NH-1

Nitrogen mustards are potent alkylating agents originally developed as chemical warfare agents and later adapted for medical applications. Despite their well-documented toxicity, systematic studies on their acute toxicity profiles remain limited. Addressing this gap, the present study offers a comprehensive in silico evaluation of nitrogen mustards, employing both qualitative and quantitative computational models. Using advanced in silico tools, the toxicity of these compounds was assessed across multiple exposure routes, including oral, dermal, and inhalation pathways. Qualitative predictions conducted with STopTox, ADMETlab, and admetSAR consistently classified nitrogen mustards as highly toxic, particularly via inhalation and dermal exposure. Key toxicophores, such as ethylenimine moieties (-N(CH₂CH₂Cl)₂), were identified as primary contributors to their cytotoxicity and DNA alkylation potential. Quantitative analyses using TEST, ProTox-III, VEGA, QSAR Toolbox, and Percepta ACD/Labs revealed considerable variability in LD₅₀ and LC₅₀ estimates across different models. The LD₅₀ values confirmed the high toxicity potential of these compounds, with HN-2 emerging as the most hazardous, particularly in inhalation exposure scenarios. This study underscores the challenges associated with computational toxicity modeling, including inter-model variability and the dependence on structural analogs. Despite these limitations, in silico methodologies provide a rapid and cost-effective alternative to experimental toxicity assessments, helping to reduce reliance on in vivo testing. Further research should focus on refining predictive models, expanding training datasets, and integrating in vitro validation studies to enhance the accuracy of toxicity predictions. The findings highlight the critical role of computational toxicology in assessing chemical threats and developing mitigation strategies for nitrogen mustard exposure.