Entropy Similarity-Driven Transformation Reaction Molecular Networking Reveals Transformation Pathways and Potential Risks of Emerging Contaminants in Wastewater: The Example of Sartans

The transformation pathways and risks of emerging contaminants (ECs) in wastewater remain unclear due to the limited throughput of nontarget screening. In this study, an improved method called entropy similarity-driven transformation reaction molecular networking (ESTRMN) was developed to identify transformation products (TPs) in wastewater. In detail, entropy similarity was the most effective algorithm for identifying parent-product spectrum pairs and a threshold of 0.5 for it was determined with the guarantee of high specificity. Additionally, a TP structure database predicted according to known structures and reactions was established to assist in identification. Sartan is one of the most commonly used angiotensin II receptor blocker antihypertensive drugs. Take sartans as an example, 69 TPs of sartans with confidence levels above 3 were identified by ESTRMN, 43 of which were newly discovered. The most common reactions included hydroxylation, hydrolysis, and oxidation, resulting in the majority of sartan TPs exhibiting higher persistence, mobility, and toxicity (PMT) than their parents. The concentration of 75% sartans and TPs increased after treatment in a WWTP, and the overall risk has not been effectively mitigated. This study emphasizes the role of ESTRMN in incorporating TPs of ECs into environmental monitoring protocols and risk assessment frameworks for wastewater management.