Quantum computational quantification of protein–ligand interactions

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 mole...

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Bibliographic Details
Published in:International journal of quantum chemistry 2022-11, Vol.122 (22), p.n/a
Main Authors: Kirsopp, Josh J. M., Di Paola, Cono, Manrique, David Zsolt, Krompiec, Michal, Greene‐Diniz, Gabriel, Guba, Wolfgang, Meyder, Agnes, Wolf, Detlef, Strahm, Martin, Muñoz Ramo, David
Format: Article
Language:English
Subjects:
Algorithms
Binding energy
Chemistry
Embedding
Ligands
Mathematical analysis
Physical chemistry
Proteins
Quantum computers
Quantum physics
Workflow
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Summary: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 (Quantinuum) 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. A simplified schematic of a prototypical, quantum‐classical workflow for rank‐ordering ligand binding affinities.
ISSN:0020-7608
1097-461X
DOI:10.1002/qua.26975