Quantum and classical computational synergy for emerging contaminants management: Advanced insights into cytochrome P450 metabolic mechanisms

Abstract

Computational toxicology provides the basis for the accurate assessment and prediction of toxic effects at the molecular level. However, classical computing often lacks speed and accuracy for complex chemical systems, leading to bottlenecks. The emergence of quantum computing has the potential to fundamentally break through these constraints, allowing the exploration of toxic effects from molecular initiation events (MIEs). This review prospects the application of quantum computing in environmental science. It provides a brief overview of classical computational chemistry and quantum computing, elucidating the quantitative mapping between these two approaches. Cytochrome P450 (CYP) enzymes, an important biomarker for monitoring and identifying environmental risks of pollutants, is taken as an example to summarize the progress of classical algorithms in explaining its metabolic mechanism. By comparing the required runtimes of quantum and classical computing approaches, the review highlights the potential quantum advantage in high-precision chemical simulations, especially in large-scale CYP model calculations. A hybrid quantum-classical strategy is specially developed for the practical workflow of quantum computing in environmental science. By means of the close collaboration between theory and experiment, it shows great potential in deeply understanding the environmental impact of emerging pollutants and designing relevant environmental monitoring programs. This review can provide valuable clues for future sustainable solutions. Through the effective synergy between quantum computing development and precision management of environmental pollution, it is expected to revolutionize the way we understand and mitigate the impacts of emerging pollutants.