Frequently Asked Questions
Quick clarifications for interpretation, tool usage, and network topology.
PMT compounds are Persistent, Mobile, and Toxic substances. They resist degradation (P), travel long distances in aquatic systems (M), and pose toxicological risks to humans and ecosystems (T).
The database stems from 140,161 unique compounds in the ZeroPM inventory. After filtering, 98,091 precursors were used to predict 13,678,364 transformation products across 42,797,878 unique reactions.
Predictions were carried out using the environmental microbial and abiotic modules of BioTransformer 4.0. Up to three reaction steps were calculated for each compound using parallel processing on an HPC cluster.
A dead-end TP is a predicted product that generates no further predicted products within the 3 model steps (and wasn't eliminated due to computational errors). In this database, 15,048 compounds were identified as dead-end TPs.
Rule-based prediction models are prone to combinatorial explosion. Limiting the predictions to three steps helps keep computation tractable while still reaching many meaningful intermediates and dead-end products.
Mobility, persistence, and toxicity are evaluated using KOC, CERAPP, and CoMPARA modules in OPERA, guided by global applicability domain (AD) indexes. A log Koc ≤ 3 indicates mobility according to EU-CLP criteria.
BioTransformer uses generalized reaction rules (e.g., adding an OH group to any secondary amine). While based on experimental data, these general rules may be applied to compounds where they wouldn't realistically occur in nature.
Rule-based models cannot predict transformation reactions for which they have no defined rules. Collecting more experimental data is crucial to create new reaction rules and address this under-prediction.
Yes, 72 of the 638 predicted PMT dead-end TPs are on NORMAN suspect lists, and at least 7 (such as TFA and cyanuric acid) have been confirmed in environmental or animal samples.
Some highly polar or low-mass compounds (like 4,5-dihydro-1H-1,2,4-triazol-5-one or 1,2,4-triazole) are challenging to detect with standard reversed-phase chromatography or lack functional groups for electrospray ionization.
Grouping original precursors that form the same dead-end TP (e.g., all compounds forming TFA) helps identify multiple sources of environmental contamination and can prevent regrettable substitution when replacing hazardous chemicals.
By identifying common substructures among original precursors (like the CF3-C group for TFA), we can flag other chemicals with these substructures as potential sources of specific dead-end TPs, speeding up prioritization.
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