Quantum-Centric Alchemical Free Energy Calculations.

Area of Science:

• Computational Chemistry
• Quantum Computing
• Biomolecular Simulations

Background:

• Alchemical free energy (AFE) predictions are crucial for understanding molecular interactions.
• Current methods often rely on classical approximations, limiting accuracy for systems with significant electronic correlation.
• Integrating high-level electronic structure methods into AFE workflows is challenging.

Purpose of the Study:

• To develop and validate a hybrid quantum-classical workflow for AFE predictions.
• To incorporate configuration interaction (CI) calculations into the book-ending framework.
• To assess the feasibility of using quantum processing units (QPUs) for accurate free energy calculations.

Main Methods:

• Extended the book-ending framework with a hybrid quantum-classical workflow.
• Developed an interface for CI calculations using classical (PySCF) and quantum-centric (SQD, ext-SQD) backends.
• Computed book-ending corrections for hydration free energies (HFEs) of small organic molecules using quantum hardware.

Main Results:

• Successfully incorporated CI-level electronic structure calculations into AFE workflows.
• CI-corrected HFEs showed reasonable agreement with experimental values.
• Demonstrated the feasibility of QPU-accelerated free energy predictions.

Conclusions:

• Hybrid quantum-classical workflows can enhance the accuracy of AFE predictions.
• Quantum hardware offers a scalable route to CI-quality electronic structure data.
• This approach has potential applications in modeling molecular recognition, enzyme catalysis, and drug-receptor interactions.