De Novo Design of Protein-Binding Peptides by Quantum Computing

Physics-based approaches to de novo drug design involve the simultaneous exploration of vast chemical and conformational spaces. The rapid development of quantum computing technologies offers a promising perspective to efficiently tackle this challenge. In this work, we focus on peptide design and present a multiscale framework that combines classical and quantum computing to optimize amino acid sequences and predict binding poses at atomic resolution. We illustrate our scheme by designing binders for several protein targets, and we contrast the performance of the D-Wave quantum annealer with that of an industry-grade classical optimizer. To assess our results, we compare the designed sequences and the corresponding poses with those available in a data set of experimentally characterized peptide binders.