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Satheesh S, El-Sherbiny MM. Toxicity assays and in silico approach to assess the impacts of chlorine dioxide on survival, respiration and some biochemical markers of marine zooplankton. MARINE ENVIRONMENTAL RESEARCH 2024; 197:106469. [PMID: 38531260 DOI: 10.1016/j.marenvres.2024.106469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/24/2024] [Accepted: 03/19/2024] [Indexed: 03/28/2024]
Abstract
Chlorination is the common antifouling method in desalination and power plant water intake structures to control microbial and macrofouling growth. In this study, the impacts of chlorine dioxide on toxicity, metabolic activity and biochemical markers like glutathione S-transferase and catalase enzyme activity were tested using four zooplankton species (Centropages sp., Acartia sp., Oncaea sp., and Calanus sp.) collected from the Red Sea. The zooplankton species were treated with different concentrations (0.02, 0.05, 0.1, 0.2, and 0.5 mg L-1) of chlorine dioxide. Further, chlorite, the main decomposition product of chlorine dioxide, was used for molecular docking studies against glutathione S-transferase and catalase enzymes. The results indicated the LC50 range of 0.552-1.643 mg L-1 for the studied zooplankton species. The respiration rate of the zooplankton increased due to the chlorine dioxide treatment with a maximum of 0.562 μg O2 copepod h-1 in Acartia. The glutathione S-transferase and catalase enzyme activities showed elevated values in zooplankton treated with chlorine dioxide. Molecular docking of chlorite with enzymes involved in antioxidant defense activity, such as glutathione S-transferase and catalase enzyme showed weak interactions. Overall, this study yielded significant insights for understanding the effects of chlorine dioxide on the survival, metabolism, and biochemical composition of marine zooplankton.
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Affiliation(s)
- S Satheesh
- Department of Marine Biology, Faculty of Marine Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
| | - M M El-Sherbiny
- Department of Marine Biology, Faculty of Marine Sciences, King Abdulaziz University, Jeddah, Saudi Arabia; Department of Marine Sciences, Faculty of Science, Suez Canal University, Ismailia, 41522, Egypt
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2
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Hussain R, Graham U, Elder A, Nedergaard M. Air pollution, glymphatic impairment, and Alzheimer's disease. Trends Neurosci 2023; 46:901-911. [PMID: 37777345 DOI: 10.1016/j.tins.2023.08.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 07/12/2023] [Accepted: 08/29/2023] [Indexed: 10/02/2023]
Abstract
Epidemiological evidence demonstrates a link between air pollution exposure and the onset and progression of cognitive impairment and Alzheimer's disease (AD). However, current understanding of the underlying pathophysiological mechanisms is limited. This opinion article examines the hypothesis that air pollution-induced impairment of glymphatic clearance represents a crucial etiological event in the development of AD. Exposure to airborne particulate matter (PM) leads to systemic inflammation and neuroinflammation, increased metal load, respiratory and cardiovascular dysfunction, and sleep abnormalities. All these factors are known to reduce the efficiency of glymphatic clearance. Rescuing glymphatic function by restricting the impact of causative agents, and improving sleep and cardiovascular system health, may increase the efficiency of waste metabolite clearance and subsequently slow the progression of AD. In sum, we introduce air pollution-mediated glymphatic impairment as an important mechanistic factor to be considered when interpreting the etiology and progression of AD as well as its responsiveness to therapeutic interventions.
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Affiliation(s)
- Rashad Hussain
- Center for Translational Neuromedicine, University of Rochester, Rochester, NY 14642, USA.
| | | | - Alison Elder
- Department of Environmental Medicine, University of Rochester, Rochester, NY 14642, USA
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, University of Rochester, Rochester, NY 14642, USA; Center for Translational Neuroscience, University of Copenhagen, 2200 Copenhagen, Denmark.
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3
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Singh AK, Bilal M, Barceló D, Iqbal HMN. A predictive toolset for the identification of degradation pattern and toxic hazard estimation of multimeric hazardous compounds persists in water bodies. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 824:153979. [PMID: 35181354 DOI: 10.1016/j.scitotenv.2022.153979] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 02/10/2022] [Accepted: 02/14/2022] [Indexed: 02/08/2023]
Abstract
An array of industrial processing units generates many multimeric hazardous compounds, such as complex technical lignin and its toxic derivatives, thereby persist in expelled water bodies. The inclusion of some group of motifs in the complex technical lignin structure helps it resist degrade biologically, most often even recalcitrant. Relatively small concentrations of lignin are harmful to aquatic organisms and can trigger environmental hazards. Sadly, the entire biotransformation pathway and insightful information about these toxic derivatives are incomplete and missing in the literature. This is mainly because the current conventional treatments often fail to identify all transformed compounds and their environmental fate. Thus, a robust toolset is much needed to cover this literature gap. Inadequate performance of conventional remediation processes and biological degradation patterns can be maximally optimized with the aid of predictive toolset methods that could offer better degradability and complete transformed compound information. A predictive toolset-assisted biodegradation pattern determination is a multifaceted and reliable analytical technique that can help to overcome existing shortcomings by providing an entire transformation pathway. Considering the above critiques, this work reports on the degradation pattern, and toxicological endpoints of five hazardous compounds, i.e., 2-chlorosyringaldehyde, 5-chlorovanillin, catechol, guaiacyl 4-O-5 guaiacyl, and syringyl β-O-4 syringyl β-O-4 sinapyl alcohol, that persists in water matrices. The predictive transformation pattern was revealed notably less complex end-products of catechol as; succinate, and 2-Oxo-4-pentenoate. The gastrointestinal (GI) absorption rate was found high for all tested compounds, excluding trimer compound, i.e., syringyl β-O-4 syringyl β-O-4 sinapyl alcohol. The toxicity and persistence profile tested via Toxtree showed that the Cramer Rules, Verhaar Scheme, and Structural Alerts for Reactivity, (START) biodegradation ability as positive, and all five target compounds were found as class-II persistent compounds. Furthermore, the Ecological Structure-Activity Relationships (ECOSAR)assisted testing specifies that all tested derivatives have multiple aquatic toxic levels. In summary, the current findings endorse the hazardous compounds and undertake prescreening of the deprivation policy to protect the environment.
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Affiliation(s)
- Anil Kumar Singh
- Environmental Microbiology Laboratory, Environmental Toxicology Group, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Muhammad Bilal
- School of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian 223003, China
| | - Damià Barceló
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Jordi Girona, 18-26, 08034 Barcelona, Spain; Catalan Institute of Water Research (ICRA-CERCA), Parc Científic i Tecnològic de la Universitat de Girona, c/Emili Grahit, 101, Edifici H2O, 17003 Girona, Spain; Sustainability Cluster, School of Engineering, UPES, Dehradun, India
| | - Hafiz M N Iqbal
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey 64849, Mexico.
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Peng W, Wang T, Liang XR, Yang YS, Wang QZ, Cheng HF, Peng YK, Ding F. Characterizing the potentially neuronal acetylcholinesterase reactivity toward chiral pyraclofos: Enantioselective insights from spectroscopy, in silico docking, molecular dynamics simulation and per-residue energy decomposition studies. J Mol Graph Model 2021; 110:108069. [PMID: 34773872 DOI: 10.1016/j.jmgm.2021.108069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 10/27/2021] [Accepted: 10/28/2021] [Indexed: 10/20/2022]
Abstract
Chiral organophosphorus agents are distributed ubiquitously in the environment, but the neuroactivity of these asymmetric chemicals to humans remains uncertain. This scenario was to explore the stereoselective neurobiological response of human acetylcholinesterase (AChE) to chiral pyraclofos at the enantiomeric scale, and then decipher the microscopic basis of enantioselective neurotoxicity of pyraclofos enantiomers. The results indicated that (R)-/(S)-pyraclofos can form the bioconjugates with AChE with a stoichiometric ratio of 1:1, but the neuronal affinity of (R)-pyraclofos (K = 6.31 × 104 M-1) with AChE was larger than that of (S)-pyraclofos (K = 1.86 × 104 M-1), and significant enantioselectivity was existed in the biochemical reaction. The modes of neurobiological action revealed that pyraclofos enantiomers were situated at the substrate binding domain, and the strength of the overall noncovalent bonds between (S)-pyraclofos and the residues was weaker than that of (R)-pyraclofos, resulting in the high inhibitory effect of (R)-pyraclofos toward the activity of AChE. Dynamic enantioselective biointeractions illustrated that the intervention of inherent conformational flexibility in the AChE-(R)-pyraclofos was greater than that of the AChE-(S)-pyraclofos, which arises from the big spatial displacement and the conformational flip of the binding domain composed of the residues Thr-64~Asn-89, Gly-122~Asp-134, and Thr-436~Tyr-449. Energy decomposition exhibited that the Gibbs free energies of the AChE-(R)-/(S)-pyraclofos were ΔG° = -37.4/-30.2 kJ mol-1, respectively, and the disparity comes from the electrostatic energy during the stereoselective neurochemical reactions. Quantitative conformational analysis further confirmed the atomic-scale computational chemistry conclusions, and the perturbation of (S)-pyraclofos on the AChE's ordered conformation was lower than that of (R)-pyraclofos, which is germane to the interaction energies of the crucial residues, e.g. Tyr-124, Tyr-337, Asp-74, Trp-86, and Tyr-119. Evidently, this attempt will contribute mechanistic information to uncovering the neurobiological effects of chiral organophosphates on the body.
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Affiliation(s)
- Wei Peng
- School of Water and Environment, Chang'an University, Xi'an, 710054, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710054, China; State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China
| | - Tao Wang
- School of Water and Environment, Chang'an University, Xi'an, 710054, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710054, China
| | - Xiang-Rong Liang
- School of Water and Environment, Chang'an University, Xi'an, 710054, China
| | - Yu-Sen Yang
- School of Water and Environment, Chang'an University, Xi'an, 710054, China
| | - Qi-Zhao Wang
- School of Water and Environment, Chang'an University, Xi'an, 710054, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710054, China
| | - Hong-Fei Cheng
- School of Earth Science and Resources, Chang'an University, Xi'an, 710054, China
| | - Yu-Kui Peng
- Xining Center for Agricultural Product Quality and Safety Testing, Xining, 810016, China
| | - Fei Ding
- School of Water and Environment, Chang'an University, Xi'an, 710054, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710054, China; Department of Agricultural Chemistry, Qingdao Agricultural University, Qingdao, 266109, China.
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Appiah-Kubi P, Olotu FA, Soliman MES. Exploring the structural basis and atomistic binding mechanistic of the selective antagonist blockade at D 3 dopamine receptor over D 2 dopamine receptor. J Mol Recognit 2021; 34:e2885. [PMID: 33401335 DOI: 10.1002/jmr.2885] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 11/17/2020] [Accepted: 12/15/2020] [Indexed: 12/28/2022]
Abstract
More recently, there has been a paradigm shift toward selective drug targeting in the treatment of neurological disorders, including drug addiction, schizophrenia, and Parkinson's disease mediated by the different dopamine receptor subtypes. Antagonists with higher selectivity for D3 dopamine receptor (D3DR) over D2 dopamine receptor (D2DR) have been shown to attenuate drug-seeking behavior and associated side effects compared to non-subtype selective antagonists. However, high conservations among constituent residues of both proteins, particularly at the ligand-binding pockets, remain a challenge to therapeutic drug design. Recent studies have reported the discovery of two small-molecules R-VK4-40 and Y-QA31 which substantially inhibited D3DR with >180-fold selectivity over D2DR. Therefore, in this study, we seek to provide molecular and structural insights into these differential binding mechanistic using meta-analytic computational simulation methods. Findings revealed that R-VK4-40 and Y-QA31 adopted shallow binding modes and were more surface-exposed at D3DR while on the contrary, they exhibited deep hydrophobic pocket binding at D2DR. Also, two non-conserved residues; Tyr361.39 and Ser18245.51 were identified in D3DR, based on their crucial roles and contributions to the selective binding of R-VK4-40 and Y-QA31. Importantly, both antagonists exhibited high affinities in complex with D3DR compared to D2DR, while van der Waals energies contributed majorly to their binding and stability. Structural analyses also revealed the distinct stabilizing effects of both compounds on D3DR secondary architecture relative to D2DR. Therefore, findings herein pinpointed the origin and mechanistic of selectivity of the compounds, which may assist in the rational design of potential small molecules of the D2 -like dopamine family receptor subtype with improved potency and selectivity.
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Affiliation(s)
- Patrick Appiah-Kubi
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Fisayo Andrew Olotu
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Mahmoud E S Soliman
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
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Kamerlin N, Delcey MG, Manzetti S, van der Spoel D. Toward a Computational Ecotoxicity Assay. J Chem Inf Model 2020; 60:3792-3803. [PMID: 32648756 DOI: 10.1021/acs.jcim.0c00574] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Thousands of anthropogenic chemicals are released into the environment each year, posing potential hazards to human and environmental health. Toxic chemicals may cause a variety of adverse health effects, triggering immediate symptoms or delayed effects over longer periods of time. It is thus crucial to develop methods that can rapidly screen and predict the toxicity of chemicals to limit the potential harmful impacts of chemical pollutants. Computational methods are being increasingly used in toxicity predictions. Here, the method of molecular docking is assessed for screening potential toxicity of a variety of xenobiotic compounds, including pesticides, pharmaceuticals, pollutants, and toxins derived from the chemical industry. The method predicts the binding energy of pollutants to a set of carefully selected receptors under the assumption that toxicity in many cases is related to interference with biochemical pathways. The strength of the applied method lies in its rapid generation of interaction maps between potential toxins and the targeted enzymes, which could quickly yield molecular-level information and insight into potential perturbation pathways, aiding in the prioritization of chemicals for further tests. Two scoring functions are compared: Autodock Vina and the machine-learning scoring function RF-Score-VS. The results are promising, although hampered by the accuracy of the scoring functions. The strengths and weaknesses of the docking protocol are discussed, as well as future directions for improving the accuracy for the purpose of toxicity predictions.
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Affiliation(s)
- Natasha Kamerlin
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Box 596, SE-751 24 Uppsala, Sweden
| | - Mickaël G Delcey
- Department of Chemistry-Ångström Laboratory, Uppsala University, SE-75120 Uppsala, Sweden
| | - Sergio Manzetti
- Institute for Science and Technology, Fjordforsk A.S., Midtun, 6894 Vangsnes, Norway
| | - David van der Spoel
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Box 596, SE-751 24 Uppsala, Sweden
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van der Spoel D, Manzetti S, Zhang H, Klamt A. Prediction of Partition Coefficients of Environmental Toxins Using Computational Chemistry Methods. ACS OMEGA 2019; 4:13772-13781. [PMID: 31497695 PMCID: PMC6713992 DOI: 10.1021/acsomega.9b01277] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 06/27/2019] [Indexed: 05/05/2023]
Abstract
The partitioning of compounds between aqueous and other phases is important for predicting toxicity. Although thousands of octanol-water partition coefficients have been measured, these represent only a small fraction of the anthropogenic compounds present in the environment. The octanol phase is often taken to be a mimic of the inner parts of phospholipid membranes. However, the core of such membranes is typically more hydrophobic than octanol, and other partition coefficients with other compounds may give complementary information. Although a number of (cheap) empirical methods exist to compute octanol-water (log k OW) and hexadecane-water (log k HW) partition coefficients, it would be interesting to know whether physics-based models can predict these crucial values more accurately. Here, we have computed log k OW and log k HW for 133 compounds from seven different pollutant categories as well as a control group using the solvation model based on electronic density (SMD) protocol based on Hartree-Fock (HF) or density functional theory (DFT) and the COSMO-RS method. For comparison, XlogP3 (log k OW) values were retrieved from the PubChem database, and KowWin log k OW values were determined as well. For 24 of these compounds, log k OW was computed using potential of mean force (PMF) calculations based on classical molecular dynamics simulations. A comparison of the accuracy of the methods shows that COSMO-RS, KowWin, and XlogP3 all have a root-mean-square deviation (rmsd) from the experimental data of ≈0.4 log units, whereas the SMD protocol has an rmsd of 1.0 log units using HF and 0.9 using DFT. PMF calculations yield the poorest accuracy (rmsd = 1.1 log units). Thirty-six out of 133 calculations are for compounds without known log k OW, and for these, we provide what we consider a robust prediction, in the sense that there are few outliers, by averaging over the methods. The results supplied may be instrumental when developing new methods in computational ecotoxicity. The log k HW values are found to be strongly correlated to log k OW for most compounds.
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Affiliation(s)
- David van der Spoel
- Uppsala Center for
Computational Chemistry, Science for Life Laboratory, Department of
Cell and Molecular Biology, Uppsala University, Husargatan 3, Box
596, SE-75124 Uppsala, Sweden
- E-mail: . Phone: +46 18 4714205
| | - Sergio Manzetti
- Uppsala Center for
Computational Chemistry, Science for Life Laboratory, Department of
Cell and Molecular Biology, Uppsala University, Husargatan 3, Box
596, SE-75124 Uppsala, Sweden
- Fjordforsk A.S., Institute
for Science and Technology, Midtun, 6894 Vangsnes, Norway
| | - Haiyang Zhang
- Department of Biological Science and Engineering,
School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China
| | - Andreas Klamt
- COSMOlogic GmbH & Co. KG, Imbacher Weg 46, D-51379 Leverkusen, Germany
- Institute of Physical and Theoretical Chemistry, University of Regensburg, 93053 Regensburg, Germany
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