Regensburg 2022 – scientific programme
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QI: Fachverband Quanteninformation
QI 12: Quantum Computing and Algorithms
QI 12.6: Talk
Thursday, September 8, 2022, 16:15–16:30, H8
Towards the Simulation of Large Scale Protein-Ligand Interactions on NISQ-era Quantum Computers — •Nikolaj Moll1, Fionn D. Malone2, Robert M. Parrish2, Alicia R. Welden2, Thomas Fox3, Matthias Degroote1, Elica Kyoseva1, Raffaele Santagati1, and Michael Streif1 — 1Quantum Lab, Boehringer Ingelheim, 55218 Ingelheim, Germany — 2QC Ware Corporation, Palo Alto, CA, 94301, USA — 3Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG, 88397 Biberach, Germany
Most quantum computing research for quantum chemistry applications has focused on the calculation of ground state energies, while in the pharmaceutical industry, one is often more interested in gaining insight into the interaction of drugs and proteins. The interaction energy together with entropic contributions allows the determination of the efficacy of a potential drug. Here we explore the use of symmetry-adapted perturbation theory (SAPT) as a simple means to compute interaction energies between two molecular systems with a hybrid method combing NISQ-era quantum and classical computers. From the one- and two-particle reduced density matrices of the monomer wavefunctions obtained by the variational quantum eigensolver (VQE), we compute SAPT contributions to the interaction energy. At first order, this energy yields the electrostatic and exchange contributions for non-covalently bound systems. Ideal statevector simulations show that the SAPT(VQE) interaction energy components display orders of magnitude lower absolute errors than the corresponding VQE total energies which sub kcal/mol accuracy in the SAPT interaction energies.