Fullqubit alchemist: quantum algorithm for alchemical free energy calculations

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Authors: Po‐Wei Huang, Gregory Boyd, Gian-Luca R. Anselmetti, Matthias Degroote, Nikolaj Moll, Raffaele Santagati, Michael Streif, Benjamin Ries, Daniel Marti-Dafcik, Hamza Jnane, Sophia Simon, Nathan Wiebe
+2 more Thomas R. Bromley, Bálint Koczor
Cited by: 1

Abstract

Abstract Accurately computing the free energies of biological processes is a cornerstone of computer-aided drug design, but it is a daunting task. The need to sample vast conformational spaces and account for entropic contributions makes the estimation of binding free energies very expensive. While classical methods, such as thermodynamic integration and alchemical free energy calculations, have significantly contributed to reducing computational costs, they still face limitations in terms of efficiency and scalability. We tackle this through a quantum algorithm for the estimation of free energy differences by adapting the existing Liouvillian approach and introducing several key algorithmic improvements. We directly implement the Liouvillian operator and provide an efficient description of electronic forces acting on both nuclear and electronic particles on the quantum ground state potential energy surface. This leads to super-polynomial runtime scaling improvements in the precision of our Liouvillian simulation approach and quadratic improvements in the scaling with the number of particles relative to prior quantum algorithms. Second, our algorithm calculates free energy differences via a fully quantum implementation of thermodynamic integration and alchemy, thereby foregoing expensive entropy estimation subroutines used in prior works. Our results open new avenues towards the application of quantum computers in drug discovery.

Fields of Study & Subjects

Protein Structure and Dynamics Quantum Computing Algorithms and Architecture Machine Learning in Materials Science

Publication details

Journal / source
npj Quantum Information
Publisher
Springer Science and Business Media LLC
Publication date
23 June 2026
Language
EN