Quantum Simulation of Preferred Tautomeric State Prediction

TL;DR

This paper introduces a hybrid quantum computing approach to predict the dominant tautomeric form of drug-like molecules efficiently, combining quantum chemistry and quantum algorithms to improve accuracy and resource utilization.

Contribution

It presents a novel hybrid quantum workflow utilizing active-space orbitals, efficient Hamiltonian encoding, and VQE algorithms for tautomer prediction, demonstrating feasibility on real molecules.

Findings

Predicted tautomeric states agree with CCSD benchmarks.

Achieved chemical accuracy with only eight qubits for Edaravone.

Efficient quantum resource usage with 80 two-qubit gates.

Abstract

Prediction of tautomers plays an essential role in computer-aided drug discovery. However, it remains a challenging task nowadays to accurately predict the canonical tautomeric form of a given drug-like molecule. Lack of extensive tautomer databases, most likely due to the difficulty in experimental studies, hampers the development of effective empirical methods for tautomer predictions. A more accurate estimation of the stable tautomeric form can be achieved by quantum chemistry calculations. Yet, the computational cost required prevents quantum chemistry calculation as a standard tool for tautomer prediction in computer-aided drug discovery. In this paper we propose a hybrid quantum chemistry-quantum computation workflow to efficiently predict the dominant tautomeric form. Specifically, we select active-space molecular orbitals based on quantum chemistry methods. Then we utilize efficient encoding methods to map the Hamiltonian onto quantum devices to reduce the qubit resources and circuit depth. Finally, variational quantum eigensolver (VQE) algorithms are employed for ground state estimation where hardware-efficient ansatz circuits are used. To demonstrate the applicability of our methodology, we perform experiments on two tautomeric systems: acetone and Edaravone, each having 52 and 150 spin-orbitals in the STO-3G basis set, respectively. Our numerical results show that their tautomeric state prediction agrees with the CCSD benchmarks. Moreover, the required quantum resources are efficient: in the example of Edaravone, we could achieve chemical accuracy with only eight qubits and 80 two-qubit gates.