Article
Toxicology
Terje Svingen, Daniel L. Villeneuve, Dries Knapen, Eleftheria Maria Panagiotou, Monica Kam Draskau, Pauliina Damdimopoulou, Jason M. O'Brien
Summary: The AOP framework organizes scientific knowledge to infer cause-effect relationships between stressor events and toxicity outcomes, supporting chemical safety assessment and regulatory toxicology. However, developing robust AOPs requires substantial work and time, leading to a proposed more pragmatic approach for AOP development.
TOXICOLOGICAL SCIENCES
(2021)
Review
Toxicology
Anna Itkonen, Jukka Hakkola, Jaana Rysa
Summary: Pharmaceuticals and environmental contaminants contribute to hypercholesterolemia by activating pregnane X receptor (PXR). PXR activation disrupts lipid metabolism and promotes hypercholesterolemia through multiple mechanisms. This novel toxicity pathway is of great concern and requires further attention.
ARCHIVES OF TOXICOLOGY
(2023)
Article
Toxicology
Kristina Pogrmic-Majkic, Dragana Samardzija Nenadov, Biljana Tesic, Svetlana Fa Nedeljkovic, Dunja Kokai, Bojana Stanic, Nebojsa Andric
Summary: This study utilized AOPs and AOP networks to understand the impact of chemicals on human health. It derived the HFRT-AOP network and mapped DEHP to this network, providing insights into the toxic mechanism of DEHP-induced human female reproductive toxicity.
ARCHIVES OF TOXICOLOGY
(2022)
Article
Environmental Sciences
Janani Ravichandran, Bagavathy Shanmugam Karthikeyan, Areejit Samal
Summary: An adverse outcome pathway (AOP) is a representation of mechanistic information on adverse effects caused by environmental exposure. This study focuses on the construction and analysis of an endocrine-relevant AOP (ED-AOP) network. The connectivity analysis and graph-theoretic analyses of the network revealed important events and system-level perturbations caused by endocrine disruption, providing insights for risk assessment and the development of new endpoints or assays.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Review
Pharmacology & Pharmacy
Mathieu Vinken
Summary: Up to half of hospitalized COVID-19 patients may experience liver damage, which can be caused either by direct actions of the virus or pharmacological treatment. Research suggests that liver injury may result from direct viral binding and local actions in cholangiocytes, or indirectly from systemic hypoxia and inflammation in patients. URGENT further research is needed to fill knowledge gaps for future targeted development of vaccines and therapies.
Article
Toxicology
Wanyu He, Jiaqi Ding, Ning Gao, Lingyan Zhu, Lin Zhu, Jianfeng Feng
Summary: This study expands the understanding of the toxicity of organophosphate esters (OPEs) and systematically identifies the mechanism of OPEs toxicity under the framework of adverse outcome pathway (AOP). The results show that the toxicity mechanism of OPEs on aquatic organisms and mammals differ, primarily due to their different biological metabolic systems.
ARCHIVES OF TOXICOLOGY
(2023)
Review
Biochemistry & Molecular Biology
Patrudu Makena, Tatiana Kikalova, Gaddamanugu L. L. Prasad, Sarah A. A. Baxter
Summary: Lung fibrosis is a progressive fatal disease caused by deregulated wound healing of lung epithelial cells. Chronic cigarette smoking and oxidative stress are major risk factors for lung fibrosis. This study aims to develop an adverse outcome pathway (AOP) to investigate the mechanisms of lung fibrosis due to lung injury caused by inhaled toxicants, including cigarette smoke. Cellular and tissue-level events lead to the development of lung fibrosis through proinflammatory and profibrotic mediators.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Engineering, Environmental
Yuan Jin, Guangshuai Qi, Yingqing Shou, Daochuan Li, Yuzhen Liu, Heyuan Guan, Qianqian Zhang, Shen Chen, Jiao Luo, Lin Xu, Chuanhai Li, Wanli Ma, Ningning Chen, Yuxin Zheng, Dianke Yu
Summary: This study developed a highly reliable AOP model concerning human health, validated and quantitatively evaluated it, and conducted targeted bioassays to further understand cellular responses. Through these research efforts, a comprehensive AOP network was established, providing valuable insights for risk assessment.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Computer Science, Interdisciplinary Applications
Jonas van Ertvelde, Anouk Verhoeven, Amy Maerten, Axelle Cooreman, Bruna dos Santos Rodrigues, Julen Sanz-Serrano, Milos Mihajlovic, Ignacio Tripodi, Marc Teunis, Ramiro Jover, Thomas Luechtefeld, Tamara Vanhaecke, Jian Jiang, Mathieu Vinken
Summary: This study introduces a novel approach using artificial intelligence to optimize the adverse outcome pathway (AOP) network of chemical-induced cholestasis. The optimized network was generated through automated data collection and quantitative confidence assessment of molecular initiating events, key events, and key event relationships. The results identified 38 unique key events and 135 key event relationships, with transporter changes being the most frequent key event and having the most confident relationship with the adverse outcome, cholestasis. Other important key events include nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation, and apoptosis.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Environmental Sciences
Jason. C. C. Lambert
Summary: New Approach Methodologies (NAMs), such as structure-activity/read-across, -omics technologies, and Adverse Outcome Pathway (AOP), have been considered alternative sources of chemical and biological information in human health risk assessment. However, the integration of NAMs into chemical mixtures risk assessment is limited due to the lack of validation and acceptance by risk assessors. AOP footprinting is proposed as a key methodology to integrate NAM data into mixtures risk assessment.
Article
Engineering, Environmental
You Song, Keke Zheng, Dag Anders Brede, Tania Gomes, Li Xie, Yetneberk Kassaye, Brit Salbu, Knut Erik Tollefsen
Summary: This study used multiomics dose-response modeling to identify the hazards of low-dose ionizing radiation to Daphnia magna. It demonstrated the use of omics data to support the development of an adverse outcome pathway (AOP) network for ionizing radiation. The results showed that molecular pathways related to oxidative stress, DNA damage, mitochondrial dysfunction, protein degradation, and apoptosis were highly relevant to the effects of gamma radiation.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Environmental Sciences
Veronica Lizano-Fallas, Ana Carrasco del Amor, Susana Cristobal
Summary: The exposure to multiple chemicals has raised concerns for human and environmental health. The adverse outcome pathway method provides a framework for mechanism-based assessment in environmental health, but the identification of molecular initiating events and protein targets remains a challenge. However, recent mass spectrometry-based methods offer proteome-wide identification of protein targets, but revealing a molecular initiating event is still dependent on available knowledge.
Review
Biochemistry & Molecular Biology
Yann Gueguen, Marie Frerejacques
Summary: An adverse outcome pathway (AOP) is a conceptual framework that describes the causally and sequentially linked events occurring during exposure to stressors, with relevance to risk assessment. This paper proposes a review of knowledge on uranium-induced kidney impairment and suggests a tentative AOP for this condition. The identified key events include mitochondrial dysfunction, DNA damage, and cellular stress responses, leading to tubular damage and kidney failure.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Pharmacology & Pharmacy
Elena Menegola, Christina H. J. Veltman, Maria Battistoni, Francesca Di Renzo, Angelo Moretto, Francesca Metruccio, Anna Beronius, Johanna Zilliacus, Katerina Kyriakopoulou, Anastasia Spyropoulou, Kyriaki Machera, Leo T. M. van der Ven, Mirjam Luijten
Summary: The study described a linear AOP for skeletal craniofacial defects with CYP26 inhibition as the MIE and conazoles as representative stressors. It showed high biological plausibility and moderate overall empirical evidence, with high essentiality assessment for the KEs.
Review
Cell Biology
Helena T. Hogberg, Ann Lam, Elan Ohayon, Muhammad Ali Shahbaz, Laure-Alix Clerbaux, Anna Bal-Price, Sandra Coecke, Rachel Concha, Francesca De Bernardi, Eizleayne Edrosa, Alan J. Hargreaves, Katja M. Kanninen, Amalia Munoz, Francesca Pistollato, Surat Saravanan, Natalia Garcia-Reyero, Clemens Wittwehr, Magdalini Sachana
Summary: This review organizes available knowledge on the neurobiological mechanisms of COVID-19, identifies four AOPs leading to neurological adverse outcomes, and discusses factors influencing the impact of COVID-19 on neurological AOPs. The use of the AOP framework helps visualize core pathways and shared mechanisms.
Review
Chemistry, Medicinal
Marcus W. H. Wang, Jonathan M. Goodman, Timothy E. H. Allen
Summary: Machine learning has become prominent in predictive toxicology, with support vector machines, random forest, and decision trees being the dominant methods. Challenges include the characteristics of the data and exploring areas for improvement.
CHEMICAL RESEARCH IN TOXICOLOGY
(2021)
Correction
Environmental Sciences
Kamel Mansouri, Agnes Karmaus, Jeremy Fitzpatrick, Grace Patlewicz, Prachi Pradeep, Domenico Alberga, Nathalie Alepee, Timothy E. H. Allen, Dave Allen, Vinicius M. Alves, Carolina H. Andrade, Tyler R. Auernhammer, Davide Ballabio, Shannon Bell, Emilio Benfenati, Sudin Bhattacharya, Joyce V. Bastos, Stephen Boyd, J. B. Brown, Stephen J. Capuzzi, Yaroslav Chushak, Heather Ciallella, Alex M. Clark, Viviana Consonni, Pankaj R. Daga, Sean Ekins, Sherif Farag, Maxim Fedorov, Denis Fourches, Domenico Gadaleta, Feng Gao, Jeffery M. Gearhart, Garett Goh, Jonathan M. Goodman, Francesca Grisoni, Christopher M. Grulke, Thomas Hartung, Matthew Hirn, Pavel Karpov, Alexandru Korotcov, Giovanna J. Lavado, Michael Lawless, Xinhao Li, Thomas Luechtefeld, Filippo Lunghini, Giuseppe F. Mangiatordi, Gilles Marcou, Dan Marsh, Todd Martin, Andrea Mauri, Eugene N. Muratov, Glenn J. Myatt, Dac-Trung Nguyen, Orazio Nicolotti, Reine Note, Paritosh Pande, Amanda K. Parks, Tyler Peryea, Ahsan Polash, Robert Rallo, Alessandra Roncaglioni, Craig Rowlands, Patricia Ruiz, Daniel Russo, Ahmed Sayed, Risa Sayre, Timothy Sheils, Charles Siegel, Arthur C. Silva, Anton Simeonov, Sergey Sosnin, Noel Southall, Judy Strickland, Yun Tang, Brian Teppen, Igor V. Tetko, Dennis Thomas, Valery Tkachenko, Roberto Todeschini, Cosimo Toma, Ignacio Tripodi, Daniela Trisciuzzi, Alexander Tropsha, Alexandre Varnek, Kristijan Vukovic, Zhongyu Wang, Liguo Wang, Katrina M. Waters, Andrew J. Wedlake, Sanjeeva J. Wijeyesakere, Dan Wilson, Zijun Xiao, Hongbin Yang, Gergely Zahoranszky-Kohalmi, Alexey V. Zakharov, Fagen F. Zhang, Zhen Zhang, Tongan Zhao, Hao Zhu, Kimberley M. Zorn, Warren Casey, Nicole C. Kleinstreuer
ENVIRONMENTAL HEALTH PERSPECTIVES
(2021)
Article
Chemistry, Multidisciplinary
Jonathan M. Goodman, Igor Pletnev, Paul Thiessen, Evan Bolton, Stephen R. Heller
Summary: The software for the IUPAC Chemical Identifier, InChI, is highly reliable and has been upgraded to version 1.06 with significant new features including support for pseudo-element atoms and improved description of polymers. Research results show that the accuracy of version 1.05 was 99.996% and version 1.06 represents a step closer to perfection, with few applications needing changes as a result of the upgrade.
JOURNAL OF CHEMINFORMATICS
(2021)
Review
Chemistry, Multidisciplinary
Daniel S. Wigh, Jonathan M. Goodman, Alexei A. Lapkin
Summary: Interdisciplinary work in chemistry is becoming increasingly important due to advancements in computing, machine learning, and artificial intelligence. Understanding the representation of molecules in a machine-readable format is crucial for computational chemistry. This article introduces different representations of molecules and highlights three significant ones. Researchers often share their work on platforms like GitHub, but discussions on computation time and domain of applicability are often overlooked. The authors propose questions for further consideration to make chemical VAEs more accessible.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Jonathan M. Goodman, Gerd Blanke, Hans Kraut
Summary: RInChI is a canonical identifier widely used for reactions in databases. It can handle large collections of reactions and link information from diverse sources. Studies demonstrate its usefulness in analyzing billion-scale molecular data in the SAVI database, with the simplified form of Web-RInChIKey providing enough information for effective differentiation. RInChI exhibits different properties from Reaction SMILES, and both approaches offer valuable and distinct information.
PURE AND APPLIED CHEMISTRY
(2022)
Article
Chemistry, Multidisciplinary
Christopher J. Swain, Jeremy G. Frey, Jonathan M. Goodman
Summary: In November 2020, the Royal Society of Chemistry's Chemical Information and Computer Applications interest group held a five-day conference on Open Chemical Science, focusing on open data, open access publishing, and various open-source tools for chemistry. This online event was highly popular and attracted attendees from 45 different countries. The workshops, in particular, were well-received and led to a year-long series of further workshops.
PURE AND APPLIED CHEMISTRY
(2022)
Article
Chemistry, Multidisciplinary
Mathew M. Simpson, Ching Ching Lam, Jonathan M. Goodman, Shankar Balasubramanian
Summary: The epigenetic modification 5-methylcytosine is crucial for development, cell specific gene expression, and disease states. However, the selective chemical modification of 5-methylcytosine is currently challenging. In this study, we present a xanthone-photosensitized process that introduces a 4-pyridine modification at the methyl group of 5-methylcytosine. This reaction mechanism involves single electron oxidation and deprotonation to generate the methyl group radical, followed by cross coupling to install the 4-pyridine label.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Chemistry, Physical
Daniel S. Wigh, Matthieu Tissot, Patrick Pasau, Jonathan M. Goodman, Alexei A. Lapkin
Summary: Computational reaction prediction is a widely used task in chemistry, and in this work, an algorithm for predicting the rate of protodeboronation of boronic acids is presented. The algorithm is based on a mechanistic model derived from kinetic studies and is validated using cross-validation techniques. The algorithm shows promise in assisting chemists in reactions involving boronic acids.
JOURNAL OF PHYSICAL CHEMISTRY A
(2023)
Article
Chemistry, Multidisciplinary
Jonathan Lam, Richard J. Lewis, Jonathan M. Goodman
Summary: Vibrational circular dichroism (VCD) spectroscopy provides data for determining absolute configuration, but interpretation is challenging. We have validated a method, the Cai dot factor, using a database of VCD data for 30 pairs of organic compounds. Analysis shows that this method is reliable and efficient for absolute configuration determination, even with imperfect spectra. Most molecules tested have high confidence scores and correct assignments.
JOURNAL OF CHEMINFORMATICS
(2023)
Correction
Chemistry, Organic
Ching Ching Lam, Jonathan M. Goodman
Summary: In this paper, the authors provide computational insights on the origin of enantioselectivity in reactions with diarylprolinol silyl ether catalysts via a radical pathway. This study is of significant importance for understanding the mechanism of organic catalytic reactions and developing efficient chiral catalysts.
ORGANIC CHEMISTRY FRONTIERS
(2022)
Article
Chemistry, Organic
Ching Ching Lam, Jonathan M. Goodman
Summary: The study reveals that the effect of catalyst variation on the selectivity reaction can be explained by conformational changes and structural deformations.
ORGANIC CHEMISTRY FRONTIERS
(2022)
Article
Chemistry, Multidisciplinary
Sanha Lee, Kristaps Ermanis, Jonathan M. Goodman
Summary: The use of machine learning in computational chemistry has seen significant progress, with the ability to predict molecular properties accurately and cost-effectively using large molecular databases.
Article
Chemistry, Multidisciplinary
Alexander Howarth, Jonathan M. Goodman
Summary: DP5 probability is a new method for quantifying molecular uncertainty. It can rapidly differentiate between structure proposals using C-13 NMR spectra and prevent incorrect structures from being published and reassigned.
Meeting Abstract
Toxicology
T. E. H. Allen, A. J. Wedlake, M. N. Grayson, A. M. Middleton, M. Folia, M. Baltazar, P. Piechota, E. Gelzinyte, J. M. Goodman, P. J. Russell, P. Kukic, S. Gutsell
TOXICOLOGY LETTERS
(2021)
Review
Chemistry, Organic
Guillermo Caballero-Garcia, Jonathan M. Goodman
Summary: N-Triflylphosphoramides (NTPA) have emerged as popular catalysts for enantioselective transformations due to their stronger Bronsted acid properties compared to phosphoric acids (PA). This review categorizes NTPA-catalyzed reactions based on the enantio-determining step and highlights their use in total synthesis.
ORGANIC & BIOMOLECULAR CHEMISTRY
(2021)