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This demonstration validates the efficacy of hybrid quantum-classical workflows for modeling complex molecular systems like cytochrome P450nor, achieving chemical accuracy within 0.5 kcal/mol. By leveraging IonQ's trapped-ion architecture alongside classical GPU preprocessing, the workflow delivers more than double the accuracy of standard mean-field methods, marking a tangible step forward in practical applications for drug discovery and metabolic risk assessment.
QC Ware and IonQ Demonstrate Hybrid Quantum Chemistry Workflow for Drug Discovery
Insider Brief PRESS RELEASE – QC Ware today announced a technology demonstration of a hybrid quantum-classical chemistry workflow using its Promethium® platform and IonQ‘s Forte trapped-ion quantum computer via Amazon Braket. The demonstration modeled the heme active site of cytochrome P450nor, a nitric oxide reductase in the cytochrome P450 superfamily — the same superfamily whose […]
QC Ware and IonQ demonstrated a hybrid quantum-classical chemistry workflow that calculated electrostatic interaction energy for a cytochrome P450nor model within 0.5 kcal/mol of classical benchmarks. The workflow combined GPU-accelerated preprocessing through QC Ware’s Promethium platform with quantum measurements on IonQ’s Forte trapped-ion system through Amazon Braket. The demonstration used an eight-qubit active-space model and is intended…
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