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Banerjee P, Kemmler E, Dunkel M, Preissner R. ProTox 3.0: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Res 2024; 52:W513-W520. [PMID: 38647086 PMCID: PMC11223834 DOI: 10.1093/nar/gkae303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 03/26/2024] [Accepted: 04/09/2024] [Indexed: 04/25/2024] Open
Abstract
Interaction with chemicals, present in drugs, food, environments, and consumer goods, is an integral part of our everyday life. However, depending on the amount and duration, such interactions can also result in adverse effects. With the increase in computational methods, the in silico methods can offer significant benefits to both regulatory needs and requirements for risk assessments and the pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox 3.0, which incorporates molecular similarity and machine-learning models for the prediction of 61 toxicity endpoints such as acute toxicity, organ toxicity, clinical toxicity, molecular-initiating events (MOE), adverse outcomes (Tox21) pathways, several other toxicological endpoints and toxicity off-targets. All the ProTox 3.0 models are validated on independent external sets and have shown strong performance. ProTox envisages itself as a complete, freely available computational platform for in silico toxicity prediction for toxicologists, regulatory agencies, computational chemists, and medicinal chemists. The ProTox 3.0 webserver is free and open to all users, and there is no login requirement and can be accessed via https://tox.charite.de. The web server takes a 2D chemical structure as input and reports the toxicological profile of the compound for each endpoint with a confidence score and overall toxicity radar plot and network plot.
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Affiliation(s)
- Priyanka Banerjee
- Institute for Physiology & Science-IT, Charité – University Medicine Berlin, 10115 Berlin, Germany
- Member of the KFO 339: Food Allergy and Tolerance (Food@), Clinical Research Unit funded by the German Research Foundation, Berlin, Germany
| | - Emanuel Kemmler
- Institute for Physiology & Science-IT, Charité – University Medicine Berlin, 10115 Berlin, Germany
- Member of the KFO 339: Food Allergy and Tolerance (Food@), Clinical Research Unit funded by the German Research Foundation, Berlin, Germany
| | - Mathias Dunkel
- Institute for Physiology & Science-IT, Charité – University Medicine Berlin, 10115 Berlin, Germany
| | - Robert Preissner
- Institute for Physiology & Science-IT, Charité – University Medicine Berlin, 10115 Berlin, Germany
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2
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Serafini MM, Sepehri S, Midali M, Stinckens M, Biesiekierska M, Wolniakowska A, Gatzios A, Rundén-Pran E, Reszka E, Marinovich M, Vanhaecke T, Roszak J, Viviani B, SenGupta T. Recent advances and current challenges of new approach methodologies in developmental and adult neurotoxicity testing. Arch Toxicol 2024; 98:1271-1295. [PMID: 38480536 DOI: 10.1007/s00204-024-03703-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/06/2024] [Indexed: 03/27/2024]
Abstract
Adult neurotoxicity (ANT) and developmental neurotoxicity (DNT) assessments aim to understand the adverse effects and underlying mechanisms of toxicants on the human nervous system. In recent years, there has been an increasing focus on the so-called new approach methodologies (NAMs). The Organization for Economic Co-operation and Development (OECD), together with European and American regulatory agencies, promote the use of validated alternative test systems, but to date, guidelines for regulatory DNT and ANT assessment rely primarily on classical animal testing. Alternative methods include both non-animal approaches and test systems on non-vertebrates (e.g., nematodes) or non-mammals (e.g., fish). Therefore, this review summarizes the recent advances of NAMs focusing on ANT and DNT and highlights the potential and current critical issues for the full implementation of these methods in the future. The status of the DNT in vitro battery (DNT IVB) is also reviewed as a first step of NAMs for the assessment of neurotoxicity in the regulatory context. Critical issues such as (i) the need for test batteries and method integration (from in silico and in vitro to in vivo alternatives, e.g., zebrafish, C. elegans) requiring interdisciplinarity to manage complexity, (ii) interlaboratory transferability, and (iii) the urgent need for method validation are discussed.
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Affiliation(s)
- Melania Maria Serafini
- Department of Pharmacological and Biomolecular Sciences, "Rodolfo Paoletti", Università degli Studi di Milano, Milan, Italy.
| | - Sara Sepehri
- Department of In Vitro Toxicology and Dermato-Cosmetology (IVTD), Vrije Universiteit Brussels, Brussels, Belgium
| | - Miriam Midali
- Department of Pharmacological and Biomolecular Sciences, "Rodolfo Paoletti", Università degli Studi di Milano, Milan, Italy
| | - Marth Stinckens
- Department of In Vitro Toxicology and Dermato-Cosmetology (IVTD), Vrije Universiteit Brussels, Brussels, Belgium
| | - Marta Biesiekierska
- Department of Translational Research, Nofer Institute of Occupational Medicine, Lodz, Poland
| | - Anna Wolniakowska
- Department of Translational Research, Nofer Institute of Occupational Medicine, Lodz, Poland
| | - Alexandra Gatzios
- Department of In Vitro Toxicology and Dermato-Cosmetology (IVTD), Vrije Universiteit Brussels, Brussels, Belgium
| | - Elise Rundén-Pran
- The Climate and Environmental Research Institute NILU, Kjeller, Norway
| | - Edyta Reszka
- Department of Translational Research, Nofer Institute of Occupational Medicine, Lodz, Poland
| | - Marina Marinovich
- Department of Pharmacological and Biomolecular Sciences, "Rodolfo Paoletti", Università degli Studi di Milano, Milan, Italy
- Center of Research on New Approach Methodologies (NAMs) in chemical risk assessment (SAFE-MI), Università degli Studi di Milano, Milan, Italy
| | - Tamara Vanhaecke
- Department of In Vitro Toxicology and Dermato-Cosmetology (IVTD), Vrije Universiteit Brussels, Brussels, Belgium
| | - Joanna Roszak
- Department of Translational Research, Nofer Institute of Occupational Medicine, Lodz, Poland
| | - Barbara Viviani
- Department of Pharmacological and Biomolecular Sciences, "Rodolfo Paoletti", Università degli Studi di Milano, Milan, Italy
- Center of Research on New Approach Methodologies (NAMs) in chemical risk assessment (SAFE-MI), Università degli Studi di Milano, Milan, Italy
| | - Tanima SenGupta
- The Climate and Environmental Research Institute NILU, Kjeller, Norway
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3
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Tal T, Myhre O, Fritsche E, Rüegg J, Craenen K, Aiello-Holden K, Agrillo C, Babin PJ, Escher BI, Dirven H, Hellsten K, Dolva K, Hessel E, Heusinkveld HJ, Hadzhiev Y, Hurem S, Jagiello K, Judzinska B, Klüver N, Knoll-Gellida A, Kühne BA, Leist M, Lislien M, Lyche JL, Müller F, Colbourne JK, Neuhaus W, Pallocca G, Seeger B, Scharkin I, Scholz S, Spjuth O, Torres-Ruiz M, Bartmann K. New approach methods to assess developmental and adult neurotoxicity for regulatory use: a PARC work package 5 project. FRONTIERS IN TOXICOLOGY 2024; 6:1359507. [PMID: 38742231 PMCID: PMC11089904 DOI: 10.3389/ftox.2024.1359507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/18/2024] [Indexed: 05/16/2024] Open
Abstract
In the European regulatory context, rodent in vivo studies are the predominant source of neurotoxicity information. Although they form a cornerstone of neurotoxicological assessments, they are costly and the topic of ethical debate. While the public expects chemicals and products to be safe for the developing and mature nervous systems, considerable numbers of chemicals in commerce have not, or only to a limited extent, been assessed for their potential to cause neurotoxicity. As such, there is a societal push toward the replacement of animal models with in vitro or alternative methods. New approach methods (NAMs) can contribute to the regulatory knowledge base, increase chemical safety, and modernize chemical hazard and risk assessment. Provided they reach an acceptable level of regulatory relevance and reliability, NAMs may be considered as replacements for specific in vivo studies. The European Partnership for the Assessment of Risks from Chemicals (PARC) addresses challenges to the development and implementation of NAMs in chemical risk assessment. In collaboration with regulatory agencies, Project 5.2.1e (Neurotoxicity) aims to develop and evaluate NAMs for developmental neurotoxicity (DNT) and adult neurotoxicity (ANT) and to understand the applicability domain of specific NAMs for the detection of endocrine disruption and epigenetic perturbation. To speed up assay time and reduce costs, we identify early indicators of later-onset effects. Ultimately, we will assemble second-generation developmental neurotoxicity and first-generation adult neurotoxicity test batteries, both of which aim to provide regulatory hazard and risk assessors and industry stakeholders with robust, speedy, lower-cost, and informative next-generation hazard and risk assessment tools.
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Affiliation(s)
- Tamara Tal
- Helmholtz Centre for Environmental Research – UFZ, Chemicals in the Environment Research Section, Leipzig, Germany
- University of Leipzig, Medical Faculty, Leipzig, Germany
| | - Oddvar Myhre
- Norwegian Institute of Public Health – NIPH, Department of Chemical Toxicology, Oslo, Norway
| | - Ellen Fritsche
- IUF – Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
- DNTOX GmbH, Düsseldorf, Germany
- Swiss Centre for Applied Human Toxicology, University of Basel, Basel, Switzerland
| | - Joëlle Rüegg
- Uppsala University, Department of Organismal Biology, Uppsala, Sweden
| | - Kai Craenen
- European Chemicals Agency (ECHA), Helsinki, Finland
| | | | - Caroline Agrillo
- Uppsala University, Department of Organismal Biology, Uppsala, Sweden
| | - Patrick J. Babin
- Université de Bordeaux, Institut National de la Santé et de la Recherche Médicale (INSERM), Maladies Rares: Génétique et Métabolisme (MRGM), Pessac, France
| | - Beate I. Escher
- Helmholtz Centre for Environmental Research – UFZ, Chemicals in the Environment Research Section, Leipzig, Germany
| | - Hubert Dirven
- Norwegian Institute of Public Health – NIPH, Department of Chemical Toxicology, Oslo, Norway
| | | | - Kristine Dolva
- University of Oslo, Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, Olso, Norway
| | - Ellen Hessel
- Dutch Nation Institute for Public Health and the Environment (RIVM), Centre for Health Protection, Bilthoven, Netherlands
| | - Harm J. Heusinkveld
- Dutch Nation Institute for Public Health and the Environment (RIVM), Centre for Health Protection, Bilthoven, Netherlands
| | - Yavor Hadzhiev
- University of Birmingham, Centre for Environmental Research and Justice, Birmingham, UK
| | - Selma Hurem
- Norwegian University of Life Sciences (NMBU), Faculty of Veterinary Medicine, Ås, Norway
| | - Karolina Jagiello
- University of Gdansk, Laboratory of Environmental Chemoinformatics, Gdansk, Poland
| | - Beata Judzinska
- University of Gdansk, Laboratory of Environmental Chemoinformatics, Gdansk, Poland
| | - Nils Klüver
- Helmholtz Centre for Environmental Research – UFZ, Chemicals in the Environment Research Section, Leipzig, Germany
| | - Anja Knoll-Gellida
- Université de Bordeaux, Institut National de la Santé et de la Recherche Médicale (INSERM), Maladies Rares: Génétique et Métabolisme (MRGM), Pessac, France
| | - Britta A. Kühne
- University of Veterinary Medicine Hannover, Foundation, Institute for Food Quality and Food Safety, Hannover, Germany
| | - Marcel Leist
- University of Konstanz, In Vitro Toxicology and Biomedicine/CAAT-Europe, Konstanz, Germany
| | - Malene Lislien
- Norwegian Institute of Public Health – NIPH, Department of Chemical Toxicology, Oslo, Norway
| | - Jan L. Lyche
- Norwegian University of Life Sciences (NMBU), Faculty of Veterinary Medicine, Ås, Norway
| | - Ferenc Müller
- University of Birmingham, Centre for Environmental Research and Justice, Birmingham, UK
| | - John K. Colbourne
- University of Birmingham, Centre for Environmental Research and Justice, Birmingham, UK
| | - Winfried Neuhaus
- AIT Austrian Institute of Technology GmbH, Competence Unit Molecular Diagnostics, Center Health and Bioresources, Vienna, Austria
- Danube Private University, Faculty of Dentistry and Medicine, Department of Medicine, Krems, Austria
| | - Giorgia Pallocca
- University of Konstanz, In Vitro Toxicology and Biomedicine/CAAT-Europe, Konstanz, Germany
| | - Bettina Seeger
- University of Veterinary Medicine Hannover, Foundation, Institute for Food Quality and Food Safety, Hannover, Germany
| | - Ilka Scharkin
- IUF – Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Stefan Scholz
- Helmholtz Centre for Environmental Research – UFZ, Chemicals in the Environment Research Section, Leipzig, Germany
| | - Ola Spjuth
- Uppsala University and Science for Life Laboratory, Department of Pharmaceutical Biosciences, Uppsala, Sweden
| | - Monica Torres-Ruiz
- Instituto de Salud Carlos III (ISCIII), Centro Nacional de Sanidad Ambiental (CNSA), Environmental Toxicology Unit, Majadahonda, Spain
| | - Kristina Bartmann
- IUF – Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
- DNTOX GmbH, Düsseldorf, Germany
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4
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He X, Yang Z, Wang L, Sun Y, Cao H, Liang Y. NeuTox: A weighted ensemble model for screening potential neuronal cytotoxicity of chemicals based on various types of molecular representations. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133443. [PMID: 38198870 DOI: 10.1016/j.jhazmat.2024.133443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
Chemical-induced neurotoxicity has been widely brought into focus in the risk assessment of chemical safety. However, the traditional in vivo animal models to evaluate neurotoxicity are time-consuming and expensive, which cannot completely represent the pathophysiology of neurotoxicity in humans. Cytotoxicity to human neuroblastoma cell line (SH-SY5Y) is commonly used as an alternative to animal testing for the assessment of neurotoxicity, yet it is still not appropriate for high throughput screening of potential neuronal cytotoxicity of chemicals. In this study, we constructed an ensemble prediction model, termed NeuTox, by combining multiple machine learning algorithms with molecular representations based on the weighted score of Particle Swarm Optimization. For the test set, NeuTox shows excellent performance with an accuracy of 0.9064, which are superior to the top-performing individual models. The subsequent experimental verifications reveal that 5,5'-isopropylidenedi-2-biphenylol and 4,4'-cyclo-hexylidenebisphenol exhibited stronger SH-SY5Y-based cytotoxicity compared to bisphenol A, suggesting that NeuTox has good generalization ability in the first-tier assessment of neuronal cytotoxicity of BPA analogs. For ease of use, NeuTox is presented as an online web server that can be freely accessed via http://www.iehneutox-predictor.cn/NeuToxPredict/Predict.
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Affiliation(s)
- Xuejun He
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Zeguo Yang
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Ling Wang
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Yuzhen Sun
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Huiming Cao
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China.
| | - Yong Liang
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China
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5
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Li R, Zhang Z, Xuan Y, Wang Y, Zhong Y, Zhang L, Zhang J, Chen Q, Yu S, Yuan J. HNF4A as a potential target of PFOA and PFOS leading to hepatic steatosis: Integrated molecular docking, molecular dynamic and transcriptomic analyses. Chem Biol Interact 2024; 390:110867. [PMID: 38199259 DOI: 10.1016/j.cbi.2024.110867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 12/30/2023] [Accepted: 01/08/2024] [Indexed: 01/12/2024]
Abstract
Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are indeed among the most well known and extensively studied Per- and polyfluoroalkyl substances (PFASs), and increasing evidence confirm their effects on human health, especially liver steatosis. Nonetheless, the molecular mechanisms of their initiation of hepatic steatosis is still elusive. Therefore, potential targets of PFOA/PFOS must be explored to ameliorate its adverse consequences. This research aims to investigate the molecular mechanisms of PFOA and PFOS-induced liver steatosis, with emphasis on identifying a potential target that links these PFASs to liver steatosis. The potential target that causes PFOA and PFOS-induced liver steatosis have been explored and determined based on molecular docking, molecular dynamics (MD) simulation, and transcriptomics analysis. In silico results show that PFOA/PFOS can form a stable binding conformation with HNF4A, and PFOA/PFOS may interact with HNF4A to affect the downstream conduction mechanism. Transcriptome data from PFOA/PFOS-induced human stem cell spheres showed that HNF4A was inhibited, suggesting that PFOA/PFOS may constrain its function. PFOS mainly down-regulated genes related to cholesterol synthesis while PFOA mainly up-regulated genes related to fatty acid β-oxidation. This study explored the toxicological mechanism of liver steatosis caused by PFOA/PFOS. These compounds might inhibit and down-regulate HNF4A, which is the molecular initiation events (MIE) that induces liver steatosis.
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Affiliation(s)
- Rui Li
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Zijing Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Yuxin Xuan
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Yulu Wang
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Yuyan Zhong
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Lingyin Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Jinrui Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Qian Chen
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China
| | - Shuling Yu
- Key Laboratory of Natural Medicine and Immune-Engineering of Henan Province, Henan University, Kaifeng, Henan, 475004, PR China
| | - Jintao Yuan
- College of Public Health, Zhengzhou University, Zhengzhou, 450001, PR China.
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6
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Zhang L, Li M, Zhang D, Zhang S, Zhang L, Wang X, Qian Z. Developmental neurotoxicity (DNT) QSAR combination prediction model establishment and structural characteristics interpretation. Toxicol Res (Camb) 2024; 13:tfad116. [PMID: 38178999 PMCID: PMC10762666 DOI: 10.1093/toxres/tfad116] [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: 11/06/2023] [Revised: 09/14/2023] [Accepted: 11/08/2023] [Indexed: 01/06/2024] Open
Abstract
With the incidence of neurodevelopmental disorders on the rise, it is imperative to screen and evaluate developmental neurotoxicity (DNT) compounds from a large number of environmental chemicals and understand their mechanisms. In this study, DNT qualitative structure-activity relationship (QSAR) study was carried out for the first time based on DNT data of mammals and structural characterization of DNT compounds was preliminarily illustrated. Five different classification algorithms and two feature selection methods were used to construct prediction models. The best model had good predictive ability on the external test set, but a small application domain (AD). Through combining of three different models, both MCC and AD values were improved. Furthermore, electronical properties, van der Waals volume-related properties and S, Cl or P containing substructure were found to be associated with DNT through modeling descriptors analysis and structure alerts (SAs) identification. This study lays a foundation for further DNT prediction of environmental exposures in human and contributes to the understanding of DNT mechanism.
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Affiliation(s)
- Lu Zhang
- Department of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
| | - Min Li
- Department of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
| | - Dalong Zhang
- Department of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
| | - Shujing Zhang
- Department of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
| | - Li Zhang
- Department of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
| | - Xiaojun Wang
- Department of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
| | - Zhiyong Qian
- Department of Toxicology, Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
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7
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Rodríguez-Belenguer P, March-Vila E, Pastor M, Mangas-Sanjuan V, Soria-Olivas E. Usage of model combination in computational toxicology. Toxicol Lett 2023; 389:34-44. [PMID: 37890682 DOI: 10.1016/j.toxlet.2023.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/17/2023] [Accepted: 10/24/2023] [Indexed: 10/29/2023]
Abstract
New Approach Methodologies (NAMs) have ushered in a new era in the field of toxicology, aiming to replace animal testing. However, despite these advancements, they are not exempt from the inherent complexities associated with the study's endpoint. In this review, we have identified three major groups of complexities: mechanistic, chemical space, and methodological. The mechanistic complexity arises from interconnected biological processes within a network that are challenging to model in a single step. In the second group, chemical space complexity exhibits significant dissimilarity between compounds in the training and test series. The third group encompasses algorithmic and molecular descriptor limitations and typical class imbalance problems. To address these complexities, this work provides a guide to the usage of a combination of predictive Quantitative Structure-Activity Relationship (QSAR) models, known as metamodels. This combination of low-level models (LLMs) enables a more precise approach to the problem by focusing on different sub-mechanisms or sub-processes. For mechanistic complexity, multiple Molecular Initiating Events (MIEs) or levels of information are combined to form a mechanistic-based metamodel. Regarding the complexity arising from chemical space, two types of approaches were reviewed to construct a fragment-based chemical space metamodel: those with and without structure sharing. Metamodels with structure sharing utilize unsupervised strategies to identify data patterns and build low-level models for each cluster, which are then combined. For situations without structure sharing due to pharmaceutical industry intellectual property, the use of prediction sharing, and federated learning approaches have been reviewed. Lastly, to tackle methodological complexity, various algorithms are combined to overcome their limitations, diverse descriptors are employed to enhance problem definition and balanced dataset combinations are used to address class imbalance issues (methodological-based metamodels). Remarkably, metamodels consistently outperformed classical QSAR models across all cases, highlighting the importance of alternatives to classical QSAR models when faced with such complexities.
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Affiliation(s)
- Pablo Rodríguez-Belenguer
- Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; Department of Pharmacy and Pharmaceutical Technology and Parasitology, Universitat de València, 46100 Valencia, Spain
| | - Eric March-Vila
- Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain
| | - Manuel Pastor
- Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain
| | - Victor Mangas-Sanjuan
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, Universitat de València, 46100 Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, Universitat Politècnica de València, 46100 Valencia, Spain
| | - Emilio Soria-Olivas
- IDAL, Intelligent Data Analysis Laboratory, ETSE, Universitat de València, 46100 Valencia, Spain.
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8
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Grillberger K, Cöllen E, Trivisani CI, Blum J, Leist M, Ecker GF. Structural Insights into Neonicotinoids and N-Unsubstituted Metabolites on Human nAChRs by Molecular Docking, Dynamics Simulations, and Calcium Imaging. Int J Mol Sci 2023; 24:13170. [PMID: 37685977 PMCID: PMC10487998 DOI: 10.3390/ijms241713170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 08/10/2023] [Accepted: 08/12/2023] [Indexed: 09/10/2023] Open
Abstract
Neonicotinoid pesticides were initially designed in order to achieve species selectivity on insect nicotinic acetylcholine receptors (nAChRs). However, concerns arose when agonistic effects were also detected in human cells expressing nAChRs. In the context of next-generation risk assessments (NGRAs), new approach methods (NAMs) should replace animal testing where appropriate. Herein, we present a combination of in silico and in vitro methodologies that are used to investigate the potentially toxic effects of neonicotinoids and nicotinoid metabolites on human neurons. First, an ensemble docking study was conducted on the nAChR isoforms α7 and α3β4 to assess potential crucial molecular initiating event (MIE) interactions. Representative docking poses were further refined using molecular dynamics (MD) simulations and binding energy calculations using implicit solvent models. Finally, calcium imaging on LUHMES neurons confirmed a key event (KE) downstream of the MIE. This method was also used to confirm the predicted agonistic effect of the metabolite descyano-thiacloprid (DCNT).
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Affiliation(s)
- Karin Grillberger
- Department of Pharmaceutical Sciences, University of Vienna, 1090 Vienna, Austria
| | - Eike Cöllen
- In Vitro Toxicology and Biomedicine, University of Konstanz, 78457 Konstanz, Germany
| | | | - Jonathan Blum
- In Vitro Toxicology and Biomedicine, University of Konstanz, 78457 Konstanz, Germany
| | - Marcel Leist
- In Vitro Toxicology and Biomedicine, University of Konstanz, 78457 Konstanz, Germany
| | - Gerhard F. Ecker
- Department of Pharmaceutical Sciences, University of Vienna, 1090 Vienna, Austria
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9
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Karabulut S, Kaur H, Gauld JW. Applications and Potential of In Silico Approaches for Psychedelic Chemistry. Molecules 2023; 28:5966. [PMID: 37630218 PMCID: PMC10459288 DOI: 10.3390/molecules28165966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/01/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
Molecular-level investigations of the Central Nervous System have been revolutionized by the development of computational methods, computing power, and capacity advances. These techniques have enabled researchers to analyze large amounts of data from various sources, including genomics, in vivo, and in vitro drug tests. In this review, we explore how computational methods and informatics have contributed to our understanding of mental health disorders and the development of novel drugs for neurological diseases, with a special focus on the emerging field of psychedelics. In addition, the use of state-of-the-art computational methods to predict the potential of drug compounds and bioinformatic tools to integrate disparate data sources to create predictive models is also discussed. Furthermore, the challenges associated with these methods, such as the need for large datasets and the diversity of in vitro data, are explored. Overall, this review highlights the immense potential of computational methods and informatics in Central Nervous System research and underscores the need for continued development and refinement of these techniques and more inclusion of Quantitative Structure-Activity Relationships (QSARs).
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Affiliation(s)
- Sedat Karabulut
- Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4, Canada;
| | - Harpreet Kaur
- Pharmala Biotech, 82 Richmond Street E, Toronto, ON M5C 1P1, Canada;
| | - James W. Gauld
- Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4, Canada;
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Kan HL, Tung CW, Chang SE, Lin YC. In silico prediction of parkinsonian motor deficits-related neurotoxicants based on the adverse outcome pathway concept. Arch Toxicol 2022; 96:3305-3314. [PMID: 36175685 DOI: 10.1007/s00204-022-03376-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 09/07/2022] [Indexed: 11/02/2022]
Abstract
Exposure to neurotoxicants has been associated with Parkinson's disease (PD). Limited by the clinical variation in the signs and symptoms as well as the slow disease progression, the identification of parkinsonian neurotoxicants relies on animal models. Here, we propose an innovative in silico model for the prediction of parkinsonian neurotoxicants. The model was designed based on a validated adverse outcome pathway (AOP) for parkinsonian motor deficits initiated from the inhibition of mitochondrial complex I. The model consists of a molecular docking model for mitochondrial complex I protein to predict the molecular initiating event and a neuronal cytotoxicity Quantitative Structure-Activity Relationships (QSAR) model to predict the cellular outcome of the AOP. Four known PD-related complex I inhibitors and four non-neurotoxic chemicals were utilized to develop the threshold of the models and to validate the model, respectively. The integrated model showed 100% specificity in ruling out the non-neurotoxic chemicals. The screening of 41 neurotoxicants and complex I inhibitors with the model resulted in 16 chemicals predicted to induce parkinsonian disorder through the molecular initiating event of mitochondrial complex I inhibition. Five of them, namely cyhalothrin, deguelin, deltamethrin, diazepam, and permethrin, are cases with direct evidence linking them to parkinsonian motor deficit-related signs and symptoms. The neurotoxicant prediction model for parkinsonian motor deficits based on the AOP concept may be useful in prioritizing chemicals for further evaluations on PD potential.
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Affiliation(s)
- Hung-Lin Kan
- Doctoral Degree Program in Toxicology, College of Pharmacy, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
| | - Chun-Wei Tung
- Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Miaoli County, 35053, Taiwan.
| | - Shao-En Chang
- Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Miaoli County, 35053, Taiwan
| | - Ying-Chi Lin
- Doctoral Degree Program in Toxicology, College of Pharmacy, Kaohsiung Medical University, Kaohsiung, 807, Taiwan. .,School of Pharmacy, College of Pharmacy, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
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