Acute Lung Injury (ALI) is driven by excessive oxidative stress and dysregulation of redox pathways, leading to severe pulmonary inflammation and tissue damage. Although antioxidant peptide therapeutics show significant promise, current computational design strategies rely primarily on classical molecular simulations, which do not capture essential quantum phenomena such as electron transfer and radical stabilization. This project proposes a hybrid quantum–classical multi-scale modeling framework integrating molecular dynamics simulations with QM/MM and Density Functional Theory (DFT) calculations. By incorporating electronic properties, including HOMO–LUMO analysis and radical stabilization energies, into peptide optimization, the framework aims to enhance predictive accuracy and mechanistic understanding of redox modulation in ALI. This approach establishes a scalable platform for quantum-informed precision peptide therapeutics in inflammatory lung diseases.
Marziyeh Qasemi (Mon,) studied this question.