Molecular Quantum Computations on a Protein

TL;DR

This paper demonstrates a quantum-classical hybrid workflow for calculating molecular electronic structures of large proteins, showing that quantum computing can be integrated into protein simulations for accurate energy predictions.

Contribution

It introduces a fragment-based quantum workflow employing wave function embedding and quantum diagonalization, enabling large-scale protein electronic structure calculations.

Findings

Quantum workflow accurately predicts conformer energies.

Quantum diagonalization effectively handles challenging fragments.

Large protein systems can be simulated with combined quantum-classical methods.

Abstract

This work presents the implementation of a fragment-based, quantum-centric supercomputing workflow for computing molecular electronic structure using quantum hardware. The workflow is applied to predict the relative energies of two conformers of the 300-atom Trp-cage miniprotein. The methodology employs wave function-based embedding (EWF) as the underlying fragmentation framework, in which all atoms in the system are explicitly included in the CI treatment. CI calculations for individual fragments are performed using either sample-based quantum diagonalization (SQD) for challenging fragments or full configuration interaction (FCI) for trivial fragments. To assess the accuracy of SQD for fragment CI calculations, EWF-(FCI,SQD) results are compared against EWF-MP2 and EWF-CCSD benchmarks. Overall, the results demonstrate that large-scale electronic configuration interaction (CI) simulations of protein systems containing hundreds or even thousands of atoms can be realized through the combined use of quantum and classical computing resources.