Mechanism-Based Inactivation of Cytochrome P450 Enzymes: Computational Insights

Mechanism-based inactivation (MBI) refers to the metabolic bioactivation of a xenobiotic by cytochrome P450s to a highly reactive intermediate which subsequently binds to the enzyme and leads to the quasi-irreversible or irreversible inhibition. Xenobiotics, mainly drugs with specific functional units, are the major sources of MBI. Two possible consequences of MBI by medicinal compounds are drug-drug interaction and severe toxicity that are observed and highlighted by clinical experiments. Today almost all of these latent functional groups (e.g., thiophene, furan, alkylamines, etc.) are known, and their features and mechanisms of action, owing to the vast experimental and theoretical studies, are determined. In the past decade, molecular modeling techniques, mostly density functional theory, have revealed the most feasible mechanism that a drug undergoes by P450 enzymes to generate a highly reactive intermediate. In this review, we provide a comprehensive and detailed picture of computational advances toward the elucidation of the activation mechanisms of various known groups with MBI activity. To this aim, we briefly describe the computational concepts to carry out and analyze the mechanistic investigations, and then, we summarize the studies on compounds with known inhibition activity including thiophene, furan, alkylamines, terminal acetylene, etc. This study can be reference literature for both theoretical and experimental (bio)chemists in several different fields including rational drug design, the process of toxicity prevention, and the discovery of novel inhibitors and catalysts.

Automated summary

Mechanism-based inactivation (MBI) refers to the metabolic bioactivation of xenobiotics by cytochrome P450s, leading to the formation of highly reactive intermediates that irreversibly inhibit the enzyme. Medicinal compounds undergoing MBI may result in drug-drug interactions and severe toxicity, as observed in clinical experiments. Advances in computational modeling have helped elucidate the activation mechanisms of various functional groups with MBI activity, providing valuable insights for drug design, toxicity prevention, and the discovery of inhibitors and catalysts.