Evaluation of the OECD QSAR toolbox automatic workflow for the prediction of the acute toxicity of organic chemicals to fathead minnow

The estimation of acute oral toxicity (LD50) of G-series organophosphorus-based chemical warfare agents using quantitative and qualitative toxicology in silico methods

The idea of this study was the estimation of the theoretical acute toxicity (t-LD50, rat, oral dose) of organophosphorus-based chemical warfare agents from the G-series (n = 12) using different in silico methods. Initially identified in Germany, the G-type nerve agents include potent compounds such as tabun, sarin, and soman. Despite their historical significance, there is a noticeable gap in acute toxicity data for these agents. This study employs qualitative (STopTox and AdmetSAR) and quantitative (TEST; CATMoS; ProTox-II and QSAR Toolbox) in silico methods to predict LD50 values, offering an ethical alternative to animal testing. Additionally, we conducted quantitative extrapolation from animals, and the results of qualitative tests confirmed the acute toxicity potential of these substances and enabled the identification of toxicophoric groups. According to our estimations, the most lethal agents within this category were GV, soman (GD), sarin (GB), thiosarin (GBS), and chlorosarin (GC), with t-LD50 values (oral administration, extrapolated from rat to human) of 0.05 mg/kg bw, 0.08 mg/kg bw, 0.12 mg/kg bw, 0.15 mg/kg bw, and 0.17 mg/kg bw, respectively. On the contrary, compounds with a cycloalkane attached to the phospho-oxygen linkage, specifically methyl cyclosarin and cyclosarin, were found to be the least toxic, with values of 2.28 mg/kg bw and 3.03 mg/kg bw. The findings aim to fill the knowledge gap regarding the acute toxicity of these agents, highlighting the need for modern toxicological methods that align with ethical considerations, next-generation risk assessment (NGRA) and the 3Rs (replacement, reduction and refinement) principles.

The acute toxicity of Novichok's degradation products using quantitative and qualitative toxicology in silico methods

The emergence of Novichok agents, potent organophosphorus nerve agents, has spurred the demand for advanced analytical methods and toxicity assessments as a result of their involvement in high-profile incidents. This study focuses on the degradation products of Novichok agents, particularly their potential toxic effects on biological systems. Traditional in vivo methods for toxicity evaluation face ethical and practical constraints, prompting a shift toward in silico toxicology research. In this context, we conducted a comprehensive qualitative and quantitative analysis of acute oral toxicity (AOT) for Novichok degradation products, using various in silico methods, including TEST, CATMoS, ProTox-II, ADMETlab, ACD/Labs Percepta, and QSAR Toolbox. Adopting these methodologies aligns with the 3Rs principle, emphasising Replacement, Reduction, and Refinement in the realm of toxicological studies. Qualitative assessments with STopTox and admetSAR revealed toxic profiles for all degradation products, with predicted toxicophores highlighting structural features responsible for toxicity. Quantitative predictions yielded varied estimates of acute oral toxicity, with the most toxic degradation products being EOPAA, MOPGA, MOPAA, MPGA, EOPGA, and MPAA, respectively. Structural modifications common to all examined hydrolytic degradation products involve substituting the fluorine atom with a hydroxyl group, imparting consequential effects on toxicity. The need for sophisticated analytical techniques for identifying and quantifying Novichok degradation products is underscored due to their inherent reactivity. This study represents a crucial step in unravelling the complexities of Novichok toxicity, highlighting the ongoing need for research into its degradation processes to refine analytical methodologies and fortify readiness against potential threats.

The prediction of hydrolysis and biodegradation of organophosphorus-based chemical warfare agents (G-series and V-series) using toxicology in silico methods

Nerve agents (G- and V-series) are a group of extremely toxic organophosphorus chemical warfare agents that we have had the opportunity to encounter many times on a massive scale (Matsumoto City, Tokyo subway and Gulf War). The threat of using nerve agents in terrorist attacks or military operations is still present, even with establishing the Chemical Weapons Convention as the legal framework. Understanding their environmental sustainability and health risks is critical to social security. Due to the risk of contact with dangerous nerve agents and animal welfare considerations, in silico methods were used to assess hydrolysis and biodegradation safely. The environmental fate of the examined nerve agents was elucidated using QSAR models. The results indicate that the investigated compounds released into the environment hydrolyse at a different rate, from extremely fast (<1 day) to very slow (over a year); V-agents undergo slower hydrolysis compared to G-agents. V-agents turned out to be relatively challenging to biodegrade, the ultimate biodegradation time frame of which was predicted as weeks to months, while for G-agents, the overwhelming majority was classified as weeks. In silico methods for predicting various parameters are critical to preparing for the forthcoming application of nerve agents.

The prediction of acute toxicity (LD50) for organophosphorus-based chemical warfare agents (V-series) using toxicology in silico methods

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.

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).