mRNA codon optimization on quantum computers

Abstract

Reverse translation of polypeptide sequences to expressible mRNA constructs is a NP-hard combinatorial optimization problem. Each amino acid in the protein sequence can be represented by as many as six codons, and the process of selecting the combination that maximizes probability of expression is termed codon optimization. This work investigates the potential impact of leveraging quantum computing technology for codon optimization. An adiabatic quantum computer (AQC) is compared to a standard genetic algorithm (GA) programmed with the same objective function. The AQC is found to be competitive in identifying optimal solutions and future generations of AQCs may be able to outperform classical GAs. The utility of gate-based systems is also evaluated using a simulator resulting in the finding that while current generations of devices lack the hardware requirements, in terms of both qubit count and connectivity, to solve realistic problems, future generation devices may be highly efficient.

Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems

“…This system has more than twice as many qubits as its predecessor D-Wave 2000Q and an increase in qubit connectivity from 6 to 15 by using the Pegasus topology [12][13][14][15]. High expectations have been placed on its computational power, and first independent studies have become available [16][17][18][19][20][21][22][23]. For such a rapidly developing technology, it is an important task for independent researchers to study progress and test new developments.…”

Garden optimization problems for benchmarking quantum annealers

“…Nevertheless, we remark that before generalizing the results shown here, it would be good to verify the general trends by benchmarking these systems using other classes of problems. For similar studies, see [10,[35][36][37][38][39][40][41].…”

Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems

“…This system has more than twice as many qubits as its predecessor D-Wave 2000Q and an increase in qubit connectivity from 6 to 15 by using the Pegasus topology [11][12][13][14]. High expectations have been placed on its computational power, and first independent studies have become available [15][16][17][18][19][20][21]. For such a rapidly developing technology, it is an important task for independent researchers to study progress and test new developments.…”