Peptide conformational sampling using the Quantum Approximate Optimization Algorithm

• DOI: 10.48550/arxiv.2204.01821
• Publication Date: 2022-01-01
• Authors: Sami Boulebnane; Xavier Lucas; Agnes Meyder; Stanisław Adaszewski; Ashley Montanaro
• Keywords: Folding (DSP implementation)

Protein folding -- the problem of predicting spatial structure a protein given its sequence amino-acids has attracted considerable research effort in biochemistry recent decades. In this work, we explore potential quantum computing to solve simplified version folding. More precisely, numerically investigate performance variational algorithm, Quantum Approximate Optimization Algorithm (QAOA), sampling low-energy conformations short peptides. We start by benchmarking algorithm on an even simpler problem: self-avoiding walks, which is necessary condition for valid conformation. Motivated promising results achieved QAOA problem, then apply more complete folding, including physical potential. case, based numerical simulations 20 qubits, find less results: deep circuits are required achieve accurate results, and can be matched random up small overhead. Overall, these cast serious doubt ability address near term, extremely setting. believe that approach conclusions presented work could offer valuable methodological insights how systematically evaluate optimization algorithms real-world problems beyond