Determining the Relative Binding Affinity of Ricin Toxin A Inhibitors by Using Molecular Docking and Nonequilibrium Work

A novel approach to assess the health risk of aryl hydrocarbon receptor-bound contaminants via inhalation exposure using CYP1A1 expression as a biomarker

Polycyclic aromatic hydrocarbons (PAHs) and dioxins are potential causes of multiple diseases by activating the aryl hydrocarbon receptor (AhR) pathway. Health risk assessment of chemicals primarily relies on the relative potency factor (RPF), although its accuracy may be limited when solely using EC50 values. The induction of cytochrome P4501A1 (CYP1A1) serves as a biomarker for AhR activation and is an integrator of dioxin-like toxicity. Here, we present a method for evaluating the risks associated with AhR activation using mathematical models of dose-CYP1A1 induction. The dose-effect curves for certain PAHs and dioxins, including Ant, BghiP, 1,2,3,4,7,8-HxCDD, and others, exhibited a non-classical S-shaped form. The toxic equivalent factor (TEF) profiles revealed a broad range of toxic equivalent factor values. The TEFs for PAHs ranged from approximately 0.01 to 6, with higher values being observed when the concentration was less than 10-10 M, with the exceptions of Ace, Phe, and BghiP. Most congeners of dioxins got the lowest TEF value at around 10-10 M, ranging from 0.04 to 1.00. The binding affinity of AhR to ligands did not display a strong correlation with the EC50 of CYP1A1 expression, suggesting that the AhR-mediated effects of PAHs and dioxins are not fixed but instead fluctuate with the dose. Air samples acquired from a parking area were used to compare the proficiency of RPF and our current approach. In the current method, naphthalene and chrysene were the primary contributors of PAHs to AhR-mediated risks in parking lots air samples, respectively. However, the contributions of naphthalene and chrysene could be disregarded in the RPF approach.

The strategy for estrogen receptor mediated-risk assessment in environmental water: A combination of species sensitivity distributions and in silico approaches

Risk assessment for molecular toxicity endpoints of environmental matrices may be a pressing issue. Here, we combined chemical analysis with species sensitivity distributions (SSD) and in silico docking for multi-species estrogen receptor mediated-risk assessment in water from Dongjiang River, China. The water contains high levels of phenolic endocrine-disrupting chemicals (PEDCs) and phthalic acid esters (PAEs). The concentration of ∑₄PEDCs and ∑₆PAEs ranged from 2202 to 3404 ng/L and 834-4368 ng/L, with an average of 3241 and 2215 ng/L, respectively. The SSD approach showed that 4-NP, BPA, E2 of PEDCs, and DBP, DOP, and DEHP could severely threaten the aquatic ecosystems, while most other target compounds posed low-to-medium risks. Moreover, binding affinities from molecular docking among PEDCs, PAEs, and estrogen receptors (ERα, Erβ, and GPER) were applied as toxic equivalency factors. Estrogen receptor-mediated risk suggested that PEDCs were the main contributors, containing 53.37-69.79% of total risk. They potentially pose more severe estrogen-receptor toxicity to zebrafish, turtles, and frogs. ERβ was the major contributor, followed by ERα and GPER. This study is the first attempt to assess the estrogen receptor-mediated risk of river water in multiple aquatic organisms. The in silico simulation approach could complement toxic effect evaluations in molecular endpoints.

Ecological and AhR-mediated risk assessment of polycyclic aromatic hydrocarbons and polybrominated diphenyl ethers on multiple aquatic species in river water: A combined chemical analysis and in silico approach

Assessing the adverse health risks at molecular endpoints to various aquatic organisms could be an urgent issue. In this manuscript, the ecological and AhR-mediated risk of sixteen polycyclic aromatic hydrocarbons (PAHs) and six polybrominated diphenyl ethers (PBDEs) in surface water of Dongjiang River, Southern China was evaluated using chemical analysis and in silico approaches. Average concentrations of ∑₁₆PAHs and ∑₆PBDEs were 586.3 ng/L and 2.672 ng/L in the dry season (DS), and 366.8 ng/L and 2.554 ng/L in the wet season (WS). Concentrations of PAHs during the DS were significantly higher than that in the WS, while no obvious seasonal distribution was observed for PBDEs. Only Ant and BaP in all congers of PAHs posed low to medium ecological risks, and PBDEs posed a low ecological risk. Moreover, AhR-mediated risk from PAHs was two orders of magnitude higher that from PBDEs, and the AhR-mediated toxicity on frog and eel were higher than those on other aquatic organisms in Dongjiang River. Phe and BDE209 were the significant contributor to the AhR-mediated risk induced by PAHs and PBDEs, respectively. This study is the first attempt to assess AhR-mediated risk of river water in multiple aquatic organisms.

Integration of Molecular Docking Analysis and Molecular Dynamics Simulations for Studying Food Proteins and Bioactive Peptides

In silico tools, such as molecular docking, are widely applied to study interactions and binding affinity of biological activity of proteins and peptides. However, restricted sampling of both ligand and receptor conformations and use of approximated scoring functions can produce results that do not correlate with actual experimental binding affinities. Molecular dynamics simulations (MDS) can provide valuable information in deciphering functional mechanisms of proteins/peptides and other biomolecules, overcoming the rigid sampling limitations in docking analysis. This review will discuss the information related to the traditional use of in silico models, such as molecular docking, and its application for studying food proteins and bioactive peptides, followed by an in-depth introduction to the theory of MDS and description of why these molecular simulation techniques are important in the theoretical prediction of structural and functional dynamics of food proteins and bioactive peptides. Applications, limitations, and future prospects of MDS will also be discussed.

Assessment of epigenotoxic profiles of Dongjiang River: A comprehensive of chemical analysis, in vitro bioassay and in silico approach

This research explored the occurrence, epigenetic toxic profiling and main toxic pollutants of POPs in surface water of Dongjiang River, southern China. The concentrations of selected POPs including polycyclic aromatic hydrocarbons (PAHs), endocrine disrupting chemicals (EDCs), phthalate esters (PAEs) and polybrominated diphenyl ethers (PBDEs) of surface water from 18 sites were investigated. ∑₁₆PAHs and ∑₄EDCs were at a moderate level, while ∑₆PAEs and ∑₆PBDEs had low pollution levels. PAHs, EDCs and PAEs showed higher concentrations in dry season than those in wet season, and the loading of selected POPs in tributaries was higher than those in mainstream due to intensive manufactures and lower runoff volume. Moreover, activities of DNA methyltransferase (DNMT)1, histone deacetylase (HDAC2, HDAC8) were confirmed to be sensitive indicators for epigenetic toxicity. The DNMT1-mediated epigenetic equivalency toxicity of organic extracts in Dongjiang River were more serious than those of HDAC2 and HDAC8. Correlation analysis shown binding affinity between POPs and DNMT1, HDAC2 and HDAC8 could be regarded as toxic equivalency factors. Risk assessment suggested that 4-nonylphenol and bisphenol A were the largest contributors to epigenetic risk. This study is the first attempt to quantify epigenetic toxicity and epigenetic risk evaluation of river water.

Thermochemical and Quantum Descriptor Calculations for Gaining Insight into Ricin Toxin A (RTA) Inhibitors

In this work, we performed a study to assess the interactions between the ricin toxin A (RTA) subunit of ricin and some of its inhibitors using modern semiempirical quantum chemistry and ONIOM quantum mechanics/molecular mechanics (QM/MM) methods. Two approaches were followed (calculation of binding enthalpies, ΔH _bind, and reactivity quantum chemical descriptors) and compared with the respective half-maximal inhibitory concentration (IC₅₀) experimental data, to gain insight into RTA inhibitors and verify which quantum chemical method would better describe RTA-ligand interactions. The geometries for all RTA-ligand complexes were obtained after running classical molecular dynamics simulations in aqueous media. We found that single-point energy calculations of ΔH _bind with the PM6-DH+, PM6-D3H4, and PM7 semiempirical methods and ONIOM QM/MM presented a good correlation with the IC₅₀ data. We also observed, however, that the correlation decreased significantly when we calculated ΔH _bind after full-atom geometry optimization with all semiempirical methods. Based on the results from reactivity descriptors calculations for the cases studied, we noted that both types of interactions, molecular overlap and electrostatic interactions, play significant roles in the overall affinity of these ligands for the RTA binding pocket.

Discovery of RTA ricin subunit inhibitors: a computational study using PM7 quantum chemical method and steered molecular dynamics

Ricin is a potent toxin derived from the castor bean plant and comprises two subunits, RTA and RTB. Because of its cytotoxicity, ricin has alarmed world authorities for its potential use as a chemical weapon. Ricin also affects castor bean agribusiness, given the risk of animal and human poisoning. Over the years, many groups attempted to propose small-molecules that bind to the RTA active site, the catalytic chain. Despite such efforts, there is still no effective countermeasure against ricin poisoning. The computational study carried out in the present work renews the discussion about small-molecules that may inhibit this toxin. Here, a structure-based virtual screening protocol capable of discerning active RTA inhibitors from inactive ones was performed to screen over 2 million compounds from the ZINC database to find novel scaffolds that strongly bind into the active site of the RTA. Besides, a novel score method based on ligand undocking force profiles and semi-empirical quantum chemical calculations provided insights into the rescore of docking poses. Summing up, the filtering steps pointed out seven main compounds, with the SCF00-451 as a promising candidate to inhibit the killing activity of such potent phytotoxin.

Ligand-Based Virtual Screening, Molecular Docking, Molecular Dynamics, and MM-PBSA Calculations towards the Identification of Potential Novel Ricin Inhibitors

Ricin is a toxin found in the castor seeds and listed as a chemical weapon by the Chemical Weapons Convention (CWC) due to its high toxicity combined with the easiness of obtention and lack of available antidotes. The relatively frequent episodes of usage or attempting to use ricin in terrorist attacks reinforce the urge to develop an antidote for this toxin. In this sense, we selected in this work the current RTA (ricin catalytic subunit) inhibitor with the best experimental performance, as a reference molecule for virtual screening in the PubChem database. The selected molecules were then evaluated through docking studies, followed by drug-likeness investigation, molecular dynamics simulations and Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) calculations. In every step, the selection of molecules was mainly based on their ability to occupy both the active and secondary sites of RTA, which are located right next to each other, but are not simultaneously occupied by the current RTA inhibitors. Results show that the three PubChem compounds 18309602, 18498053, and 136023163 presented better overall results than the reference molecule itself, showing up as new hits for the RTA inhibition, and encouraging further experimental evaluation.