High-Performance Computational Simulation of Quantum Many-Body Systems with Benchmark Validation Using Biophysical Macromolecular Structures in Hybrid Protein Matrices

Abstract

This study presents a multidisciplinary framework integrating high-performance computational simulations of quantum many-body systems with experimental and statistical modelling of hybrid protein matrices. The objective was to investigate the relationship between molecular-scale interactions and macroscopic physicochemical properties within soy–whey protein systems. Soy Protein Isolate (SPI) and Whey Protein Isolate (WPI) were used as model components, with microbial transglutaminase (MTGase) employed to induce ultrasonic-assisted enzymatic crosslinking. A Central Composite Rotatable Design (CCRD) within Response Surface Methodology (RSM) was implemented to evaluate the effects of SPI:WPI ratio and enzyme concentration on hardness, chewiness, and bond energy. At the quantum level, high-performance computing (HPC)-based simulations were conceptually applied to approximate protein systems as quantum many-body systems, enabling the evaluation of interaction energies, bond formation tendencies, and electronic-level stability. Molecular interaction parameters derived from these simulations were correlated with experimentally measurable responses. Benchmark validation using Protein Data Bank (PDB) structures and Root Mean Square Deviation (RMSD) analysis confirmed structural consistency between modelled and reference protein conformations. Statistical analysis revealed that both formulation variables significantly influenced response parameters (p < 0.0001), with enzyme concentration exhibiting the dominant effect on network formation and mechanical strength. Increasing MTGase levels and SPI content resulted in enhanced crosslink density, more negative bond energies, and improved textural attributes. The predictive model demonstrated strong agreement with benchmark data, with variance below 1.5%, indicating high reliability and robustness. Overall, the study establishes a novel integrative approach that bridges quantum-scale interaction modelling with macroscopic food system behaviour, demonstrating that molecular-level electronic interactions and empirical formulation variables jointly govern the structural and functional properties of hybrid protein matrices.