing biomolecular theory explicitly treats proteins as nano-quantum fluids governed by a π-field. I therefore present this framework as a novel conceptual and mathematical model for biomolecular dynamics.
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The coexistence of quantum coherence, nonlinear fluid dynamics, and biomolecular π-fields within biological and nanoscale systems requires a unified mathematical description. Classical hydrodynamics alone fails to capture coherence propagation, while the linear Schrödinger equation cannot model dissipation, viscosity, or turbulence. Here, I introduce the Schrödinger–Navier–Stokes–π Unified Computational Framework, a novel equation set combining: the quantum phase field of the Schrödinger equation, the viscous and nonlinear transport of Navier–Stokes dynamics, the curvature-driven quantum π-potential, and a hybrid Hamiltonian–dissipative evolution capturing both coherence and irreversible flow. This framework predicts quantum-fluid transitions, π-induced tunneling acceleration, coherence-enhanced mixing, nanoscale turbulence, and dynamic switching between classical and quantum transport regimes. It provides a general model applicable to biology, nanotechnology, photonics, and quantum materials. Keywords : Quantum Hydrodynamics Navier–Stokes Schrödinger Equation Unified Computational Framework π-field Dynamics Quantum Fluid Mechanics Hybrid Quantum-Classical Transport Coherence-Based Models Quantum Biology Nanoscale Transport Bio-Quantum Modeling Quantum Potential Quantum Fluid Engineering Biophysical Modeling Nonlinear Dynamics Computational Physics High-Order Numerical Methods Dissipative Quantum Systems Biomolecular Channels Quantum-Inspired Computing
I present a unified theoretical and numerical framework that couples quantum wave dynamics (Schrödinger) with classical viscous flow (Navier–Stokes) through an emergent quantum-π field (π_q) that encodes phase-topology and coherence. The model reproduces Schrödinger dynamics in the conservative limit, Navier–Stokes turbulence in the dissipative limit, and novel intermediate regimes where quantum coherence and fluid turbulence coexist and interact. I derive the governing equations by (i) applying a Madelung decomposition to a complex field ψ, (ii) introducing a controlled viscous regularization and non-linear coupling terms, and (iii) coupling a dynamically evolving π_q scalar (or tensor) field that modulates local coherence, effective mass, and information flux. I then present a robust hybrid numerical method (QHFVM — Quantum Hydrodynamic Finite-Volume Method) combining split-step spectral propagation for dispersive quantum terms and conservative finite-volume solvers for advective, viscous and pressure dynamics. I validate the approach on a set of canonical problems (quantum vortex shedding in a viscous background, π-phase revival in confined geometries, and turbulence spectra with quantum corrections), show numerical convergence and conservation properties, and outline applications spanning quantum fluids, nanoscale bio-fluids, materials, and hybrid QEC architectures. Flash explanations highlight intuition and immediate experimental tests.
This article introduces a unified model combining the Schrödinger equation, Navier–Stokes dynamics, and π-field coherence into a single computational framework. The approach describes systems where quantum coherence, viscosity, dissipation, and structural curvature coexist at the nanoscale. The framework predicts hybrid transport regimes, coherence-modulated flow, and π-induced quantum potentials. High-order numerical simulations (4th-order finite differences + RK4) demonstrate transitions between quantum-dominant, hybrid, and classical behaviours. To my knowledge, this is the first formulation unifying Schrödinger dynamics, viscous fluid flow, and π-field curvature into one model.
This paper presents a novel approach to protein structure prediction leveraging the principles of quantum entanglement. Traditional protein structure prediction methods are often limited by the computational complexity of simulating large biomolecular systems. We propose a framework that utilizes quantum entanglement to model the complex correlations inherent in protein folding, potentially overcoming these limitations. The core idea involves translating the amino acid sequence of a protein into a quantum state and employing quantum computation, specifically entanglement-based algorithms, to predict the protein's three-dimensional structure. The theoretical framework outlines the transformation process, the quantum algorithm design, and the methods for interpreting the results. We explore the potential advantages of this approach, focusing on its ability to capture long-range interactions and conformational flexibility that are difficult to model accurately with classical methods. The ultimate goal is to establish a new paradigm for protein structure prediction, offering improved accuracy and efficiency.