Quantum Computational Quantification of Protein-Ligand Interactions

Quantum Chemistry

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 β-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.

The advent of quantum mechanics at the turn of the 20th century changed the way we look at the physical sciences. For chemistry, the implications were profound, as Dirac famously noted: “the fundamental laws for the whole of chemistry are thus completely known, and the difficulty lies only in the fact that application of these laws leads to equations that are too complex to be solved.” Indeed, calculations of accurate solutions of the electronic Schrödinger equation, such as the Full Configuration Interaction method (FCI), of molecules scale exponentially with the number of atoms, rendering them applicable only to the smallest systems. Practical approximations to FCI, such as e.g. CCSD(T), touted as computational chemistry’s gold standard, do exist, but their applicability is limited: single-reference methods like CCSD(T) fail for strongly-correlated (“multireference”) systems and the formal scaling of CCSD(T) with system size is O(N7), rendering it useful only for relatively small molecules.