Chemical Research in Toxicology最新文献

{"title":"Assessing the Toxicity of Terpene- and Amino Acid-Based Natural Deep Eutectic Solvents.","authors":"Madushmita Hatimuria, Sweety Basumatary, Amit Kumar Trivedi, Vinod Kumar, Satish Kumar Pandey, Ashok Pabbathi","doi":"10.1021/acs.chemrestox.5c00026","DOIUrl":"10.1021/acs.chemrestox.5c00026","url":null,"abstract":"<p><p>Over the past decade, there has been a significant increase in the discovery of greener solvents for industrial applications. In this context, deep eutectic solvents (DESs) have emerged as promising candidates across various sectors, including biomass conversion, paper and pulp, pharmaceuticals, and textiles. A new class of DESs, known as natural deep eutectic solvents (NADESs), is derived from natural chemicals and is expected to be more environmentally friendly. However, research into the environmental impact and toxicity of NADESs is still limited. Given the broad applications of DESs and the urgent need for sustainable alternatives, studying their toxicity is crucial. In our current study, we focused on NADESs formulated from menthol, thymol, and amino acid. We assessed their toxicity on different cell lines using standard biochemical assays. Remarkably, our findings also indicate that these NADESs exhibit low toxicity in the HaCaT cell line and a mice blood sample. We also found that all of the tested NADESs have shown better antimicrobial property values compared to the individual components of NADESs, indicating the importance of NADES formulation for applications. Among the tested NADESs, menthol:thymol (1:1) showed the best antibacterial properties. These results hold significant implications for the development of NADESs in industrial applications, suggesting a path forward for the adoption of greener and safer solvents.</p>","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":" ","pages":"923-929"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143955907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data Exploration for Target Predictions Using Proprietary and Publicly Available Data Sets.","authors":"Aljoša Smajić, Thomas Steger-Hartmann, Gerhard F Ecker, Anke Hackl","doi":"10.1021/acs.chemrestox.4c00347","DOIUrl":"10.1021/acs.chemrestox.4c00347","url":null,"abstract":"<p><p>When applying machine learning (ML) approaches for the prediction of bioactivity, it is common to collect data from different assays or sources and combine them into single data sets. However, depending on the data domains and sources from which these data are retrieved, bioactivity data for the same macromolecular target may show a high variance of values (looking at a single compound) and cover very different parts of the chemical space as well as the bioactivity range (looking at the whole data set). The effectiveness and applicability domain of the resulting prediction models may be strongly influenced by the sources from which their training data were retrieved. Therefore, we investigated the chemical space and active/inactive distribution of proprietary pharmaceutical data from Bayer AG and the publicly available ChEMBL database, and their impact when applied as training data for classification models. For this end, we applied two different sets of descriptors in combination with different ML algorithms. The results show substantial differences in chemical space between the two different data sources, leading to suboptimal prediction performance when models are applied to domains other than their training data. MCC values between -0.34 and 0.37 among all targets were retrieved, indicating suboptimal model performance when models trained on Bayer AG data were tested on ChEMBL data and vice versa. The mean Tanimoto similarity of the nearest neighbors between these two data sources indicated similarities for 31 targets equal to or less than 0.3. Interestingly, all applied methods to assess overlap of chemical space of the two data sources to predict the applicability of models beyond their training data sets did not correlate with observed performances. Finally, we applied different strategies for creating mixed training data sets based on both public and proprietary sources, using assay format (cell-based and cell-free) information and Tanimoto similarities.</p>","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":" ","pages":"820-833"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12093362/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143954633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imidazole-Based ALK5 Inhibitor Attenuates TGF-β/Smad-Mediated Hepatic Stellate Cell Activation and Hepatic Fibrogenesis.","authors":"Si-Qi Wang, Yu-Qing Meng, Yan-Ling Wu, Ji-Xing Nan, Cheng-Hua Jin, Li-Hua Lian","doi":"10.1021/acs.chemrestox.5c00036","DOIUrl":"10.1021/acs.chemrestox.5c00036","url":null,"abstract":"<p><p>Liver fibrosis resulting from severe liver damage is a major clinical problem for which effective pharmacological drugs and treatment strategies are lacking. TGF-β, a hallmark of liver fibrosis, has been shown to promote ALK5 phosphorylation in an activated state. Hence, the suppression of ALK5 signal transduction has emerged as a promising therapeutic strategy for the treatment of liver fibrosis. In this study, the imidazole derivative J-1149, which exhibited inhibitory activity against ALK5, was synthesized to exert antifibrotic effects, and the inhibition mechanisms were uncovered. Our findings suggested that J-1149 significantly attenuated HSC activation and liver fibrogenesis by acting on the TGF-β/Smad signaling pathway. Concurrently, the potential of J-1149 to impede the P2X7R/NLRP3 axis, curtail the infiltration of macrophages and neutrophils, and reduce liver fibrogenesis was also highlighted. These results demonstrated that J-1149 is a promising candidate for the treatment of liver fibrosis.</p>","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":" ","pages":"930-941"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143952368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tale of Three <i>N</i>-Nitrosamines and the Variables Needed to Assess Their Carcinogenicity In Silico Incorporated into a Single Workflow.","authors":"Jakub Kostal, Adelina Voutchkova-Kostal","doi":"10.1021/acs.chemrestox.4c00482","DOIUrl":"10.1021/acs.chemrestox.4c00482","url":null,"abstract":"<p><p><i>N</i>-Nitrosamine impurities in pharmaceuticals present a considerable challenge for regulators and industry alike, where the absence of carcinogenic-potency studies has left a gap that must be adequately filled to protect public health. In the interim, this means balancing risk assessment with the necessity to continue research, development, and supply of pharmaceuticals. In the long term, we need a cost-effective solution that optimizes both. As if beholden to Newton's Third Law, every crisis breeds an opportunity of equal magnitude. Consequently, cross-industry consortia have been racing to find a solution by advancing our current science. Recent spotlight has been on in silico tools, as a fast and increasingly reliable alternative to in vivo and in vitro testing. Because <i>N</i>-nitrosamine bioactivation lends itself uniquely to quantum mechanics (QM) approaches, the integration of electronic-structure considerations has emerged as the dominant in silico approach. This signifies a considerable leap in predictive toxicology, which has, for much of its existence, relied on atomistic (quantitative) structure-activity relationships, i.e., (Q)SARs. Here we present a validation of an integrated docking-QM approach within the CADRE program and demonstrate its utility on three different impurities, <i>N</i>-nitroso-7-monomethylamino-6-deoxytetracycline, <i>N</i>-nitroso-dabigatran etexilate, and 1-methyl-4-nitrosopiperazine. We show that a combined in silico strategy, which considers bioavailability, transport, cytochrome P450 binding, and reactivity, can be leveraged to supplement the overly conservative Carcinogenic Potency Categorization Approach (CPCA) in setting the daily acceptable intake (AI) using defensible, highly mechanistic, and quantitative drivers of <i>N</i>-nitrosamine metabolism. To that end, we argue that while <i>N</i>-nitroso-7-monomethylamino-6-deoxytetracycline and 1-methyl-4-nitrosopiperazine are cohort-of-concern impurities, <i>N</i>-nitroso-dabigatran etexilate is not a potent carcinogen (TD₅₀ > 1.5 mg/kg/day), contrasting the CPCA-derived AI. Lastly, we discuss how the CADRE tool can be integrated with the broader landscape of QM methods and the CPCA into a single harmonized in silico strategy for carcinogenicity assessment of <i>N</i>-nitrosamine impurities.</p>","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":" ","pages":"834-848"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143951560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Obituary for Robert P. Hanzlik (1943–2025)","authors":"John R. Cashman*,&nbsp; and ,&nbsp;Matthew A. Cerny,&nbsp;","doi":"10.1021/acs.chemrestox.5c0016810.1021/acs.chemrestox.5c00168","DOIUrl":"https://doi.org/10.1021/acs.chemrestox.5c00168https://doi.org/10.1021/acs.chemrestox.5c00168","url":null,"abstract":"","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":"38 5","pages":"745–746 745–746"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144083564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Sara Casati,&nbsp;Roberta F. Bergamaschi,&nbsp;Riccardo Primavera,&nbsp;Alessandro Ravelli,&nbsp;Ivana Lavota,&nbsp;Alessio Battistini,&nbsp;Gabriella Roda,&nbsp;Chiara Ciccarelli,&nbsp;Claudio Guidotti and Paola Rota*,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":"38 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.5c00068","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144450247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Qiaoyun Huang,&nbsp;Jianfeng Zhang,&nbsp;Songbin Dong and Bin Hu*,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":"38 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.5c00004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144450251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Yiqun Mo,&nbsp;Jisheng Nie,&nbsp;Yue Zhang,&nbsp;Yuanbao Zhang,&nbsp;Jiali Yuan and Qunwei Zhang*,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":"38 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.4c00551","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144450259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"John R. Cashman*,&nbsp; and ,&nbsp;Matthew A. Cerny,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":"38 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.5c00168","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144450244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Shiyuan Guo,&nbsp;Pengcheng Wang,&nbsp;Songbo Wei and Yinsheng Wang*,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":31,"journal":{"name":"Chemical Research in Toxicology","volume":"38 5","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.5c00107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144450245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}