Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous Abstract"Evidence for damage-dependent hygienic behaviour towards Varroa destructor-parasitised brood in the western honey bee, Apis mellifera"    Next Abstract"Host recognition by the specialist hoverfly Microdon mutabilis, a social parasite of the ant Formica lemani" »

Toxicol Sci


Title:Editor's Highlight: Identification of Any Structure-Specific Hepatotoxic Potential of Different Pyrrolizidine Alkaloids Using Random Forests and Artificial Neural Networks
Author(s):Schoning V; Hammann F; Peinl M; Drewe J;
Address:"Max Zeller Sohne AG, CH 8590 Romanshorn, Switzerland. Department of Clinical Pharmacology, University Hospital Basel, CH 4031 Basel, Switzerland. rt-mp Softwaredevelopment, D-63694 Limeshain, Germany"
Journal Title:Toxicol Sci
Year:2017
Volume:160
Issue:2
Page Number:361 - 370
DOI: 10.1093/toxsci/kfx187
ISSN/ISBN:1096-0929 (Electronic) 1096-0929 (Linking)
Abstract:"Pyrrolizidine alkaloids (PAs) are characteristic metabolites of some plant families and form a powerful defense mechanism against herbivores. More than 600 different PAs are known. PAs are ester alkaloids composed of a necine base and a necic acid, which can be used to divide PAs in different structural subcategories. The main target organs for PA metabolism and toxicity are liver and lungs. Additionally, PAs are potentially genotoxic, carcinogenic and exhibit developmental toxicity. Only for very few PAs, in vitro and in vivo investigations have characterized their toxic potential. However, these investigations suggest that structural differences have an influence on the toxicity of single PAs. To investigate this structural relationship for a large number of PAs, a quantitative structural-activity relationship (QSAR) analysis for hepatotoxicity of over 600 different PAs was performed, using Random Forest- and artificial Neural Networks-algorithms. These models were trained with a recently established dataset specific for acute hepatotoxicity in humans. Using this dataset, a set of molecular predictors was identified to predict the hepatotoxic potential of each compound in validated QSAR models. Based on these models, the hepatotoxic potential of the 602 PAs was predicted and the following hepatotoxic rank order in 3 main categories defined (1) for necine base: otonecine > retronecine > platynecine; (2) for necine base modification: dehydropyrrolizidine >> tertiary PA = N-oxide; and (3) for necic acid: macrocyclic diester >/= open-ring diester > monoester. A further analysis with combined structural features revealed that necic acid has a higher influence on the acute hepatotoxicity than the necine base"
Keywords:"Algorithms Chemical and Drug Induced Liver Injury/*etiology Cyclic N-Oxides/chemistry/classification/toxicity Databases, Factual Dicarboxylic Acids/chemistry/classification/toxicity Heterocyclic Compounds, 2-Ring/chemistry/classification/toxicity Humans L;"
Notes:"MedlineSchoning, Verena Hammann, Felix Peinl, Mark Drewe, Jurgen eng Comparative Study Validation Study 2017/10/04 Toxicol Sci. 2017 Dec 1; 160(2):361-370. doi: 10.1093/toxsci/kfx187"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 26-12-2024