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Varsou DD, Kolokathis PD, Antoniou M, Sidiropoulos NK, Tsoumanis A, Papadiamantis AG, Melagraki G, Lynch I, Afantitis A. In silico assessment of nanoparticle toxicity powered by the Enalos Cloud Platform: Integrating automated machine learning and synthetic data for enhanced nanosafety evaluation. Comput Struct Biotechnol J 2024; 25:47-60. [PMID: 38646468 PMCID: PMC11026727 DOI: 10.1016/j.csbj.2024.03.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 03/22/2024] [Accepted: 03/23/2024] [Indexed: 04/23/2024] Open
Abstract
The rapid advance of nanotechnology has led to the development and widespread application of nanomaterials, raising concerns regarding their potential adverse effects on human health and the environment. Traditional (experimental) methods for assessing the nanoparticles (NPs) safety are time-consuming, expensive, and resource-intensive, and raise ethical concerns due to their reliance on animals. To address these challenges, we propose an in silico workflow that serves as an alternative or complementary approach to conventional hazard and risk assessment strategies, which incorporates state-of-the-art computational methodologies. In this study we present an automated machine learning (autoML) scheme that employs dose-response toxicity data for silver (Ag), titanium dioxide (TiO2), and copper oxide (CuO) NPs. This model is further enriched with atomistic descriptors to capture the NPs' underlying structural properties. To overcome the issue of limited data availability, synthetic data generation techniques are used. These techniques help in broadening the dataset, thus improving the representation of different NP classes. A key aspect of this approach is a novel three-step applicability domain method (which includes the development of a local similarity approach) that enhances user confidence in the results by evaluating the prediction's reliability. We anticipate that this approach will significantly expedite the nanosafety assessment process enabling regulation to keep pace with innovation, and will provide valuable insights for the design and development of safe and sustainable NPs. The ML model developed in this study is made available to the scientific community as an easy-to-use web-service through the Enalos Cloud Platform (www.enaloscloud.novamechanics.com/sabydoma/safenanoscope/), facilitating broader access and collaborative advancements in nanosafety.
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Affiliation(s)
- Dimitra-Danai Varsou
- NovaMechanics MIKE, Piraeus 18545, Greece
- Entelos Institute, Larnaca 6059, Cyprus
| | | | | | | | - Andreas Tsoumanis
- Entelos Institute, Larnaca 6059, Cyprus
- NovaMechanics Ltd, Nicosia 1070, Cyprus
| | - Anastasios G. Papadiamantis
- Entelos Institute, Larnaca 6059, Cyprus
- NovaMechanics Ltd, Nicosia 1070, Cyprus
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, UK
| | - Georgia Melagraki
- Division of Physical Sciences and Applications, Hellenic Military Academy, Vari 16672, Greece
| | - Iseult Lynch
- Entelos Institute, Larnaca 6059, Cyprus
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, UK
| | - Antreas Afantitis
- NovaMechanics MIKE, Piraeus 18545, Greece
- Entelos Institute, Larnaca 6059, Cyprus
- NovaMechanics Ltd, Nicosia 1070, Cyprus
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2
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Serratosa F. ATENA: A Web-Based Tool for Modelling Metal Oxide Nanoparticles Based on NanoFingerprint Quantitative Structure-Activity Relationships. Molecules 2024; 29:2235. [PMID: 38792096 PMCID: PMC11124079 DOI: 10.3390/molecules29102235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 05/07/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
Modelling size-realistic nanomaterials to analyse some of their properties, such as toxicity, solubility, or electronic structure, is a current challenge in computational and theoretical chemistry. The representation of the all-atom three-dimensional structure of a nanocompound would be ideal, as it could account explicitly for structural effects. However, the use of the whole structure is tedious due to the high data management and the structural complexity that accompanies the surface of the nanoparticle. Developing appropriate tools that enable a quantitative analysis of the structure, as well as the selection of regions of interest such as the core-shell, is a crucial step toward enabling the efficient analysis and processing of model nanostructures. The aim of this study was twofold. First, we defined the NanoFingerprint, which is a representation of a nanocompound in the form of a vector based on its 3D structure. The local relationship between atoms, i.e., their coordination within successive layers of neighbours, allows the characterisation of the local structure through the atom connectivity, maintaining the information of the three-dimensional structure but increasing the management ability. Second, we present a web server, called ATENA, to generate NanoFingerprints and other tools based on the 3D structure of the nanocompounds. A case study is reported to show the validity of our new fingerprint tool and the usefulness of our server. The scientific community and also private companies have a new tool based on a public web server for exploring the toxicity of nanocompounds.
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Affiliation(s)
- Francesc Serratosa
- Computer Science and Math Department, Universitat Rovira i Virgili, 43007 Tarragona, Catalonia, Spain
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3
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Del Giudice G, Serra A, Saarimäki LA, Kotsis K, Rouse I, Colibaba SA, Jagiello K, Mikolajczyk A, Fratello M, Papadiamantis AG, Sanabria N, Annala ME, Morikka J, Kinaret PAS, Voyiatzis E, Melagraki G, Afantitis A, Tämm K, Puzyn T, Gulumian M, Lobaskin V, Lynch I, Federico A, Greco D. An ancestral molecular response to nanomaterial particulates. NATURE NANOTECHNOLOGY 2023; 18:957-966. [PMID: 37157020 PMCID: PMC10427433 DOI: 10.1038/s41565-023-01393-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 03/31/2023] [Indexed: 05/10/2023]
Abstract
The varied transcriptomic response to nanoparticles has hampered the understanding of the mechanism of action. Here, by performing a meta-analysis of a large collection of transcriptomics data from various engineered nanoparticle exposure studies, we identify common patterns of gene regulation that impact the transcriptomic response. Analysis identifies deregulation of immune functions as a prominent response across different exposure studies. Looking at the promoter regions of these genes, a set of binding sites for zinc finger transcription factors C2H2, involved in cell stress responses, protein misfolding and chromatin remodelling and immunomodulation, is identified. The model can be used to explain the outcomes of mechanism of action and is observed across a range of species indicating this is a conserved part of the innate immune system.
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Affiliation(s)
- G Del Giudice
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - A Serra
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Tampere Institute for Advanced Study, Tampere, Finland
| | - L A Saarimäki
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - K Kotsis
- School of Physics, University College Dublin, Dublin, Ireland
| | - I Rouse
- School of Physics, University College Dublin, Dublin, Ireland
| | - S A Colibaba
- School of Physics, University College Dublin, Dublin, Ireland
| | - K Jagiello
- Group of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
- QSAR Lab Ltd, Gdańsk, Poland
| | - A Mikolajczyk
- Group of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
- QSAR Lab Ltd, Gdańsk, Poland
| | - M Fratello
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - A G Papadiamantis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
- Novamechanics Ltd, Nicosia, Cyprus
| | - N Sanabria
- National Institute for Occupational Health, National Health Laboratory Services, Johannesburg, South Africa
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - M E Annala
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - J Morikka
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - P A S Kinaret
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Institute of Biotechnology, Helsinki Institute of Life Sciences (HiLife), University of Helsinki, Helsinki, Finland
| | | | - G Melagraki
- Division of Physical Sciences and Applications, Hellenic Military Academy, Vari, Greece
| | | | - K Tämm
- Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - T Puzyn
- Group of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
- QSAR Lab Ltd, Gdańsk, Poland
| | - M Gulumian
- National Institute for Occupational Health, National Health Laboratory Services, Johannesburg, South Africa
- Haematology and Molecular Medicine Department, School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
- Water Research Group, Unit for Environmental Sciences and Management, North West University, Potchefstroom, South Africa
| | - V Lobaskin
- School of Physics, University College Dublin, Dublin, Ireland
| | - I Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
| | - A Federico
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Tampere Institute for Advanced Study, Tampere, Finland
| | - D Greco
- FHAIVE, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- Institute of Biotechnology, Helsinki Institute of Life Sciences (HiLife), University of Helsinki, Helsinki, Finland.
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland.
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4
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Yan X, Yue T, Winkler DA, Yin Y, Zhu H, Jiang G, Yan B. Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation. Chem Rev 2023. [PMID: 37262026 DOI: 10.1021/acs.chemrev.3c00070] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. The question is how to extract critical information buried in vast data streams. Here we show that artificial intelligence (AI) and molecular simulation play key roles in transforming nanotoxicity data into critical information, i.e., constructing the quantitative nanostructure (physicochemical properties)-toxicity relationships, and elucidating the toxicity-related molecular mechanisms. For AI and molecular simulation to realize their full impacts in this mission, several obstacles must be overcome. These include the paucity of high-quality nanomaterials (NMs) and standardized nanotoxicity data, the lack of model-friendly databases, the scarcity of specific and universal nanodescriptors, and the inability to simulate NMs at realistic spatial and temporal scales. This review provides a comprehensive and representative, but not exhaustive, summary of the current capability gaps and tools required to fill these formidable gaps. Specifically, we discuss the applications of AI and molecular simulation, which can address the large-scale data challenge for nanotoxicology research. The need for model-friendly nanotoxicity databases, powerful nanodescriptors, new modeling approaches, molecular mechanism analysis, and design of the next-generation NMs are also critically discussed. Finally, we provide a perspective on future trends and challenges.
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Affiliation(s)
- Xiliang Yan
- Institute of Environmental Research at the Greater Bay Area, Key Laboratory for Water Quality and Conservation of the Pearl River Delta, Ministry of Education, Guangzhou University, Guangzhou 510006, China
| | - Tongtao Yue
- Key Laboratory of Marine Environment and Ecology, Ministry of Education, Institute of Coastal Environmental Pollution Control, Ocean University of China, Qingdao 266100, China
| | - David A Winkler
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
- School of Pharmacy, University of Nottingham, Nottingham NG7 2QL, U.K
- Department of Biochemistry and Chemistry, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria 3086, Australia
| | - Yongguang Yin
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Hao Zhu
- Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Bing Yan
- Institute of Environmental Research at the Greater Bay Area, Key Laboratory for Water Quality and Conservation of the Pearl River Delta, Ministry of Education, Guangzhou University, Guangzhou 510006, China
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5
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Gomes SIL, Roca CP, Pokhrel S, Mädler L, Scott-Fordsmand JJ, Amorim MJB. TiO 2 nanoparticles' library toxicity (UV and non-UV exposure) - High-throughput in vivo transcriptomics reveals mechanisms. NANOIMPACT 2023; 30:100458. [PMID: 36858316 DOI: 10.1016/j.impact.2023.100458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 02/21/2023] [Accepted: 02/24/2023] [Indexed: 06/03/2023]
Abstract
The hazards of nanomaterials/nanoparticles (NMs/NPs) are mostly assessed using individual NMs, and a more systematic approach, using many NMs, is needed to evaluate its risks in the environment. Libraries of NMs, with a range of identified different but related characters/descriptors allow the comparison of effects across many NMs. The effects of a custom designed Fe-doped TiO2 NMs library containing 11 NMs was assessed on the soil model Enchytraeus crypticus (Oligochaeta), both with and without UV (standard fluorescent) radiation. Effects were analyzed at organism (phenotypic, survival and reproduction) and gene expression level (transcriptomics, high-throughput 4x44K microarray) to understand the underlying mechanisms. A total of 48 microarrays (20 test conditions) were done plus controls (UV and non-UV). Unique mechanisms induced by TiO2 NPs exposure included the impairment in RNA processing for TiO2_10nm, or deregulated apoptosis for 2%FeTiO2_10nm. Strikingly apparent was the size dependent effects such as induction of reproductive effects via smaller TiO2 NPs (≤12 nm) - embryo interaction, while larger particles (27 nm) caused reproductive effects through different mechanisms. Also, phagocytosis was affected by 12 and 27 nm NPs, but not by ≤11 nm. The organism level study shows the integrated response, i.e. the result after a cascade of events. While uni-cell models offer key mechanistic information, we here deliver a combined biological system level (phenotype and genotype), seldom available, especially for environmental models.
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Affiliation(s)
- Susana I L Gomes
- Department of Biology & CESAM, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Carlos P Roca
- Department of Ecoscience, Aarhus University, C.F. Møllers Alle 4, DK-8000, Aarhus, Denmark
| | - Suman Pokhrel
- Department of Production Engineering, University of Bremen, Badgasteiner Str. 1, 28359 Bremen, Germany; Leibniz Institute for Materials Engineering IWT, Badgasteiner Str. 3, 28359 Bremen, Germany
| | - Lutz Mädler
- Department of Production Engineering, University of Bremen, Badgasteiner Str. 1, 28359 Bremen, Germany; Leibniz Institute for Materials Engineering IWT, Badgasteiner Str. 3, 28359 Bremen, Germany
| | | | - Mónica J B Amorim
- Department of Biology & CESAM, University of Aveiro, 3810-193 Aveiro, Portugal.
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6
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Singhal A, Sevink GJA. A Core-Shell Approach for Systematically Coarsening Nanoparticle-Membrane Interactions: Application to Silver Nanoparticles. NANOMATERIALS (BASEL, SWITZERLAND) 2022; 12:3859. [PMID: 36364637 PMCID: PMC9656456 DOI: 10.3390/nano12213859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 10/28/2022] [Accepted: 10/28/2022] [Indexed: 06/16/2023]
Abstract
The continuous release of engineered nanomaterial (ENM) into the environment may bring about health concerns following human exposure. One important source of ENMs are silver nanoparticles (NPs) that are extensively used as anti-bacterial additives. The introduction of ENMs into the human body can occur via ingestion, skin uptake or the respiratory system. Therefore, evaluating how NPs translocate over bio-membranes is essential in assessing their primary toxicity. Unfortunately, data regarding membrane-NP interaction is still scarce, as is theoretical and in silico insight into what governs adhesion and translocation for the most relevant NPs and membranes. Coarse-grained (CG) molecular descriptions have the potential to alleviate this situation, but are hampered by the absence of a direct link to NP materials and membrane adhesion mechanisms. Here, we interrogate the relationship between the most common NP representation at the CG level and the adhesion characteristics of a model lung membrane. We find that this representation for silver NPs is non-transferable, meaning that a proper CG representation for one size is not suited for other sizes. We also identify two basic types of primary adhesion-(partial) NPs wrapping by the membrane and NP insertion into the membrane-that closely relate to the overall NP hydrophobicity and significantly differ in terms of lipid coatings. The proven non-transferability of the standard CG representation with size forms an inspiration for introducing a core-shell model even for bare NPs that are uniform in composition. Using existing all-atom molecular dynamics (MD) data as a reference, we show that this extension does allow us to reproduce size-dependent NP adhesion properties and lipid responses to NP binding at the CG level. The subsequent CGMD evaluation for 10 nm Ag NPs provides new insight into membrane binding for relevant NP sizes and into the role of water in trapping NPs into defected mixed monolayer-bilayer states. This development will be instrumental for simulating NP-membrane adhesion towards more experimentally relevant length and time scales for particular NP materials.
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7
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Mancardi G, Alberghini M, Aguilera-Porta N, Calatayud M, Asinari P, Chiavazzo E. Multi-Scale Modelling of Aggregation of TiO 2 Nanoparticle Suspensions in Water. NANOMATERIALS 2022; 12:nano12020217. [PMID: 35055235 PMCID: PMC8778026 DOI: 10.3390/nano12020217] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/20/2021] [Accepted: 12/30/2021] [Indexed: 02/04/2023]
Abstract
Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO2 nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large-scale experiments on living organisms, we investigate the aggregation of titanium dioxide nanoparticles using a multi-scale technique: starting from ab initio Density Functional Theory to get an accurate determination of the energetics and electronic structure, we switch to classical Molecular Dynamics simulations to calculate the Potential of Mean Force for the connection of two identical nanoparticles in water; the fitting of the latter by a set of mathematical equations is the key for the upscale. Lastly, we perform Brownian Dynamics simulations where each nanoparticle is a spherical bead. This coarsening strategy allows studying the aggregation of a few thousand nanoparticles. Applying this novel procedure, we find three new molecular descriptors, namely, the aggregation free energy and two numerical parameters used to correct the observed deviation from the aggregation kinetics described by the Smoluchowski theory. Ultimately, molecular descriptors can be fed into QSAR models to predict the toxicity of a material knowing its physicochemical properties, enabling safe design strategies.
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Affiliation(s)
- Giulia Mancardi
- Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy; (M.A.); (P.A.); (E.C.)
- Correspondence:
| | - Matteo Alberghini
- Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy; (M.A.); (P.A.); (E.C.)
- Clean Water Center, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
| | - Neus Aguilera-Porta
- Laboratoire de Chimie Theorique, CNRS, Sorbonne Université, 4 Place Jussieu, 75005 Paris, France; (N.A.-P.); (M.C.)
| | - Monica Calatayud
- Laboratoire de Chimie Theorique, CNRS, Sorbonne Université, 4 Place Jussieu, 75005 Paris, France; (N.A.-P.); (M.C.)
| | - Pietro Asinari
- Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy; (M.A.); (P.A.); (E.C.)
- Istituto Nazionale di Ricerca Metrologica, Strada delle Cacce 91, 10135 Torino, Italy
| | - Eliodoro Chiavazzo
- Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy; (M.A.); (P.A.); (E.C.)
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8
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Gomes SIL, Amorim MJB, Pokhrel S, Mädler L, Fasano M, Chiavazzo E, Asinari P, Jänes J, Tämm K, Burk J, Scott-Fordsmand JJ. Machine learning and materials modelling interpretation of in vivo toxicological response to TiO 2 nanoparticles library (UV and non-UV exposure). NANOSCALE 2021; 13:14666-14678. [PMID: 34533558 DOI: 10.1039/d1nr03231c] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Assessing the risks of nanomaterials/nanoparticles (NMs/NPs) under various environmental conditions requires a more systematic approach, including the comparison of effects across many NMs with identified different but related characters/descriptors. Hence, there is an urgent need to provide coherent (eco)toxicological datasets containing comprehensive toxicity information relating to a diverse spectra of NPs characters. These datasets are test benches for developing holistic methodologies with broader applicability. In the present study we assessed the effects of a custom design Fe-doped TiO2 NPs library, using the soil invertebrate Enchytraeus crypticus (Oligochaeta), via a 5-day pulse via aqueous exposure followed by a 21-days recovery period in soil (survival, reproduction assessment). Obviously, when testing TiO2, realistic conditions should include UV exposure. The 11 Fe-TiO2 library contains NPs of size range between 5-27 nm with varying %Fe (enabling the photoactivation of TiO2 at energy wavelengths in the visible-light range). The NPs were each described by 122 descriptors, being a mixture of measured and atomistic model descriptors. The data were explored using single and univariate statistical methods, combined with machine learning and multiscale modelling techniques. An iterative pruning process was adopted for identifying automatically the most significant descriptors. TiO2 NPs toxicity decreased when combined with UV. Notably, the short-term water exposure induced lasting biological responses even after longer-term recovery in clean exposure. The correspondence with Fe-content correlated with the band-gap hence the reduction of UV oxidative stress. The inclusion of both measured and modelled materials data benefitted the explanation of the results, when combined with machine learning.
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Affiliation(s)
- Susana I L Gomes
- Department of Biology & CESAM, University of Aveiro, 3810-193 Aveiro, Portugal.
| | - Mónica J B Amorim
- Department of Biology & CESAM, University of Aveiro, 3810-193 Aveiro, Portugal.
| | - Suman Pokhrel
- Department of Production Engineering, University of Bremen, Badgasteiner Str. 1, 28359 Bremen, Germany
- Leibniz Institute for Materials Engineering IWT, Badgasteiner Str. 3, 28359 Bremen, Germany
| | - Lutz Mädler
- Department of Production Engineering, University of Bremen, Badgasteiner Str. 1, 28359 Bremen, Germany
- Leibniz Institute for Materials Engineering IWT, Badgasteiner Str. 3, 28359 Bremen, Germany
| | - Matteo Fasano
- Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy
| | - Eliodoro Chiavazzo
- Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy
| | - Pietro Asinari
- Energy Department, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy
- INRIM, Istituto Nazionale di Ricerca Metrologica, Strada delle Cacce 91, Torino 10135, Italy
| | - Jaak Jänes
- Department of Chemistry, University of Tartu, Ravila 14a, Tartu 50411, Estonia
| | - Kaido Tämm
- Department of Chemistry, University of Tartu, Ravila 14a, Tartu 50411, Estonia
| | - Jaanus Burk
- Department of Chemistry, University of Tartu, Ravila 14a, Tartu 50411, Estonia
| | - Janeck J Scott-Fordsmand
- Department of Bioscience, Aarhus University, Vejlsovej 25, PO BOX 314, DK-8600 Silkeborg, Denmark
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9
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Rouse I, Power D, Brandt EG, Schneemilch M, Kotsis K, Quirke N, Lyubartsev AP, Lobaskin V. First principles characterisation of bio-nano interface. Phys Chem Chem Phys 2021; 23:13473-13482. [PMID: 34109956 DOI: 10.1039/d1cp01116b] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Nanomaterials possess a wide range of potential applications due to their novel properties and exceptionally high activity as a result of their large surface to volume ratios compared to bulk matter. The active surface may present both advantage and risk when the nanomaterials interact with living organisms. As the overall biological impact of nanomaterials is triggered and mediated by interactions at the bio-nano interface, an ability to predict those from the atomistic descriptors, especially before the material is produced, can present enormous advantage for the development of nanotechnology. Fast screening of nanomaterials and their variations for specific biological effects can be enabled using computational materials modelling. The challenge lies in the range of scales that needs to be crossed from the material-specific atomistic representation to the relevant length scales covering typical biomolecules (proteins and lipids). In this work, we present a systematic multiscale approach that allows one to evaluate crucial interactions at the bionano interface from the first principles without any prior information about the material and thus establish links between the details of the nanomaterials structure to protein-nanoparticle interactions. As an example, an advanced computational characterization of titanium dioxide nanoparticles (6 different surfaces of rutile and anatase polymorphs) has been performed. We computed characteristics of the titanium dioxide interface with water using density functional theory for electronic density, used these parameters to derive an atomistic force field, and calculated adsorption energies for essential biomolecules on the surface of titania nanoparticles via direct atomistic simulations and coarse-grained molecular dynamics. Hydration energies, as well as adsorption energies for a set of 40 blood proteins are reported.
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Affiliation(s)
- Ian Rouse
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland.
| | - David Power
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland.
| | - Erik G Brandt
- Department of Materials and Environmental Chemistry, Stockholm University, S-10691 Stockholm, Sweden
| | - Matthew Schneemilch
- Department of Chemistry, Imperial College, 301G Molecular Sciences Research Hub, White City Campus, 80 Wood Lane, London W12 OBZ, UK
| | | | - Nick Quirke
- Department of Chemistry, Imperial College, 301G Molecular Sciences Research Hub, White City Campus, 80 Wood Lane, London W12 OBZ, UK
| | - Alexander P Lyubartsev
- Department of Materials and Environmental Chemistry, Stockholm University, S-10691 Stockholm, Sweden
| | - Vladimir Lobaskin
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland.
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10
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Yu H, Luo D, Dai L, Cheng F. In silico nanosafety assessment tools and their ecosystem-level integration prospect. NANOSCALE 2021; 13:8722-8739. [PMID: 33960351 DOI: 10.1039/d1nr00115a] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Engineered nanomaterials (ENMs) have tremendous potential in many fields, but their applications and commercialization are difficult to widely implement due to their safety concerns. Recently, in silico nanosafety assessment has become an important and necessary tool to realize the safer-by-design strategy of ENMs and at the same time to reduce animal tests and exposure experiments. Here, in silico nanosafety assessment tools are classified into three categories according to their methodologies and objectives, including (i) data-driven prediction for acute toxicity, (ii) fate modeling for environmental pollution, and (iii) nano-biological interaction modeling for long-term biological effects. Released ENMs may cross environmental boundaries and undergo a variety of transformations in biological and environmental media. Therefore, the potential impacts of ENMs must be assessed from a multimedia perspective and with integrated approaches considering environmental and biological effects. Ecosystems with biodiversity and an abiotic environment may be used as an excellent integration platform to assess the community- and ecosystem-level nanosafety. In this review, the advances and challenges of in silico nanosafety assessment tools are carefully discussed. Furthermore, their integration at the ecosystem level may provide more comprehensive and reliable nanosafety assessment by establishing a site-specific interactive system among ENMs, abiotic environment, and biological communities.
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Affiliation(s)
- Hengjie Yu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
| | - Dan Luo
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, New York 14853, USA
| | - Limin Dai
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
| | - Fang Cheng
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
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11
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Afantitis A. Nanoinformatics: Artificial Intelligence and Nanotechnology in the New Decade. Comb Chem High Throughput Screen 2021; 23:4-5. [PMID: 32189589 DOI: 10.2174/138620732301200316112000] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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12
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Trinh TX, Kim J. Status Quo in Data Availability and Predictive Models of Nano-Mixture Toxicity. NANOMATERIALS 2021; 11:nano11010124. [PMID: 33430414 PMCID: PMC7826902 DOI: 10.3390/nano11010124] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 12/29/2020] [Accepted: 01/04/2021] [Indexed: 11/16/2022]
Abstract
Co-exposure of nanomaterials and chemicals can cause mixture toxicity effects to living organisms. Predictive models might help to reduce the intensive laboratory experiments required for determining the toxicity of the mixtures. Previously, concentration addition (CA), independent action (IA), and quantitative structure–activity relationship (QSAR)-based models were successfully applied to mixtures of organic chemicals. However, there were few studies concerning predictive models for toxicity of nano-mixtures before June 2020. Previous reviews provided comprehensive knowledge of computational models and mechanisms for chemical mixture toxicity. There is a gap in the reviewing of datasets and predictive models, which might cause obstacles in the toxicity assessment of nano-mixtures by using in silico approach. In this review, we collected 183 studies of nano-mixture toxicity and curated data to investigate the current data and model availability and gap and to derive research challenges to facilitate further experimental studies for data gap filling and the development of predictive models.
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Affiliation(s)
- Tung X. Trinh
- Chemical Safety Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Korea;
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
| | - Jongwoon Kim
- Chemical Safety Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Korea;
- Correspondence: ; Tel.: +82-(0)42-860-7482
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13
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Damasco JA, Ravi S, Perez JD, Hagaman DE, Melancon MP. Understanding Nanoparticle Toxicity to Direct a Safe-by-Design Approach in Cancer Nanomedicine. NANOMATERIALS (BASEL, SWITZERLAND) 2020; 10:E2186. [PMID: 33147800 PMCID: PMC7692849 DOI: 10.3390/nano10112186] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 10/26/2020] [Accepted: 10/28/2020] [Indexed: 12/22/2022]
Abstract
Nanomedicine is a rapidly growing field that uses nanomaterials for the diagnosis, treatment and prevention of various diseases, including cancer. Various biocompatible nanoplatforms with diversified capabilities for tumor targeting, imaging, and therapy have materialized to yield individualized therapy. However, due to their unique properties brought about by their small size, safety concerns have emerged as their physicochemical properties can lead to altered pharmacokinetics, with the potential to cross biological barriers. In addition, the intrinsic toxicity of some of the inorganic materials (i.e., heavy metals) and their ability to accumulate and persist in the human body has been a challenge to their translation. Successful clinical translation of these nanoparticles is heavily dependent on their stability, circulation time, access and bioavailability to disease sites, and their safety profile. This review covers preclinical and clinical inorganic-nanoparticle based nanomaterial utilized for cancer imaging and therapeutics. A special emphasis is put on the rational design to develop non-toxic/safe inorganic nanoparticle constructs to increase their viability as translatable nanomedicine for cancer therapies.
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Affiliation(s)
- Jossana A. Damasco
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (J.A.D.); (J.D.P.); (D.E.H.)
| | - Saisree Ravi
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX 78539, USA;
| | - Joy D. Perez
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (J.A.D.); (J.D.P.); (D.E.H.)
| | - Daniel E. Hagaman
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (J.A.D.); (J.D.P.); (D.E.H.)
| | - Marites P. Melancon
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (J.A.D.); (J.D.P.); (D.E.H.)
- UT Health Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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14
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Papadiamantis AG, Jänes J, Voyiatzis E, Sikk L, Burk J, Burk P, Tsoumanis A, Ha MK, Yoon TH, Valsami-Jones E, Lynch I, Melagraki G, Tämm K, Afantitis A. Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform. NANOMATERIALS (BASEL, SWITZERLAND) 2020; 10:E2017. [PMID: 33066094 PMCID: PMC7601995 DOI: 10.3390/nano10102017] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 10/03/2020] [Accepted: 10/07/2020] [Indexed: 02/07/2023]
Abstract
A literature curated dataset containing 24 distinct metal oxide (MexOy) nanoparticles (NPs), including 15 physicochemical, structural and assay-related descriptors, was enriched with 62 atomistic computational descriptors and exploited to produce a robust and validated in silico model for prediction of NP cytotoxicity. The model can be used to predict the cytotoxicity (cell viability) of MexOy NPs based on the colorimetric lactate dehydrogenase (LDH) assay and the luminometric adenosine triphosphate (ATP) assay, both of which quantify irreversible cell membrane damage. Out of the 77 total descriptors used, 7 were identified as being significant for induction of cytotoxicity by MexOy NPs. These were NP core size, hydrodynamic size, assay type, exposure dose, the energy of the MexOy conduction band (EC), the coordination number of the metal atoms on the NP surface (Avg. C.N. Me atoms surface) and the average force vector surface normal component of all metal atoms (v⟂ Me atoms surface). The significance and effect of these descriptors is discussed to demonstrate their direct correlation with cytotoxicity. The produced model has been made publicly available by the Horizon 2020 (H2020) NanoSolveIT project and will be added to the project's Integrated Approach to Testing and Assessment (IATA).
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Affiliation(s)
- Anastasios G. Papadiamantis
- NovaMechanics Ltd., Nicosia 1065, Cyprus; (A.G.P.); (E.V.); (A.T.)
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK; (E.V.-J.); (I.L.)
| | - Jaak Jänes
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | | | - Lauri Sikk
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | - Jaanus Burk
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | - Peeter Burk
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | | | - My Kieu Ha
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea; (M.K.H.); (T.H.Y.)
| | - Tae Hyun Yoon
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea; (M.K.H.); (T.H.Y.)
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
| | - Eugenia Valsami-Jones
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK; (E.V.-J.); (I.L.)
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK; (E.V.-J.); (I.L.)
| | - Georgia Melagraki
- Division of Physical Sciences and Applications, Hellenic Military Academy, 16672 Vari, Greece;
| | - Kaido Tämm
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
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15
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Zhou Q, Liu L, Liu N, He B, Hu L, Wang L. Determination and characterization of metal nanoparticles in clams and oysters. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2020; 198:110670. [PMID: 32344268 DOI: 10.1016/j.ecoenv.2020.110670] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 04/20/2020] [Indexed: 05/21/2023]
Abstract
With the extensive application of nanotechnology, metal nanoparticles (MNPs) have been widely used, thus are universally detected in the environment. This has caused increasingly concerns due to their toxicity and the potential health risks they pose to humans. In this work, the concentrations and particle size distributions of MNPs and concentrations of associated metal ionic species in shellfish seafood (clams and oysters) were investigated using single particle inductively coupled plasma mass spectrometry (sp-ICP-MS) and inductively coupled plasma mass spectrometry (ICP-MS). The MNPs in the clam and oyster tissues were extracted via an alkaline digestion method with a recovery rate of 95.9% (for gold nanoparticles (AuNPs)). Then total concentrations of 41 metal elements were measured in the two types of seafood, of which 20 were selected for sp-ICP-MS analysis. The results showed that 5 types of MNPs were detectable in clams (Y, La, Ce, Pr, Gd) and 5 types of MNPs were detectable in oysters (Y, La, Ce, Pr, Nd). Size distributions of MNPs in clams and oysters were in the range of 35-55 nm and 30-65 nm, respectively. Nanoparticle concentrations in clams and oysters ranged from 0.6 to 37.7 ng/g and 4.2-19.7 ng/g, and accounted for 3.4%-50% and 5.5%-46% of the total metal content, respectively. Based on this analysis, the health risks of metals in the two kinds of seafood were evaluated by comparing the Provisional Tolerable Weekly Intake (PTWI) with limits recommended by the World Health Organization (WHO)/Food and Agriculture Organization (FAO). These results provide important information about the presence of metal nanoparticles in seafood and, to the best of our knowledge, this is the first time that the nanoparticles of rare earth elements have been detected and reported in bivalve mollusc tissues.
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Affiliation(s)
- Qinfei Zhou
- College of Environment and Safety Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, 266042, China; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
| | - Lihong Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
| | - Nian Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
| | - Bin He
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
| | - Ligang Hu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
| | - Lina Wang
- College of Environment and Safety Engineering, Qingdao University of Science and Technology, Qingdao, Shandong, 266042, China.
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16
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Afantitis A, Melagraki G, Isigonis P, Tsoumanis A, Varsou DD, Valsami-Jones E, Papadiamantis A, Ellis LJA, Sarimveis H, Doganis P, Karatzas P, Tsiros P, Liampa I, Lobaskin V, Greco D, Serra A, Kinaret PAS, Saarimäki LA, Grafström R, Kohonen P, Nymark P, Willighagen E, Puzyn T, Rybinska-Fryca A, Lyubartsev A, Alstrup Jensen K, Brandenburg JG, Lofts S, Svendsen C, Harrison S, Maier D, Tamm K, Jänes J, Sikk L, Dusinska M, Longhin E, Rundén-Pran E, Mariussen E, El Yamani N, Unger W, Radnik J, Tropsha A, Cohen Y, Leszczynski J, Ogilvie Hendren C, Wiesner M, Winkler D, Suzuki N, Yoon TH, Choi JS, Sanabria N, Gulumian M, Lynch I. NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment. Comput Struct Biotechnol J 2020; 18:583-602. [PMID: 32226594 PMCID: PMC7090366 DOI: 10.1016/j.csbj.2020.02.023] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 02/18/2020] [Accepted: 02/29/2020] [Indexed: 01/26/2023] Open
Abstract
Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals. Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment (IATA) for human and environmental risk assessment, all within the NanoSolveIT cloud-platform. These established and well-characterized NM libraries (e.g. NanoMILE, NanoSolutions, NANoREG, NanoFASE, caLIBRAte, NanoTEST and the Nanomaterial Registry (>2000 NMs)) contain physicochemical characterization data as well as data for several relevant biological endpoints, assessed in part using harmonized Organisation for Economic Co-operation and Development (OECD) methods and test guidelines. Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse effects and to predict the effects of other NMs for which less data is available. The project specifically addresses the needs of regulatory agencies and industry to effectively and rapidly evaluate the exposure, NM hazard and risk from nanomaterials and nano-enabled products, enabling implementation of computational 'safe-by-design' approaches to facilitate NM commercialization.
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Key Words
- (quantitative) Structure–activity relationships
- AI, Artificial Intelligence
- AOPs, Adverse Outcome Pathways
- API, Application Programming interface
- CG, coarse-grained (model)
- CNTs, carbon nanotubes
- Computational toxicology
- Engineered nanomaterials
- FAIR, Findable Accessible Inter-operable and Re-usable
- GUI, Graphical Processing Unit
- HOMO-LUMO, Highest Occupied Molecular Orbital Lowest Unoccupied Molecular Orbital
- Hazard assessment
- IATA, Integrated Approaches to Testing and Assessment
- Integrated approach for testing and assessment
- KE, key events
- MIE, molecular initiating events
- ML, machine learning
- MOA, mechanism (mode) of action
- MWCNT, multi-walled carbon nanotubes
- Machine learning
- NMs, nanomaterials
- Nanoinformatics
- OECD, Organisation for Economic Co-operation and Development
- PBPK, Physiologically Based PharmacoKinetics
- PC, Protein Corona
- PChem, Physicochemical
- PTGS, Predictive Toxicogenomics Space
- Predictive modelling
- QC, quantum-chemical
- QM, quantum-mechanical
- QSAR, quantitative structure-activity relationship
- QSPR, quantitative structure-property relationship
- RA, risk assessment
- REST, Representational State Transfer
- ROS, reactive oxygen species
- Read across
- SAR, structure-activity relationship
- SMILES, Simplified Molecular Input Line Entry System
- SOPs, standard operating procedures
- Safe-by-design
- Toxicogenomics
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Affiliation(s)
| | | | | | | | | | - Eugenia Valsami-Jones
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, UK
| | - Anastasios Papadiamantis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, UK
| | - Laura-Jayne A. Ellis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, UK
| | - Haralambos Sarimveis
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece
| | - Philip Doganis
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece
| | - Pantelis Karatzas
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece
| | - Periklis Tsiros
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece
| | - Irene Liampa
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece
| | - Vladimir Lobaskin
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland
| | - Dario Greco
- Faculty of Medicine and Health Technology, University of Tampere, FI-33014, Finland
| | - Angela Serra
- Faculty of Medicine and Health Technology, University of Tampere, FI-33014, Finland
| | | | | | - Roland Grafström
- Misvik Biology OY, Itäinen Pitkäkatu 4, 20520 Turku, Finland
- Karolinska Institute, Institute of Environmental Medicine, Nobels väg 13, 17177 Stockholm, Sweden
| | - Pekka Kohonen
- Misvik Biology OY, Itäinen Pitkäkatu 4, 20520 Turku, Finland
- Karolinska Institute, Institute of Environmental Medicine, Nobels väg 13, 17177 Stockholm, Sweden
| | - Penny Nymark
- Misvik Biology OY, Itäinen Pitkäkatu 4, 20520 Turku, Finland
- Karolinska Institute, Institute of Environmental Medicine, Nobels väg 13, 17177 Stockholm, Sweden
| | - Egon Willighagen
- Department of Bioinformatics – BiGCaT, School of Nutrition and Translational Research in Metabolism, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, the Netherlands
| | - Tomasz Puzyn
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland
- University of Gdansk, Faculty of Chemistry, Wita Stwosza 63, 80-308 Gdansk, Poland
| | | | - Alexander Lyubartsev
- Institutionen för material- och miljökemi, Stockholms Universitet, 106 91 Stockholm, Sweden
| | - Keld Alstrup Jensen
- The National Research Center for the Work Environment, Lersø Parkallé 105, 2100 Copenhagen, Denmark
| | - Jan Gerit Brandenburg
- Interdisciplinary Center for Scientific Computing, Heidelberg University, Germany
- Chief Digital Organization, Merck KGaA, Frankfurter Str. 250, 64293 Darmstadt, Germany
| | - Stephen Lofts
- UK Centre for Ecology and Hydrology, Library Ave, Bailrigg, Lancaster LA1 4AP, UK
| | - Claus Svendsen
- UK Centre for Ecology and Hydrology, MacLean Bldg, Benson Ln, Crowmarsh Gifford, Wallingford OX10 8BB, UK
| | - Samuel Harrison
- UK Centre for Ecology and Hydrology, Library Ave, Bailrigg, Lancaster LA1 4AP, UK
| | - Dieter Maier
- Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany
| | - Kaido Tamm
- Department of Chemistry, University of Tartu, Ülikooli 18, 50090 Tartu, Estonia
| | - Jaak Jänes
- Department of Chemistry, University of Tartu, Ülikooli 18, 50090 Tartu, Estonia
| | - Lauri Sikk
- Department of Chemistry, University of Tartu, Ülikooli 18, 50090 Tartu, Estonia
| | - Maria Dusinska
- NILU-Norwegian Institute for Air Research, Instituttveien 18, 2002 Kjeller, Norway
| | - Eleonora Longhin
- NILU-Norwegian Institute for Air Research, Instituttveien 18, 2002 Kjeller, Norway
| | - Elise Rundén-Pran
- NILU-Norwegian Institute for Air Research, Instituttveien 18, 2002 Kjeller, Norway
| | - Espen Mariussen
- NILU-Norwegian Institute for Air Research, Instituttveien 18, 2002 Kjeller, Norway
| | - Naouale El Yamani
- NILU-Norwegian Institute for Air Research, Instituttveien 18, 2002 Kjeller, Norway
| | - Wolfgang Unger
- Federal Institute for Material Testing and Research (BAM), Unter den Eichen 44-46, 12203 Berlin, Germany
| | - Jörg Radnik
- Federal Institute for Material Testing and Research (BAM), Unter den Eichen 44-46, 12203 Berlin, Germany
| | - Alexander Tropsha
- Eschelman School of Pharmacy, University of North Carolina at Chapel Hill, 100K Beard Hall, CB# 7568, Chapel Hill, NC 27955-7568, USA
| | - Yoram Cohen
- Samueli School Of Engineering, University of California, Los Angeles, 5531 Boelter Hall, Los Angeles, CA 90095, USA
| | - Jerzy Leszczynski
- Interdisciplinary Nanotoxicity Center, Jackson State University, 1400 J. R. Lynch Street, Jackson, MS 39217, USA
| | - Christine Ogilvie Hendren
- Center for Environmental Implications of Nanotechnologies, Duke University, 121 Hudson Hall, Durham, NC 27708-0287, USA
| | - Mark Wiesner
- Center for Environmental Implications of Nanotechnologies, Duke University, 121 Hudson Hall, Durham, NC 27708-0287, USA
| | - David Winkler
- La Trobe Institute of Molecular Sciences, La Trobe University, Plenty Rd & Kingsbury Dr, Bundoora, VIC 3086, Australia
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville 3052, Australia
- CSIRO Data61, Clayton 3168, Australia
- School of Pharmacy, University of Nottingham, Nottingham, UK
| | - Noriyuki Suzuki
- National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-0053, Japan
| | - Tae Hyun Yoon
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Republic of Korea
| | - Jang-Sik Choi
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Republic of Korea
| | - Natasha Sanabria
- National Health Laboratory Services, 1 Modderfontein Rd, Sandringham, Johannesburg 2192, South Africa
| | - Mary Gulumian
- National Health Laboratory Services, 1 Modderfontein Rd, Sandringham, Johannesburg 2192, South Africa
- Haematology and Molecular Medicine, University of the Witwatersrand, Johannesburg, South Africa
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, UK
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17
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Mei N, Hedberg J, Odnevall Wallinder I, Blomberg E. Influence of Biocorona Formation on the Transformation and Dissolution of Cobalt Nanoparticles under Physiological Conditions. ACS OMEGA 2019; 4:21778-21791. [PMID: 31891055 PMCID: PMC6933593 DOI: 10.1021/acsomega.9b02641] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 11/14/2019] [Indexed: 06/10/2023]
Abstract
Cobalt (Co) nanoparticles (NPs) are produced in different applications and unintentionally generated at several occupational and traffic settings. Their diffuse dispersion may lead to interactions with humans and aquatic organisms via different exposure routes that include their transformation/dissolution in biological media. This paper has investigated the particle stability and reactivity of Co NPs (dispersed by sonication prior to exposure) interacting with selected individual biomolecules (amino acids, polypeptides, and proteins) in phosphate-buffered saline (PBS). No or minor adsorption of amino acids (glutamine, glutamic acid, lysine, and cysteine) was observed on the Co NPs, independent of the functional group and charge. Instead, phosphate adsorption resulted in the formation of a surface layer (a corona) of Co phosphate. The adsorption of larger biomolecules (polyglutamic acid, polylysine, lysozyme, and mucin) was evident in parallel with the formation of Co phosphate. The dissolution of the Co NPs was rapid as 35-55% of the particle mass was dissolved within the first hour of exposure. The larger biomolecules suppressed the dissolution initially compared to exposure in PBS only, whereas the dissolution was essentially unaffected by the presence of amino acids, with cysteine as an exception. The formation of Co phosphate on the NP surface reduced the protective properties of the surface oxide of the Co NPs, as seen from the increased levels of the released Co when compared with the nonphosphate-containing saline. The results underline the diversity of possible outcomes with respect to surface characteristics and dissolution of Co NPs in biological media and emphasize the importance of surface interactions with phosphate on the NP characteristics and reactivity.
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Affiliation(s)
- Nanxuan Mei
- KTH
Royal Institute of Technology, Department of Chemistry, Division of Surface and Corrosion Science, Stockholm 114 28, Sweden
| | - Jonas Hedberg
- KTH
Royal Institute of Technology, Department of Chemistry, Division of Surface and Corrosion Science, Stockholm 114 28, Sweden
| | - Inger Odnevall Wallinder
- KTH
Royal Institute of Technology, Department of Chemistry, Division of Surface and Corrosion Science, Stockholm 114 28, Sweden
| | - Eva Blomberg
- KTH
Royal Institute of Technology, Department of Chemistry, Division of Surface and Corrosion Science, Stockholm 114 28, Sweden
- Division
Bioscience and Materials, RISE Research
Institutes of Sweden, Stockholm 111 21, Sweden
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18
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Yan X, Sedykh A, Wang W, Zhao X, Yan B, Zhu H. In silico profiling nanoparticles: predictive nanomodeling using universal nanodescriptors and various machine learning approaches. NANOSCALE 2019; 11:8352-8362. [PMID: 30984943 DOI: 10.1039/c9nr00844f] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Rational nanomaterial design is urgently demanded for new nanomaterial development with desired properties. However, computational nanomaterial modeling and virtual nanomaterial screening are not applicable for this purpose due to the complexity of nanomaterial structures. To address this challenge, a new computational workflow is established in this study to virtually profile nanoparticles by (1) constructing a structurally diverse virtual gold nanoparticle (GNP) library and (2) developing novel universal nanodescriptors. The emphasis of this study is the second task by developing geometrical nanodescriptors that are suitable for the quantitative modeling of GNPs and virtual screening purposes. The feasibility, rigor and applicability of this novel computational method are validated by testing seven GNP datasets consisting of 191 unique GNPs of various nano-bioactivities and physicochemical properties. The high predictability of the developed GNP models suggests that this workflow can be used as a universal tool for nanomaterial profiling and rational nanomaterial design.
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Affiliation(s)
- Xiliang Yan
- School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100, China
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19
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Hedberg J, Blomberg E, Odnevall Wallinder I. In the Search for Nanospecific Effects of Dissolution of Metallic Nanoparticles at Freshwater-Like Conditions: A Critical Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:4030-4044. [PMID: 30908015 DOI: 10.1021/acs.est.8b05012] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Knowledge on relations between particle properties and dissolution/transformation characteristics of metal and metal oxide nanoparticles (NPs) in freshwater is important for risk assessment and product development. This critical review aims to elucidate nanospecific effects on dissolution of metallic NPs in freshwater and similar media. Dissolution rate constants are compiled and analyzed for NPs of silver (Ag), copper (Cu), copper oxide/hydroxide (CuO, Cu(OH)2), zinc oxide (ZnO), manganese (Mn), and aluminum (Al), showing largely varying (orders of magnitude) constants when modeled using first order kinetics. An effect of small primary sizes (<15 nm) was observed, leading to increased dissolution rate constants and solubility in some cases. However, the often extensive particle agglomeration can result in reduced nanospecific effects on dissolution and also an increased uncertainty related to the surface area, a parameter that largely influence the extent of dissolution. Promising ways to model surface areas of NPs in solution using fractal dimensions and size distributions are discussed in addition to nanospecific aspects related to other processes such as corrosion, adsorption of natural organic matter (NOM), presence of capping agents, and existence of surface defects. The importance of the experimental design on the results of dissolution experiments of metal and metal oxide NPs is moreover highlighted, including the influence of ionic metal solubility and choice of particle dispersion methodology.
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Affiliation(s)
- Jonas Hedberg
- KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Chemistry , Division of Surface and Corrosion Science , Stockholm , Sweden
| | - Eva Blomberg
- KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Chemistry , Division of Surface and Corrosion Science , Stockholm , Sweden
- RISE Research Institutes of Sweden , Division Bioscience and Materials , Stockholm , Sweden
| | - Inger Odnevall Wallinder
- KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Chemistry , Division of Surface and Corrosion Science , Stockholm , Sweden
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20
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Wang J, Wang Y, Huang Y, Peijnenburg WJG, Chen J, Li X. Development of a nano-QSPR model to predict band gaps of spherical metal oxide nanoparticles. RSC Adv 2019; 9:8426-8434. [PMID: 35518709 PMCID: PMC9061875 DOI: 10.1039/c8ra10226k] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 03/06/2019] [Indexed: 01/11/2023] Open
Abstract
Antibacterial activities and cytotoxicity of metal oxide nanoparticles are determined by their special band structures, which also influence their potential ecological risks. Traditional experimental determination of the band gap is time-consuming, while the accuracy of theoretical computation depends on the selected algorithm, for which higher precision algorithms, being more expensive, can give a more accurate band gap. Therefore, in this study, a quantitative structure–property relationship (QSPR) model, highlighting the influence of crystalline type and material size, was developed to predict the band gap of metal oxide nanoparticles rapidly and accurately. The structural descriptors for metal oxide nanoparticles were generated via quantum chemistry computations, among which heat of formation and beta angle of the unit cell were the most important parameters influencing band gaps. The developed model shows great robustness and predictive ability (R2 = 0.848, RMSE = 0.378 eV, RMSECV = 0.478 eV, QEXT2 = 0.814, RMSEP = 0.408 eV). The current study can assist in screening the ecological risks of existing metal oxide nanoparticles and may act as a reference for newly designed materials. Antibacterial activities and cytotoxicity of metal oxide nanoparticles are determined by their special band structures, which also influence their potential ecological risks.![]()
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Affiliation(s)
- Jiaxing Wang
- Key Laboratory of Industrial Ecology and Environmental Engineering (MOE)
- School of Environmental Science and Technology
- Dalian University of Technology
- Dalian 116024
- China
| | - Ya Wang
- Key Laboratory of Industrial Ecology and Environmental Engineering (MOE)
- School of Environmental Science and Technology
- Dalian University of Technology
- Dalian 116024
- China
| | - Yang Huang
- Key Laboratory of Industrial Ecology and Environmental Engineering (MOE)
- School of Environmental Science and Technology
- Dalian University of Technology
- Dalian 116024
- China
| | - Willie J. G. M. Peijnenburg
- Institute of Environmental Sciences
- Leiden University
- 2300 RA Leiden
- The Netherlands
- National Institute of Public Health and the Environment
| | - Jingwen Chen
- Key Laboratory of Industrial Ecology and Environmental Engineering (MOE)
- School of Environmental Science and Technology
- Dalian University of Technology
- Dalian 116024
- China
| | - Xuehua Li
- Key Laboratory of Industrial Ecology and Environmental Engineering (MOE)
- School of Environmental Science and Technology
- Dalian University of Technology
- Dalian 116024
- China
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21
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Burk J, Sikk L, Burk P, Manshian BB, Soenen SJ, Scott-Fordsmand JJ, Tamm T, Tämm K. Fe-Doped ZnO nanoparticle toxicity: assessment by a new generation of nanodescriptors. NANOSCALE 2018; 10:21985-21993. [PMID: 30452031 DOI: 10.1039/c8nr05220d] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
In the search for novel tools to combat cancer, nanoparticles (NPs) have attracted a lot of attention. Recently, the controlled release of cancer-cell-killing metal ions from doped NPs has shown promise, but fine tuning of dissolution kinetics is required to ensure specificity and minimize undesirable toxic side-effects. Theoretical tools to help in reaching a proper understanding and finally be able to control the dissolution kinetics by NP design have not been available until now. Here, we present a novel set of true nanodescriptors to analyze the charge distribution, the effect of doping and surface coating of whole metal oxide NP structures. The polarizable model of oxygen atoms enables light to be shed on the charge distribution on the NP surface, allowing the in detail study of the factors influencing the release of metal ions from NPs. The descriptors and their capabilities are demonstrated on a Fe-doped ZnO nanoparticle system, a system with practical outlook and available experimental data.
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Affiliation(s)
- Jaanus Burk
- Institute of Chemistry, University of Tartu, Ravila 14a, Tartu 50411, Estonia.
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22
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Afantitis A, Melagraki G, Tsoumanis A, Valsami-Jones E, Lynch I. A nanoinformatics decision support tool for the virtual screening of gold nanoparticle cellular association using protein corona fingerprints. Nanotoxicology 2018; 12:1148-1165. [PMID: 30182778 DOI: 10.1080/17435390.2018.1504998] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The increasing use of nanoparticles (NPs) in a wide range of consumer and industrial applications has necessitated significant effort to address the challenge of characterizing and quantifying the underlying nanostructure - biological response relationships to ensure that these novel materials can be exploited responsibly and safely. Such efforts demand reliable experimental data not only in terms of the biological dose-response, but also regarding the physicochemical properties of the NPs and their interaction with the biological environment. The latter has not been extensively studied, as a large surface to bind biological macromolecules is a unique feature of NPs that is not relevant for chemicals or pharmaceuticals, and thus only limited data have been reported in the literature quantifying the protein corona formed when NPs interact with a biological medium and linking this with NP cellular association/uptake. In this work we report the development of a predictive model for the assessment of the biological response (cellular association, which can include both internalized NPs and those attached to the cell surface) of surface-modified gold NPs, based on their physicochemical properties and protein corona fingerprints, utilizing a dataset of 105 unique NPs. Cellular association was chosen as the end-point for the original experimental study due to its relevance to inflammatory responses, biodistribution, and toxicity in vivo. The validated predictive model is freely available online through the Enalos Cloud Platform ( http://enalos.insilicotox.com/NanoProteinCorona/ ) to be used as part of a regulatory or NP safe-by-design decision support system. This online tool will allow the virtual screening of NPs, based on a list of the significant NP descriptors, identifying those NPs that would warrant further toxicity testing on the basis of predicted NP cellular association.
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Affiliation(s)
| | | | | | - Eugenia Valsami-Jones
- b School of Geography Earth and Environmental Sciences , University of Birmingham , Birmingham , United Kingdom
| | - Iseult Lynch
- b School of Geography Earth and Environmental Sciences , University of Birmingham , Birmingham , United Kingdom
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23
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Siegrist S, Cörek E, Detampel P, Sandström J, Wick P, Huwyler J. Preclinical hazard evaluation strategy for nanomedicines. Nanotoxicology 2018; 13:73-99. [PMID: 30182784 DOI: 10.1080/17435390.2018.1505000] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The increasing nanomedicine usage has raised concerns about their possible impact on human health. Present evaluation strategies for nanomaterials rely on a case-by-case hazard assessment. They take into account material properties, biological interactions, and toxicological responses. Authorities have also emphasized that exposure route and intended use should be considered in the safety assessment of nanotherapeutics. In contrast to an individual assessment of nanomaterial hazards, we propose in the present work a novel and unique evaluation strategy designed to uncover potential adverse effects of such materials. We specifically focus on spherical engineered nanoparticles used as parenterally administered nanomedicines. Standardized assay protocols from the US Nanotechnology Characterization Laboratory as well as the EU Nanomedicine Characterisation Laboratory can be used for experimental data generation. We focus on both cellular uptake and intracellular persistence as main indicators for nanoparticle hazard potentials. Based on existing regulatory specifications defined by authorities such as the European Medicines Agency and the United States Food and Drug Administration, we provide a robust framework for application-oriented classification paired with intuitive decision making. The Hazard Evaluation Strategy (HES) for injectable nanoparticles is a three-tiered concept covering physicochemical characterization, nanoparticle (bio)interactions, and hazard assessment. It is cost-effective and can assist in the design and optimization of nanoparticles intended for therapeutic use. Furthermore, this concept is designed to be adaptable for alternative exposure and application scenarios. To the knowledge of the authors, the HES is unique in its methodology based on exclusion criteria. It is the first hazard evaluation strategy designed for nanotherapeutics.
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Affiliation(s)
- Stefan Siegrist
- a Division of Pharmaceutical Technology , Pharmacenter, University of Basel , Basel , Switzerland
| | - Emre Cörek
- a Division of Pharmaceutical Technology , Pharmacenter, University of Basel , Basel , Switzerland
| | - Pascal Detampel
- a Division of Pharmaceutical Technology , Pharmacenter, University of Basel , Basel , Switzerland
| | - Jenny Sandström
- b Swiss Centre for Applied Human Toxicology , Basel , Switzerland
| | - Peter Wick
- c Laboratory for Patricles-Biology Interactions , Empa Swiss Federal Laboratories for Materials Science and Technology , St. Gallen , Switzerland
| | - Jörg Huwyler
- a Division of Pharmaceutical Technology , Pharmacenter, University of Basel , Basel , Switzerland
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24
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Gozalbes R, Vicente de Julián-Ortiz J. Applications of Chemoinformatics in Predictive Toxicology for Regulatory Purposes, Especially in the Context of the EU REACH Legislation. ACTA ACUST UNITED AC 2018. [DOI: 10.4018/ijqspr.2018010101] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Chemoinformatics methodologies such as QSAR/QSPR have been used for decades in drug discovery projects, especially for the finding of new compounds with therapeutic properties and the optimization of ADME properties on chemical series. The application of computational techniques in predictive toxicology is much more recent, and they are experiencing an increasingly interest because of the new legal requirements imposed by national and international regulations. In the pharmaceutical field, the US Food and Drug Administration (FDA) support the use of predictive models for regulatory decision-making when assessing the genotoxic and carcinogenic potential of drug impurities. In Europe, the REACH legislation promotes the use of QSAR in order to reduce the huge amount of animal testing needed to demonstrate the safety of new chemical entities subjected to registration, provided they meet specific conditions to ensure their quality and predictive power. In this review, the authors summarize the state of art of in silico methods for regulatory purposes, with especial emphasis on QSAR models.
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25
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Chen G, Peijnenburg W, Xiao Y, Vijver MG. Current Knowledge on the Use of Computational Toxicology in Hazard Assessment of Metallic Engineered Nanomaterials. Int J Mol Sci 2017; 18:ijms18071504. [PMID: 28704975 PMCID: PMC5535994 DOI: 10.3390/ijms18071504] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 07/07/2017] [Accepted: 07/10/2017] [Indexed: 11/16/2022] Open
Abstract
As listed by the European Chemicals Agency, the three elements in evaluating the hazards of engineered nanomaterials (ENMs) include the integration and evaluation of toxicity data, categorization and labeling of ENMs, and derivation of hazard threshold levels for human health and the environment. Assessing the hazards of ENMs solely based on laboratory tests is time-consuming, resource intensive, and constrained by ethical considerations. The adoption of computational toxicology into this task has recently become a priority. Alternative approaches such as (quantitative) structure-activity relationships ((Q)SAR) and read-across are of significant help in predicting nanotoxicity and filling data gaps, and in classifying the hazards of ENMs to individual species. Thereupon, the species sensitivity distribution (SSD) approach is able to serve the establishment of ENM hazard thresholds sufficiently protecting the ecosystem. This article critically reviews the current knowledge on the development of in silico models in predicting and classifying the hazard of metallic ENMs, and the development of SSDs for metallic ENMs. Further discussion includes the significance of well-curated experimental datasets and the interpretation of toxicity mechanisms of metallic ENMs based on reported models. An outlook is also given on future directions of research in this frontier.
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Affiliation(s)
- Guangchao Chen
- Institute of Environmental Sciences, Leiden University, 2300 RA Leiden, The Netherlands.
| | - Willie Peijnenburg
- Institute of Environmental Sciences, Leiden University, 2300 RA Leiden, The Netherlands.
- Centre for Safety of Substances and Products, National Institute of Public Health and the Environment (RIVM), Bilthoven, 3720 BA Bilthoven, The Netherlands.
| | - Yinlong Xiao
- Institute of Environmental Sciences, Leiden University, 2300 RA Leiden, The Netherlands.
| | - Martina G Vijver
- Institute of Environmental Sciences, Leiden University, 2300 RA Leiden, The Netherlands.
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26
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Manshian BB, Pokhrel S, Himmelreich U, Tämm K, Sikk L, Fernández A, Rallo R, Tamm T, Mädler L, Soenen SJ. In Silico Design of Optimal Dissolution Kinetics of Fe-Doped ZnO Nanoparticles Results in Cancer-Specific Toxicity in a Preclinical Rodent Model. Adv Healthc Mater 2017; 6. [PMID: 28230930 DOI: 10.1002/adhm.201601379] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 01/12/2017] [Indexed: 11/06/2022]
Abstract
Cancer cells have unique but widely varying characteristics that have proven them difficult to be treated by classical therapeutics and calls for novel and selective treatment options. Nanomaterials (NMs) have been shown to display biological effects as a function of their chemical composition, and the extent and exact nature of these effects can vary between different biological environments. Here, ZnO NMs are doped with increasing levels of Fe, which allows to finely tune their dissolution rate resulting in significant differences in their biological behavior on cancer or normal cells. Based on in silico analysis, 2% Fe-doped ZnO NMs are found to be optimal to cause selective cancer cell death, which is confirmed in both cultured cells and syngeneic tumor models, where they also reduce metastasis formation. These results show that upon tuning NM chemical composition, NMs can be designed as a targeted selective anticancer therapy.
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Affiliation(s)
- Bella B. Manshian
- Department of Imaging and Pathology KU Leuven Herestraat 49 B3000 Leuven Belgium
| | - Suman Pokhrel
- Foundation Institute of Materials Science (IWT) Department of Production Engineering University of Bremen 28359 Bremen Germany
| | - Uwe Himmelreich
- Department of Imaging and Pathology KU Leuven Herestraat 49 B3000 Leuven Belgium
| | - Kaido Tämm
- Department of Chemistry University of Tartu Ravila 14a, 50411 Estonia
| | - Lauri Sikk
- Department of Chemistry University of Tartu Ravila 14a, 50411 Estonia
| | - Alberto Fernández
- Departament d'Enginyeria Quimica Universitat Rovira i Virgili Av. Paisos Catalans, 26 43007 Tarragona Spain
| | - Robert Rallo
- Departament d'Enginyeria Informatica i Matematiques Universitat Rovira i Virgili Av. Paisos Catalans 26 43007 Tarragona Spain
| | - Tarmo Tamm
- Institute of Technology University of Tartu Nooruse 1 Tartu 50411 Estonia
| | - Lutz Mädler
- Foundation Institute of Materials Science (IWT) Department of Production Engineering University of Bremen 28359 Bremen Germany
| | - Stefaan J. Soenen
- Department of Imaging and Pathology KU Leuven Herestraat 49 B3000 Leuven Belgium
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