RinQ: Towards predicting central sites in proteins on current quantum computers

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.

Authors

Publication Details

Journal
Materials Today Quantum
Published
2025-09-01
DOI
https://doi.org/10.1016/j.mtquan.2025.100053
Citations
2
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
4.96
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article

RinQ: Towards predicting central sites in proteins on current quantum computers

Shah Ishmam Mohtashim
2 citations
Materials Today Quantum
Quantum Computing Algorithms and Architecture
4.96
article

RinQ: Towards predicting central sites in proteins on current quantum computers

Shah Ishmam Mohtashim
article en
2 citations

Abstract

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.

Materials Today QuantumVol. 7
Openalex Percentile: Top 5%
Quantum Computing Algorithms and Architecture
4.96
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RinQ: Towards predicting central sites in proteins on current quantum computers — Shah Ishmam Mohtashim · Materials Today Quantum (2025) | TGRS Research Map | TGRS