2019
DOI: 10.2478/acph-2019-0038
|View full text |Cite
|
Sign up to set email alerts
|

Evaluation of phenylethylamine type entactogens and their metabolites relevant to ecotoxicology – a QSAR study

Abstract: The impact of the selected entactogens and their o-quinone metabolites on the environment was explored in QSAR studies by the use of predicted molecular descriptors, ADMET properties and environmental toxicity parameters, i.e., acute toxicity in Tetrahymena pyriformis (TOX_ATTP) expressed as Th_pyr_pIGC50/mmol L−1, acute toxicity in Pimephales promelas, the fathead minnow (TOX_FHM) expressed as Minnow LC50/mg L−1, the acute toxicity in Daphnia magna (TOX_DM) expressed as Daphnia LC50/mg L−1 and bioconcentratio… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2020
2020
2021
2021

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 52 publications
0
1
0
Order By: Relevance
“…(3) ADMET Predictor TM ( https://www.simulations-plus.com/software/admetpredictor/ ) is another tool utilizing QSAR to predict ADMET parameters of compounds. Takac et al ( 2019 ) used ADMET Predictor TM to investigate the potential impact and safety profile with respect to the environment and health for 25 selected entactogen molecules. The chemical structure (including 1D and 2D) information was used as the input for ADMET Predictor TM .…”
Section: In Silico Approachesmentioning
confidence: 99%
“…(3) ADMET Predictor TM ( https://www.simulations-plus.com/software/admetpredictor/ ) is another tool utilizing QSAR to predict ADMET parameters of compounds. Takac et al ( 2019 ) used ADMET Predictor TM to investigate the potential impact and safety profile with respect to the environment and health for 25 selected entactogen molecules. The chemical structure (including 1D and 2D) information was used as the input for ADMET Predictor TM .…”
Section: In Silico Approachesmentioning
confidence: 99%