Quantum Information in Protein Structure Prediction: A Geometric Modeling Framework

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Information is rapidly emerging as a transformative technology with the potential to revolutionize various fields, including chemistry and biology. Protein structure prediction, a cornerstone of biological research, has long been a significant challenge. This paper proposes a novel framework, Quantum Information in Protein Structure Prediction, that leverages quantum information and geometric modeling to enhance prediction accuracy. We explore the potential of quantum entanglement to model protein geometries and utilize geometric information to guide structure prediction. The core mechanism centers on employing quantum entanglement to establish a fundamental basis for the protein's structure, ultimately improving predictive capabilities. This work addresses a longstanding gap in the field by integrating quantum principles with geometric computation, offering a fundamentally new approach to protein structure determination.

DOI: 10.5281/zenodo.22185200

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