Quantum Computational Quantification of Protein-Ligand Interactions

TL;DR

This paper presents a hybrid classical-quantum workflow for quantifying protein-ligand interactions, demonstrating the first use of real quantum computers to calculate binding energies relevant for drug design.

Contribution

It introduces a novel hybrid quantum-classical method combining DMET and VQE for protein-ligand binding energy calculations on NISQ devices, pioneering its application in drug discovery.

Findings

First quantum computer application to protein-ligand binding energies.

Identifies hardware/software requirements for NISQ algorithms in drug design.

Rank-ordered BACE1 inhibitors using quantum-derived binding energies.

Abstract

We have demonstrated a prototypical hybrid classical and quantum computational workflow for the quantification of protein-ligand interactions. The workflow combines the Density Matrix Embedding Theory (DMET) embedding procedure with the Variational Quantum Eigensolver (VQE) approach for finding molecular electronic ground states. A series of $\beta$-secretase (BACE1) inhibitors is rank-ordered using binding energy differences calculated on the latest superconducting transmon (IBM) and trapped-ion (Honeywell) Noisy Intermediate Scale Quantum (NISQ) devices. This is the first application of real quantum computers to the calculation of protein-ligand binding energies. The results shed light on hardware and software requirements which would enable the application of NISQ algorithms in drug design.