Noga_2023_Arch.Toxicol_98_267

Reference

Title : The prediction of acute toxicity (LD(50)) for organophosphorus-based chemical warfare agents (V-series) using toxicology in silico methods - Noga_2023_Arch.Toxicol_98_267
Author(s) : Noga M , Michalska A , Jurowski K
Ref : Archives of Toxicology , 98 :267 , 2023
Abstract :

Nerve agents are organophosphate chemical warfare agents that exert their toxic effects by irreversibly inhibiting acetylcholinesterase, affecting the breakdown of the neurotransmitter acetylcholine in the synaptic cleft. Due to the risk of exposure to dangerous nerve agents and for animal welfare reasons, in silico methods have been used to assess acute toxicity safely. The next-generation risk assessment (NGRA) is a new approach for predicting toxicological parameters that can meet modern requirements for toxicological research. The present study explains the acute toxicity of the examined V-series nerve agents (n = 9) using QSAR models. Toxicity Estimation Software Tool (ver. 4.2.1 and ver. 5.1.2), QSAR Toolbox (ver. 4.6), and ProTox-II browser application were used to predict the median lethal dose. The Simplified Molecular Input Line Entry Specification (SMILES) was the input data source. The results indicate that the most deadly V-agents were VX and VM, followed by structural VX analogues: RVX and CVX. The least toxic turned out to be V-sub x and Substance 100A. In silico methods for predicting various parameters are crucial for filling data gaps ahead of experimental research and preparing for the upcoming use of nerve agents.

PubMedSearch : Noga_2023_Arch.Toxicol_98_267
PubMedID: 38051368

Related information

Inhibitor Chinese-VX    Russian-VX    EA-3148    EA-5478    VM    VS    VE    VG    VX

Citations formats

Noga M, Michalska A, Jurowski K (2023)
The prediction of acute toxicity (LD(50)) for organophosphorus-based chemical warfare agents (V-series) using toxicology in silico methods
Archives of Toxicology 98 :267

Noga M, Michalska A, Jurowski K (2023)
Archives of Toxicology 98 :267