Despite major advances in antibacterial target identification, the translation of biochemically validated targets into clinically effective therapies remains inconsistent, particularly for Gram-negative pathogens. Enzymes involved in bacterial cell envelope biogenesis, such as LpxC and NagA, exemplify this disconnect. Both targets are genetically validated, structurally tractable, and extensively characterized, yet no inhibitors have reached clinical use. Here, we argue that this gap reflects limitations in early target assessment rather than intrinsic flaws in these enzymes. Using LpxC and NagA as case studies, we highlight how context-dependent essentiality, metabolic adaptability, pathway robustness, host microenvironments, and pharmacokinetic constraints collectively shape translational outcomes. We further discuss systems-level and computational approaches that expose adaptive buffering and compensatory mechanisms overlooked by classical validation paradigms. Finally, we propose a reliability-based framework for antibacterial target prioritization that integrates physiological indispensability, pathway fragility, bypass potential, and translational feasibility. Incorporating reliability-driven criteria early in discovery may improve target selection and reduce late-stage attrition in antibacterial drug development.
El-sagheir et al. (2026) studied this question.