Peptide conformational sampling using the Quantum Approximate Optimization Algorithm

Abstract Protein folding has attracted considerable research effort in biochemistry recent decades. In this work, we explore the potential of quantum computing to solve a simplified version protein folding. More precisely, numerically investigate performance Quantum Approximate Optimization Algorithm (QAOA) sampling low-energy conformations short peptides. We start by benchmarking algorithm on an even simpler problem: self-avoiding walks. Motivated promising results, then apply more complete folding, including physical potential. case, find less results: deep circuits are required achieve accurate and QAOA can be matched random up small overhead. Overall, these results cast serious doubt ability address problem near term, extremely setting.