Synergy between Experiments and Computations: A Green Channel for Revealing Metabolic Mechanism of Xenobiotics in Chemical Toxicology

Xenobiotic metabolism can lead to metabolites with altered physicochemical and biological properties, which may differ markedly from those of their parent compounds. Thus, xenobiotic metabolism has great implication for chemical safety evaluation, which has become one of the central research areas in chemical toxicology. A plethora of analytical and in vitro methods are now available for investigating the metabolic fate of xenobiotics, especially by cytochrome P450 (CYP), at a high level of detail. However, the interpretations of metabolic reactions often face some mechanistic challenges, for example, the mechanism of the initial and rate-determining step is not easily distinguished due to the transient nature of active species of CYP, and some reactive intermediates are difficult to identify. Alternatively, computational chemistry methodologies such as quantum chemical calculations have the capacity to calculate the electronic structures for enzymatic models with hundreds of atoms, thus to be able to characterize intermediates and transition states during whole metabolic reaction course from both structural and energetics aspects, which can confront some major limitations of experimental methods. In this perspective, I first introduce state of the art experimental and computational approaches for investigating xenobiotic metabolism catalyzed by CYP, respectively. Then the strategies to harvest the synergy between experiments and computations are highlighted, which can be conducted through comparison of their analytical, kinetic, or isotope effect data at a qualitative, semiquantitative, or quantitative level to determine the metabolic mechanism. Two examples are chosen to demonstrate the synergy advantage to elucidate the metabolic mechanism of triphenyl phosphate and atrazine catalyzed by CYP, respectively, which show that the interplay between experiments and computations allows greater insight to be gained than with the isolated methods.