A Quantum Strategy for the Simulation of Large Proteins: From Fragmentation in Small Proteins to Scalability in Complex Systems

We present a scalable and resource-aware framework for the quantum simulation of large proteins, grounded in systematic molecular fragmentation, analytical Toffoli gate modeling, and empirical validation. The ground-state energy of a target biomolecule is reconstructed from capped amino acid fragments, with fixed corrections to account for artificial boundaries. Analytical cost estimates—derived from reduced Hamiltonians—are benchmarked against empirical Toffoli counts using PennyLane’s resource estimation module. Our model maintains predictive accuracy across biologically relevant systems of up to 1852 electrons, capturing consistent patterns across diverse fragments. This framework enables early-stage feasibility assessments for achieving quantum advantage in biochemical simulation pipelines.