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Cho CW, Pham TPT, Zhao Y, Stolte S, Yun YS. Review of the toxic effects of ionic liquids. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 786:147309. [PMID: 33975102 DOI: 10.1016/j.scitotenv.2021.147309] [Citation(s) in RCA: 85] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 04/15/2021] [Accepted: 04/18/2021] [Indexed: 05/11/2023]
Abstract
Interest in ionic liquids (ILs), called green or designer solvents, has been increasing because of their excellent properties such as thermal stability and low vapor pressure; thus, they can replace harmful organic chemicals and help several industrial fields e.g., energy-storage materials production and biomaterial pretreatment. However, the claim that ILs are green solvents should be carefully considered from an environmental perspective. ILs, given their minimal vapor pressure, may not directly cause atmospheric pollution. However, they have the potential to cause adverse effects if leaked into the environment, for instance if they are spilled due to human mistakes or technical errors. To estimate the risks of ILs, numerous ILs have had their toxicity assessed toward several micro- and macro-organisms over the past few decades. Since the toxic effects of ILs depend on the method of estimating toxicity, it is necessary to briefly summarize and comprehensively discuss the biological effects of ILs according to their structure and toxicity testing levels. This can help simplify our understanding of the toxicity of ILs. Therefore, in this review, we discuss the key findings of toxicological information of ILs, collect some toxicity data of ILs to different species, and explain the influence of IL structure on their toxic properties. In the discussion, we estimated two different sensitivity values of toxicity testing levels depending on the experiment condition, which are theoretical magnitudes of the inherent sensitivity of toxicity testing levels in various conditions and their changes in biological response according to the change in IL structure. Finally, some perspectives, future research directions, and limitations to toxicological research of ILs, presented so far, are discussed.
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Affiliation(s)
- Chul-Woong Cho
- Department of Bioenergy Science and Technology, Chonnam National University, Gwangju, South Korea.
| | - Thi Phuong Thuy Pham
- Faculty of Biotechnology, HoChiMihn University of Food Industry, Ho Chi Minh City, Viet Nam
| | - Yufeng Zhao
- College of Resource and Environmental Science, South-Central University for Nationalities, Wuhan 430074, Hubei Province, China
| | - Stefan Stolte
- Technische Universität Dresden, Faculty of Environmental Sciences, Department of Hydrosciences, Institute of Water Chemistry, Bergstraße 66, 01062 Dresden, Germany
| | - Yeoung-Sang Yun
- School of Chemical Engineering, Chonbuk National University, 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, South Korea.
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Tcheremenskaia O, Benigni R. Toward regulatory acceptance and improving the prediction confidence of in silico approaches: a case study of genotoxicity. Expert Opin Drug Metab Toxicol 2021; 17:987-1005. [PMID: 34078212 DOI: 10.1080/17425255.2021.1938540] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Introduction: Genotoxicity is an imperative component of the human health safety assessment of chemicals. Its secure forecast is of the utmost importance for all health prevention strategies and regulations.Areas covered: We surveyed several types of alternative, animal-free approaches ((quantitative) structure-activity relationship (Q)SAR, read-across, Adverse Outcome Pathway, Integrated Approaches to Testing and Assessment) for genotoxicity prediction within the needs of regulatory frameworks, putting special emphasis on data quality and uncertainties issues.Expert opinion: (Q)SAR models and read-across approaches for in vitro bacterial mutagenicity have sufficient reliability for use in prioritization processes, and as support in regulatory decisions in combination with other types of evidence. (Q)SARs and read-across methodologies for other genotoxicity endpoints need further improvements and should be applied with caution. It appears that there is still large room for improvement of genotoxicity prediction methods. Availability of well-curated high-quality databases, covering a broader chemical space, is one of the most important needs. Integration of in silico predictions with expert knowledge, weight-of-evidence-based assessment, and mechanistic understanding of genotoxicity pathways are other key points to be addressed for the generation of more accurate and trustable results.
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Affiliation(s)
- Olga Tcheremenskaia
- Environmental and Health Department, Istituto Superiore Di Sanità (ISS), Rome, Italy, Rome, Italy
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3
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Kowalska D, Maculewicz J, Stepnowski P, Dołżonek J. Ionic liquids as environmental hazards - Crucial data in view of future PBT and PMT assessment. JOURNAL OF HAZARDOUS MATERIALS 2021; 403:123896. [PMID: 33264960 DOI: 10.1016/j.jhazmat.2020.123896] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Revised: 08/31/2020] [Accepted: 08/31/2020] [Indexed: 06/12/2023]
Abstract
Ionic liquids (ILs) constitute a large group of chemical compounds. They have gained much attention among scientists and industry due to their unique properties. Due to the fact that ILs are purely ionic compounds, there is the possibility to design an enormous number of cation and anion combinations, making them designer solvents. Thus it also creates the possibility of producing more environmentally benign solvents. However, significant drawbacks related mainly to their toxicity and persistence have already been noticed. Furthermore the interest in these compounds is constantly growing and their impact on the environment should be defined. More and more ILs are produced or imported in the amount higher than 10 tonnes per year and the group of ILs registered in REACH is still expanding. Thus for an increasing number of compounds, it will be necessary to perform a PBT and PMT assessment using the criteria described in REACH. Therefore the data collected in this work thoroughly sort out the information on the toxicity, bioconcentration/bioaccumulation, biodegradation and mobility of ILs in the context of PBT and PMT assessment.
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Affiliation(s)
- Dorota Kowalska
- Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland.
| | - Jakub Maculewicz
- Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Piotr Stepnowski
- Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Joanna Dołżonek
- Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
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Abramenko N, Kustov L, Metelytsia L, Kovalishyn V, Tetko I, Peijnenburg W. A review of recent advances towards the development of QSAR models for toxicity assessment of ionic liquids. JOURNAL OF HAZARDOUS MATERIALS 2020; 384:121429. [PMID: 31732345 DOI: 10.1016/j.jhazmat.2019.121429] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2019] [Revised: 09/27/2019] [Accepted: 10/07/2019] [Indexed: 06/10/2023]
Affiliation(s)
- Natalia Abramenko
- N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Moscow, Leninsky prospect 47, 119991, Russia; N. Severtsov Institute of Ecology and Evolution, RAS, Moscow, Russia
| | - Leonid Kustov
- N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Moscow, Leninsky prospect 47, 119991, Russia; National University of Science and Technology MISiS, Leninsky prosp. 4, Moscow, Russia
| | - Larysa Metelytsia
- Institute of Bioorganic Chemistry & Petrochemistry, National Academy of Science of Ukraine, 1 Murmanska Street, 02660, Kyiv, Ukraine
| | - Vasyl Kovalishyn
- Institute of Bioorganic Chemistry & Petrochemistry, National Academy of Science of Ukraine, 1 Murmanska Street, 02660, Kyiv, Ukraine
| | - Igor Tetko
- Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Structural Biology, BIGCHEM GmbH, Ingolstädter Landstraße 1, b. 60w, D-85764 Neuherberg, Germany
| | - Willie Peijnenburg
- Institute of Environmental Sciences (CML), Leiden University, PO Box 9518, 2300 RA, Leiden, the Netherlands; National Institute of Public Health and the Environment, Center for Safety of Substances and Products, PO Box 1, 3720 BA, Bilthoven, the Netherlands.
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Cheng G, Sun L, Fu J. Prediction of Biodegradability for Polycyclic Aromatic Hydrocarbons Using Various In Silico Modeling Methods. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2018; 75:607-615. [PMID: 30178131 DOI: 10.1007/s00244-018-0556-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Accepted: 08/31/2018] [Indexed: 06/08/2023]
Abstract
Polycyclic aromatic hydrocarbons (PAHs) have attracted great concern as global environmental pollutants. In this work, the quantitative structure-biodegradability relationship (QSBR) study has been done to predict the biodegradability of PAHs and develop the correlation between the biodegradability and the molecular structures. The structural chemistry and quantum chemistry descriptors were used to represent molecular structures. Three in silico modeling methods, i.e., multiple linear regression (MLR), radial basis function neural network, and back-propagation artificial neural network (BPANN), are utilized to construct the linear and nonlinear prediction models and provide some insights into the structural characteristics affecting the biodegradability of PAHs. The stability of these QSBR models was tested by leave-one-out cross-validation, and the cross-validated correlation coefficients (q2) were 0.6109, 0.6887, and 0.6586, respectively. The correlation coefficients (R2) of the three models for the training set were 0.7811, 0.8883, and 0.9667, respectively. The comparison of the three models showed that the BPANN model produced a statistically more significant model than the other two models. On the basis of molecular structure, the dominant molecular structure descriptor affecting biodegradability of PAHs were analyzed and discussed.
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Affiliation(s)
- Gong Cheng
- Shenzhen Academy of Environmental Sciences, Shenzhen, 518001, China
| | - Liming Sun
- Shenzhen Academy of Environmental Sciences, Shenzhen, 518001, China
| | - Jie Fu
- Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China.
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Paternò A, Goracci L, Scire S, Musumarra G. Modeling from Theory and Modeling from Data: Complementary or Alternative Approaches? The Case of Ionic Liquids. ChemistryOpen 2017; 6:90-101. [PMID: 28168154 PMCID: PMC5288763 DOI: 10.1002/open.201600119] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Indexed: 12/02/2022] Open
Abstract
In the field of ionic liquids (ILs), theory-driven modeling approaches aimed at the best fit for all available data by using a unique, and often nonlinear, model have been widely adopted to develop quantitative structure-property relationship (QSPR) models. In this context, we propose chemoinformatic and chemometric data-driven procedures that lead to QSPR soft models with local validity that are able to predict relevant physicochemical properties of ILs, such as viscosity, density, decomposition temperature, and conductivity. These models, which use readily available and easily interpretable VolSurf+ descriptors, represent an unexploited opportunity for experimentalists to model and predict the physicochemical properties of ILs in industrial R&D design.
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Affiliation(s)
- Alessio Paternò
- Dipartimento di Scienze ChimicheUniversità di CataniaViale A. Doria 695125CataniaItaly
| | - Laura Goracci
- Laboratorio di Chemiometria e ChemioinformaticaDipartimento di ChimicaUniversità di PerugiaVia Elce di Sotto 1006123PerugiaItaly
| | - Salvatore Scire
- Dipartimento di Scienze ChimicheUniversità di CataniaViale A. Doria 695125CataniaItaly
| | - Giuseppe Musumarra
- Dipartimento di Scienze ChimicheUniversità di CataniaViale A. Doria 695125CataniaItaly
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Cho CW, Stolte S, Yun YS. Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors. Sci Rep 2016; 6:33403. [PMID: 27624396 PMCID: PMC5022054 DOI: 10.1038/srep33403] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Accepted: 08/24/2016] [Indexed: 01/08/2023] Open
Abstract
The challenge and opportunity for design of environmentally-benign ionic liquids (ILs) would start from prediction of their toxicological effects on several endpoints solely based on the structural formulas. Especially, a comprehensive yet simple equation able to predict several biological responses to IL toxicity is of much advantage. Therefore, based on 50 toxicity testing systems on ILs a comprehensively approachable prediction method was developed. For the modelling, approximately 1600 toxicity values measured by several biological systems and an amended linear free energy relationship (LFER) model were used. Since the toxicological activities of an IL could be differently described according to sensitivity of toxicity testing systems, the sensitivity of each of toxicity testing systems was also estimated in the modelling. By statistical analysis with the calculated descriptors, a LFER model was built. Also the sensitivity value of each system on the basis of the comprehensively approachable model was numerically estimated. In results, it was observed that the combination of single model and sensitivity terms was able to predict each of 50 toxicological effects of ILs with R(2) of 0.593~0.978, and SE of 0.098~0.699 log unit, and the total data set with R(2) of 0.901 and SE of 0.426 log unit.
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Affiliation(s)
- Chul-Woong Cho
- School of Chemical Engineering, Chonbuk National University, 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, South Korea
| | - Stefan Stolte
- Centre for Environmental Research and Sustainable Technology (UFT), University of Bremen, Leobener Straße, 28359, Bremen, Germany
- Department of Environmental Analysis, Faculty of Chemistry, University of Gdaňsk sk ul, Wita Stwosza 63, 80-308, Gdaňsk, Poland
| | - Yeoung-Sang Yun
- School of Chemical Engineering, Chonbuk National University, 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, South Korea
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Paterno' A, Scire S, Musumarra G. A QSPR approach to the ecotoxicity of ionic liquids ( Vibrio fischeri) using VolSurf principal properties. Toxicol Res (Camb) 2016; 5:1090-1096. [PMID: 30090414 PMCID: PMC6062259 DOI: 10.1039/c6tx00071a] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 04/19/2016] [Indexed: 12/20/2022] Open
Abstract
Recently derived in silico structural descriptors for both IL cations and anions allowed the development of a QSPR model correlating ionic liquid structures to Vibrio fischeri toxicity using the partial least squares (PLS) approach. Interpretation of the PLS model confirmed the effect of IL cationic structural features such as the influence of cation side chain length, presence of heteroatoms, and non-aromaticity of the heterocyclic scaffold on toxicity. The PLS model also provided a quantitative evaluation of anion effects, previously not evidenced due to the structural similarity of the anions considered. A simple equation in which three descriptors (two for the cations and one for the anions) allow the prediction of Vibrio fischeri toxicity for over 8000 ILs is reported.
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Affiliation(s)
- Alessio Paterno'
- Dipartimento di Scienze Chimiche , Università di Catania , Viale A. Doria 6 , I-95125 Catania , Italy .
| | - Salvatore Scire
- Dipartimento di Scienze Chimiche , Università di Catania , Viale A. Doria 6 , I-95125 Catania , Italy .
| | - Giuseppe Musumarra
- Dipartimento di Scienze Chimiche , Università di Catania , Viale A. Doria 6 , I-95125 Catania , Italy .
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9
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Paterno' A, D'Anna F, Fortuna CG, Musumarra G. Polarity study of ionic liquids with the solvatochromic dye Nile Red: a QSPR approach using in silico VolSurf+ descriptors. Tetrahedron 2016. [DOI: 10.1016/j.tet.2016.04.056] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Paternò A, Bocci G, Cruciani G, Fortuna CG, Goracci L, Sciré S, Musumarra G. Cyto- and enzyme toxicities of ionic liquids modelled on the basis of VolSurf+ descriptors and their principal properties. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2016; 27:221-244. [PMID: 30950653 DOI: 10.1080/1062936x.2016.1156571] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Five in silico principal properties (PPs) for 218 heterocyclic cations and four PPs for 38 organic and inorganic anionic counterparts of ionic liquids (ILs) were derived by the VolSurf+ approach. VolSurf+ physicochemical descriptors take into account several cationic structural features of ILs such as heterocyclic aromatic and non-aromatic cationic cores, alkyl chain length, presence of oxygen atoms in the substituents as well as the properties of a wide variety of inorganic and organic anions. Combination of these cation and anion PPs can provide descriptors for over 8000 ILs, thus allowing the development of QSPR models for IL cytotoxicity (IPC-81 rat cell line) and enzyme toxicity (acetylcholinesterase inhibition). The adoption of a Partial Least Squares approach, relating PPs and toxicities, provided affordable predictions for ILs in both learning and external validation sets, implying the possibility to extend the predictive model to a set of 520 ILs. This allows us to establish priorities in selecting ILs for experimental hazard assessment as required by the REACH regulation.
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Affiliation(s)
- A Paternò
- a Dipartimento di Scienze Chimiche , Università di Catania , Catania , Italy
| | - G Bocci
- b Laboratorio di Chemiometria e Chemioinformatica, Dipartimento di Chimica , Università di Perugia , Italy
| | - G Cruciani
- b Laboratorio di Chemiometria e Chemioinformatica, Dipartimento di Chimica , Università di Perugia , Italy
| | - C G Fortuna
- a Dipartimento di Scienze Chimiche , Università di Catania , Catania , Italy
| | - L Goracci
- b Laboratorio di Chemiometria e Chemioinformatica, Dipartimento di Chimica , Università di Perugia , Italy
| | - S Sciré
- a Dipartimento di Scienze Chimiche , Università di Catania , Catania , Italy
| | - G Musumarra
- a Dipartimento di Scienze Chimiche , Università di Catania , Catania , Italy
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Paternò A, Fiorenza R, Marullo S, Musumarra G, Scirè S. Prediction of ionic liquid's heat capacity by means of their in silico principal properties. RSC Adv 2016. [DOI: 10.1039/c6ra05106e] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
VolSurf+ in silico principal properties of ionic liquids were used to develop a QSPR model providing affordable heat capacity predictions which were experimentally validated.
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Affiliation(s)
- Alessio Paternò
- Dipartimento di Scienze Chimiche
- Università di Catania
- I-95125 Catania
- Italy
| | - Roberto Fiorenza
- Dipartimento di Scienze Chimiche
- Università di Catania
- I-95125 Catania
- Italy
| | | | - Giuseppe Musumarra
- Dipartimento di Scienze Chimiche
- Università di Catania
- I-95125 Catania
- Italy
| | - Salvatore Scirè
- Dipartimento di Scienze Chimiche
- Università di Catania
- I-95125 Catania
- Italy
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