QO-BRA: A Quantum Operator-Based Autoencoder for De Novo Molecular Design
Abstract
We introduce a variational quantum autoencoder tailored for de novo molecular design, named QO-BRA (Quantum Operator-Based Real Amplitude autoencoder). QO-BRA leverages quantum circuits for real-amplitude encoding and the SWAP test to estimate reconstruction and latent-space regularization errors during back-propagation. Adjoint encoder and decoder operators enable unitary transformations and a generative process that ensures accurate reconstruction, as well as the novelty, uniqueness, and validity of the generated samples. We showcase the capabilities of QO-BRA as applied to the de novo design of Ca 2+ -, Mg 2+ -, and Zn 2+ -binding metalloproteins after training the generative model with a modest data set.
Fields of Study & Subjects
Quantum Computing Algorithms and Architecture
Computational Drug Discovery Methods
Machine Learning in Materials Science
Publication details
- Journal / source
- Journal of Chemical Theory and Computation
- Volume
- 22
- Issue
- 4
- Pages
- 2059–2073
- Publication date
- 3 February 2026
- Language
- EN