Searching Candidate Sequences for RNA Aptamers Using Quantum Computation

Addressing the problems of increasing time and cost for drug discovery is becoming more and more important. RiboNucleic Acid (RNA) aptamers have recently attracted attention as an emerging class of medium-molecule pharmaceuticals. However, searching the candidate sequences with conventional computers within a realistic timeframe is difficult due to the large search space. To overcome this problem, we employ Ising machines such as annealing quantum computers, which solve combinatorial optimization problems formulated as Quadratic Unconstrained Binary Optimization (QUBO) problems. In this study, we formulated the aptamer-sequence search problem as a QUBO problem based on the Systematic Evolution of Ligands by EXponential enrichment (SELEX) experimental data. We demonstrated that candidate RNA sequences were generated from a real Ising machine experiment and that those sequences can bind to the target protein. We concluded that our method is an efficient way to discover aptamers.