We introduce RinQ, a hybrid quantum-classical framework for identifying functionally critical residues in proteins by formulating centrality detection as a Quadratic Unconstrained Binary Optimization (QUBO) problem. Protein structures are modeled as residue interaction networks (RINs), and the QUBO formulations are solved using D-Wave's simulated annealing. Applied to a diverse set of proteins, RinQ consistently identifies central residues that closely align with classical benchmarks, demonstrating both the accuracy and robustness of the approach.
@article{arxiv.2508.01501,
title = {RinQ: Towards predicting central sites in proteins on current quantum computers},
author = {Shah Ishmam Mohtashim},
journal= {arXiv preprint arXiv:2508.01501},
year = {2025}
}