Discrete-time quantum walks reveal critical residues involved in long-range interactions in proteins

Abstract: Long-range interactions between residues in proteins underlie diverse biological processes such as signal transmission, conformational regulation, and catalysis. Identifying residues that mediate such communication remains a major challenge. Herein, we introduce a framework based on quantum walks and entropy, and employ it on protein structures to predict important residues participating in long-range interactions. The selected proteins have been well-studied experimentally in literature. Our approach models information flow through protein contact networks using discrete-time quantum walk dynamics, where quantum superposition and interference govern transition amplitudes at the residue level. Normalized time-averaged transition probabilities quantify interaction strength between residues, while Shannon entropy calculations identify residues exhibiting delocalized interaction behavior. We find that the residues identified by us are known to be structurally and functionally important in literature. We experimentally validate our formalism on As LOV2 (PDB: 2V0U) using site-directed mutagenesis, protein purification, and dark-recovery kinetics. The predicted residues are important for understanding the mechanism of photosensing in As LOV2. Significance: This study bridges quantum transport theory and structural biology by introducing discrete-time quantum walks as a mechanism to model communication between residues. We provide a scalable and interpretable method to predict key residues, without requiring molecular dynamics or prior functional annotation. The present method, inspired by quantum physics and quantum information, and validated by experiments, offers a broad and robust framework to study communication in biomolecular systems. It further demonstrates how quantum principles such as coherence and interference can enhance our understanding of information flow in biological macromolecules.