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arXiv · 2110.08163

Quantum Computational Quantification of Protein-Ligand Interactions

Josh John Mellor Kirsopp·Cono Di Paola·David Zsolt Manrique·Michal Krompiec·Gabriel Greene-Diniz·Wolfgang Guba·Agnes Meyder·Detlef Wolf·Martin Strahm·David Muñoz Ramo
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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.

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Josh John Mellor Kirsopp, Cono Di Paola, David Zsolt Manrique, Michal Krompiec, Gabriel Greene-Diniz, Wolfgang Guba, Agnes Meyder, Detlef Wolf, Martin Strahm, David Muñoz Ramo. 2021-10-15. Quantum Computational Quantification of Protein-Ligand Interactions. https://doi.org/10.1002/qua.26975

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