From target specificity to metabolic efficiency: Design and optimization of etomidate analogues for potential improvement in postoperative outcomes

While transient perioperative side effects of intravenous anesthetics are often tolerated, the persistent postoperative sequelae resulting from drug accumulation pose a critical threat to patient safety. Etomidate, introduced in the 1970s, remains favored for its minimal hemodynamic impact but is severely limited by sustained adrenal suppression, leading to higher mortality and poorer outcomes in critically ill patients. To address these challenges, we reframed our strategy from solely optimizing receptor specificity to enhancing metabolic efficiency, thereby reducing prolonged postoperative exposure and mitigating sustained adverse effects. Using a deep-learning based molecule optimization algorithm, we identified metabolically favorable lead compounds and synthesized 31 novel imidazole-based etomidate derivatives. Among these, ETO-4 emerged as the most promising candidate, retaining potent anesthetic activity while accelerating metabolic clearance and significantly diminishing adrenal suppression. Plasma cortisol assays confirmed the effect of ETO-4 on adrenal function is greatly reduced. These findings underscore a paradigm shift in anesthetic drug design, demonstrating that prioritizing enhanced metabolic profiles can yield safer, more effective agents that improve postoperative outcomes.