In silico approaches to evaluate the molecular properties of organophosphate compounds to inhibit acetylcholinesterase activity in housefly

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).

Reducing health & environmental impacts of chemical warfare agents: Computational chemistry contributions

This review article summarizes advances in computational chemistry and cheminformatics methods and techniques that are used or have potential for use in reducing health and environmental impacts of Chemical Warfare Agents (CWA). These methods, include, but are not limited to, predictive modeling, data mining and virtual screening, similarity searching, molecular docking and dynamics and are briefly presented here. Applications of these in silico approaches, specifically for the protection of personnel and civilians against CWA, but also beyond, are discussed. CWA include toxic chemicals that can cause death, injury, or temporary incapacitation through their chemical action. CWA impose a significant worldwide threat and as such, destruction, remediation as well as protection measurements need to be carefully designed. Towards this goal computational chemistry and cheminformatics can play a key role specifically as far as decontamination, risk assessment and risk management are concerned. Among the wide range of in silico techniques applied for CWA, specific previously published paradigms are presented, including toxicity and property prediction, CWA simulant identification and CWA detoxification. Beyond CWA research, other applications with military interest are briefly presented and emerging trends of potential relevance noted.

Homology modeling, docking, molecular dynamics and in vitro studies to identify Rhipicephalus microplus acetylcholinesterase inhibitors

Rhipicephalus microplus is an important ectoparasite of cattle, causing considerable economical losses. Resistance to chemical acaricides has stimulated the search for new antiparasitic drugs, including natural products as an eco-friendly alternative of control. Flavonoids represent a class of natural compounds with many biological activities, such as enzyme inhibitors. Acetylcholinesterase is an essential enzyme for tick survival that stands out as an important target for the development of acaricides. This work aimed to predict this 3D structure by homology modeling and use the model to identify compound with inhibitory activity. The model of R. microplus AChE1 (RmAChE1) was constructed using MODELLER program. The optimization and molecular dynamic investigation were performed in GROMACS program. The model developed was used, by molecular docking, to evaluate the anticholinesterase activity of flavonoids (quercetin, rutin, diosmin, naringin and hesperidin) and an acaricide synthetic (eserine). Additionally, in vitro inhibition of AChE and larval immersion tests were performed. The model of RmAChE1 showed to be sterically and energetically acceptable. In molecular dynamics simulations, the 3D structure remains stable with Root Mean Square Deviation = 3.58 Å and Root Mean Square Fluctuation = 1.43 Å. In molecular docking analyses, only eserine and quercetin show affinity energy to the RmAChE (Gridscore: -52.17 and -39.44 kcal/mol, respectively). Among the flavonoids, quercetin exhibited the best in vitro inhibition of AChE activity (15.8%) and mortality of larvae tick (30.2%). The use of in silico and in vitro techniques has shown that quercetin showed promising anti-tick activity and structural requirements to interact with RmAChE1. Communicated by Ramaswamy H. Sarma.

Trends in the Recent Patent Literature on Cholinesterase Reactivators (2016-2019)

Acetylcholinesterase (AChE) is the key enzyme responsible for deactivating the ACh neurotransmitter. Irreversible or prolonged inhibition of AChE, therefore, elevates synaptic ACh leading to serious central and peripheral adverse effects which fall under the cholinergic syndrome spectra. To combat the toxic effects of some AChEI, such as organophosphorus (OP) nerve agents, many compounds with reactivator effects have been developed. Within the most outstanding reactivators, the substances denominated oximes stand out, showing good performance for reactivating AChE and restoring the normal synaptic acetylcholine (ACh) levels. This review was developed with the purpose of covering the new advances in AChE reactivation. Over the past years, researchers worldwide have made efforts to identify and develop novel active molecules. These researches have been moving farther into the search for novel agents that possess better effectiveness of reactivation and broad-spectrum reactivation against diverse OP agents. In addition, the discovery of ways to restore AChE in the aged form is also of great importance. This review will allow us to evaluate the major advances made in the discovery of new acetylcholinesterase reactivators by reviewing all patents published between 2016 and 2019. This is an important step in continuing this remarkable research so that new studies can begin.

Investigating the Molecular Basis of N-Substituted 1-Hydroxy-4-Sulfamoyl-2-Naphthoate Compounds Binding to Mcl1

Myeloid cell leukemia-1 (Mcl1) is an anti–apoptotic protein that has gained considerable attention due to its overexpression activity prevents cell death. Therefore, a potential inhibitor that specifically targets Mcl1 with higher binding affinity is necessary. Recently, a series of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoate compounds was reported that targets Mcl1, but its binding mechanism remains unexplored. Here, we attempted to explore the molecular mechanism of binding to Mcl1 using advanced computational approaches: pharmacophore-based 3D-QSAR, docking, and MD simulation. The selected pharmacophore—NNRRR—yielded a statistically significant 3D-QSAR model containing high confidence scores (R2 = 0.9209, Q2 = 0.8459, and RMSE = 0.3473). The contour maps—comprising hydrogen bond donor, hydrophobic, negative ionic and electron withdrawal effects—from our 3D-QSAR model identified the favorable regions crucial for maximum activity. Furthermore, the external validation of the selected model using enrichment and decoys analysis reveals a high predictive power. Also, the screening capacity of the selected model had scores of 0.94, 0.90, and 8.26 from ROC, AUC, and RIE analysis, respectively. The molecular docking of the highly active compound—C40; 4-(N-benzyl-N-(4-(4-chloro-3,5-dimethylphenoxy) phenyl) sulfamoyl)-1-hydroxy-2-naphthoate—predicted the low-energy conformational pose, and the MD simulation revealed crucial details responsible for the molecular mechanism of binding with Mcl1.