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TRUVACE RECORD VERSION
record: TRV-2026-1306
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-07T06:56:59.009130Z
status: published
lens: g_space
sector: health
headline: Mechanistic insight into Metabolic Activation Mechanism of Aniline Disinfection Byproducts catalyzed by P450 Enzymes from Distinct Species: N-hydroxylation Mechanism
dek: Disinfection by-products (DBPs) are emerging environmental pollutants generated from reactions between disinfectants and precursor compounds in the water treatment, which pose a serious toxicity effect to the ecological environment and human health. Metabolism, especially by P450 enzymes, is responsible for both the toxification and detoxification of xenobiotics in humans and other organisms. Multidisciplinary theoretical approaches utilizing density functional theory (DFT), quantitative structure-activity relat…
gain_title: Researchers developed a machine learning driven QSAR model using four molecular descriptors to predict energy barriers for N-hydroxylation of aniline disinfection byproducts, achieving R2 around 0.8.
problem_title: (none)
trace_subject: (none)
gain_reading: Researchers developed a machine learning driven QSAR model using four molecular descriptors to predict energy barriers for N-hydroxylation of aniline disinfection byproducts, achieving R2 around 0.8.
gain_evidence: A machine learning driven QSAR model is developed to predict the energy barriers of the rate-determining step involved in N-hydroxylation for AN-DBPs
problem_reading: (none)
problem_evidence: (none)
quick_read: Published October 3 2026, researchers investigated how P450 enzymes metabolize aniline disinfection byproducts formed during water treatment. Using high-throughput DFT, QM/MM for 2,6-dichloroaniline across four species, and a machine learning driven QSAR model with four Mordred descriptors, they found N-hydroxylation is feasible with OH rebound as the rate-determining step, built a predictive model with R2 approximately 0.8, and observed zebrafish P450 as most readily activated.

The work matters because it suggests biotransformation may increase rather than decrease hazard, as in silico predictions showed metabolites with higher predicted toxicity than parent compounds. This informs risk evaluation for water treatment byproducts, but remains computational, without experimental toxicity confirmation, and limited to modeled barriers and four species.
limitation: Findings rely on computational predictions rather than experimental validation; toxicity is predicted in silico and QSAR accuracy is moderate with R2 approximately 0.8, and QM/MM comparison limited to four species and one representative compound.
tag: Evidence-backed gain
key_points: High-throughput DFT calculations identified N-hydroxylation as feasible metabolic pathway with OH rebound as rate-determining step. | QM/MM calculations for 2,6-dichloroaniline across four species found zebrafish P450 enzyme most readily activated upon exposure to AN-DBPs. | In silico toxicity predictions indicated P450-mediated metabolites exhibit higher predicted toxicity than parent aniline disinfection byproducts.
rundown: The study combined density functional theory, QM/MM, and a Mordred-descriptor QSAR model to characterize N-hydroxylation of aniline DBPs. DFT identified the OH rebound reaction as the rate-determining step, and the QSAR model was trained to predict its barriers.

QM/MM analysis of 2,6-dichloroaniline metabolism by P450 enzymes from four distinct species provided structural details for H-abstraction and OH rebound pathways, with zebrafish showing the lowest activation barrier and thus most ready metabolic activation.
sources:
- peer_reviewed | Environmental Pollution | https://doi.org/10.1016/j.envpol.2026.129279 | 2026-10-03
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