Development of an Aptamer Design Method Using Quantum Annealing
POSTER
Abstract
In the development of biosensing devices or next-generation pharmaceuticals, aptamers, nucleic acid molecules that bind to target molecules specifically, have attracted considerable interest. To establish an in silico design method for aptamers, we proposed and validated a novel approach utilizing quantum annealing.
For algorithmic validation, we used human α-thrombin (PDB ID: 5EW1) as the target molecule model, whose three-dimensional structure has already been solved. Initially, docking simulations were performed between the four nucleotides (monomers) and the target molecule to estimate possible monomer binding sites and binding energies. The total binding energy of cyclic (stem-loop) aptamers were defined as the objective function to explore optimal sequences from the monomer binding data. To predict candidate aptamer sequences, optimization calculations were conducted using NEC's vector annealing with constraints such as distances, angles, and lengths between nucleotides (Aptamer RIng Approach Derived from NEtwork optimization, ARIADNE). Furthermore, the predicted sequences were chemically synthesized and evaluated for binding to the target molecule using Bio-Layer Interferometry (BLI) method. Currently, we are continuing to optimize the algorithm.
For algorithmic validation, we used human α-thrombin (PDB ID: 5EW1) as the target molecule model, whose three-dimensional structure has already been solved. Initially, docking simulations were performed between the four nucleotides (monomers) and the target molecule to estimate possible monomer binding sites and binding energies. The total binding energy of cyclic (stem-loop) aptamers were defined as the objective function to explore optimal sequences from the monomer binding data. To predict candidate aptamer sequences, optimization calculations were conducted using NEC's vector annealing with constraints such as distances, angles, and lengths between nucleotides (Aptamer RIng Approach Derived from NEtwork optimization, ARIADNE). Furthermore, the predicted sequences were chemically synthesized and evaluated for binding to the target molecule using Bio-Layer Interferometry (BLI) method. Currently, we are continuing to optimize the algorithm.
*This study was supported by Acquisition, Technology & Logistics Agency and performed by NEC Solution Innovators.
Presenters
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Katsunori Horii
- NEC Solution Innovators, Ltd.