Computational predictive toxicology modeling for assessing human health risks of novel psychoactive substances (NPS): a case study
African Journal of Drug and Alcohol Studies May 29, 2025 Abolanle A. A. Kayode, Ezekiel A. Olugbogi, Omowumi T. Kayode 3 citations
Novel psychoactive substances (NPS) pose growing health risks. Using computational tools like Maestro Schrödinger 12.8, admeSAR, Protox II, and molecular docking, researchers analyzed chemical structures, physicochemical properties, and toxicity data for known NPS compounds. Predictive models identified structural features and toxicophores linked to neurotoxicity, cardiotoxicity, hepatotoxicity, and reproductive toxicity. Metabolic pathways and bioactivation processes were also examined for their role in forming reactive metabolites that contribute to adverse health outcomes. The work aims to support regulatory and public health efforts by providing tools to assess and mitigate NPS-related harms.