Molecular Quantum Computations on a Protein

Area of Science:

• Quantum computing
• Computational chemistry
• Molecular modeling

Background:

• Accurate electronic structure calculations are crucial for understanding molecular behavior.
• Simulating large biomolecules like proteins is computationally demanding.
• Fragment-based methods offer a potential solution for scaling quantum chemistry calculations.

Purpose of the Study:

• To implement and evaluate a quantum-centric supercomputing workflow for molecular electronic structure.
• To predict the relative energies of two conformers of the 303-atom Trp-cage miniprotein.
• To assess the accuracy and impact of fragmentation on large-scale quantum chemical calculations.

Main Methods:

• Utilized a fragment-based, quantum-centric supercomputing workflow.
• Employed extended wave function-based embedding (EWF) with explicit inclusion of all atoms.
• Applied sample-based quantum diagonalization (SQD) for complex fragments and full configuration interaction (FCI) for simpler ones.
• Compared EWF-(FCI,SQD) results with EWF-MP2, EWF-CCSD, RI-MP2, and DLPNO-CCSD benchmarks.

Main Results:

• The EWF-(FCI,SQD) workflow successfully predicted relative energies for Trp-cage conformers.
• Fragmentation impact on relative energies was evaluated against unfragmented calculations.
• Demonstrated feasibility of large-scale electronic configuration interaction (CI) simulations for proteins.

Conclusions:

• The implemented quantum-centric workflow enables accurate electronic structure calculations for large biomolecules.
• Combining quantum and classical computing resources is effective for tackling complex protein simulations.
• This approach paves the way for advanced computational studies of biological systems.