Dataset Information

Datasets Construction and Development of QSAR Models for Predicting Micronucleus In Vitro and In Vivo Assay Outcomes.

ABSTRACT: In silico (quantitative) structure-activity relationship modeling is an approach that provides a fast and cost-effective alternative to assess the genotoxic potential of chemicals. However, one of the limiting factors for model development is the availability of consolidated experimental datasets. In the present study, we collected experimental data on micronuclei in vitro and in vivo, utilizing databases and conducting a PubMed search, aided by text mining using the BioBERT large language model. Chemotype enrichment analysis on the updated datasets was performed to identify enriched substructures. Additionally, chemotypes common for both endpoints were found. Five machine learning models in combination with molecular descriptors, twelve fingerprints and two data balancing techniques were applied to construct individual models. The best-performing individual models were selected for the ensemble construction. The curated final dataset consists of 981 chemicals for micronuclei in vitro and 1309 for mouse micronuclei in vivo, respectively. Out of 18 chemotypes enriched in micronuclei in vitro, only 7 were found to be relevant for in vivo prediction. The ensemble model exhibited high accuracy and sensitivity when applied to an external test set of in vitro data. A good balanced predictive performance was also achieved for the micronucleus in vivo endpoint.

SUBMITTER: Khondkaryan L

PROVIDER: S-EPMC10537630 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Datasets Construction and Development of QSAR Models for Predicting Micronucleus In Vitro and In Vivo Assay Outcomes.

Khondkaryan Lusine L Tevosyan Ani A Navasardyan Hayk H Khachatrian Hrant H Tadevosyan Gohar G Apresyan Lilit L Chilingaryan Gayane G Navoyan Zaven Z Stopper Helga H Babayan Nelly N

Toxics 20230915 9

In silico (quantitative) structure-activity relationship modeling is an approach that provides a fast and cost-effective alternative to assess the genotoxic potential of chemicals. However, one of the limiting factors for model development is the availability of consolidated experimental datasets. In the present study, we collected experimental data on micronuclei in vitro and in vivo, utilizing databases and conducting a PubMed search, aided by text mining using the BioBERT large language model ...[more]

PMID: 37755795

Similar Datasets

Project description:Nicotine's genotoxic potential has been extensively studied in vitro. While the results of mammalian cell-based studies have inferred that it can potentially damage chromosomes, in general and with few exceptions, adverse DNA effects have been observed primarily at supraphysiological concentrations in nonregulatory assays that provide little information on its mode-of-action (MoA). In this study, a modern-day regulatory genotoxicity assessment was conducted using a flow cytometry-based in vitro micronucleus (MN) assay, Good Laboratory Practice study conditions, Chinese hamster ovary cells of known provenance, and acceptance/evaluation criteria from the current OECD Test Guideline 487. Nicotine concentrations up to 3.95 mM had no effect on background levels of DNA damage; however, concentrations above the point-of-departure range of 3.94-4.54 mM induced increases in MN and hypodiploid nuclei, indicating a possible aneugenicity hazard. Follow-up experiments designed to elucidate nicotine's MoA revealed cellular vacuolization, accompanying distortions in microtubules, inhibition of tubulin polymerization, centromere-positive DNA, and multinucleate cells at MN-inducing concentrations. Vacuoles likely originated from acidic cellular compartments (e.g., lysosomes). Remarkably, genotoxicity was suppressed by chemicals that raised the luminal pH of these organelles. Other endpoints (e.g., changes in phosphorylated histones) measured in the study cast doubt on the biological relevance of this apparent genotoxicity. In addition, three major nicotine metabolites, including cotinine, had no MN effects but nornicotine induced a nicotine-like profile. It is possible that nicotine's lysosomotropic properties drive the genotoxicity observed in vitro; however, the potency and mechanistic insights revealed here indicate that it is likely of minimal physiological relevance for nicotine consumers. Environ. Mol. Mutagen. 2019. © 2019 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals, Inc. on behalf of Environmental Mutagen Society.

Dataset Information

Datasets Construction and Development of QSAR Models for Predicting Micronucleus In Vitro and In Vivo Assay Outcomes.

Publications

Datasets Construction and Development of QSAR Models for Predicting Micronucleus In Vitro and In Vivo Assay Outcomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets