ArticleEnvironmental science & technology2024
Chemical Space Covered by Applicability Domains of Quantitative Structure-Property Relationships and Semiempirical Relationships in Chemical Assessments.
Article in Environmental science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
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- Predicting peroxisome proliferator-activated receptor gamma potency of small molecules: a synergistic consensus model and deep learning binding affinity approach powered by Enalos Cloud Platform.Molecular diversity · 2026Article
- Collision-free morgan fingerprints: a principled approach to enhance machine learning performance and interpretability in chemistry.Journal of cheminformatics · 2026Article
- Atom-level descriptors and explainable prediction of iron carbide nanoparticles' cytotoxicityNanoscale advances · 2026Article
- Review
- From Ambition to Action: Navigating Obstacles and Opportunities of "Safe and Sustainable by Design".Environmental science & technology · 2025Review
- Article
- Thyroid Hormone Biomonitoring: A Review on Their Metabolism and Machine-Learning Based Analysis on Effects of Endocrine Disrupting Chemicals.Environment & health (Washington, D.C.) · 2024Review
- Identifying uncertainty in physical-chemical property estimation with IFSQSAR.Journal of cheminformatics · 2024Article
- Modeling sorption of environmental organic chemicals from water to soils.Water research X · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A significant number of chemicals registered in national and regional chemical inventories require assessments of their potential "hazard" concerns posed to humans and ecological receptors. This warrants knowledge of their partitioning and reactivity properties, which are often predicted by quantitative structure-property relationships (QSPRs) and other semiempirical relationships. It is imperative to evaluate the applicability domain (AD) of these tools to ensure their suitability for assessment purpose. Here, we investigate the extent to which the ADs of commonly used QSPRs and semiempirical relationships cover seven partitioning and reactivity properties of a chemical "space" comprising 81,000+ organic chemicals registered in regulatory and academic chemical inventories. Our findings show that around or more than half of the chemicals studied are covered by at least one of the commonly used QSPRs. The investigated QSPRs demonstrate adequate AD coverage for organochlorides and organobromines but limited AD coverage for chemicals containing fluorine and phosphorus. These QSPRs exhibit limited AD coverage for atmospheric reactivity, biodegradation, and octanol-air partitioning, particularly for ionizable organic chemicals compared to nonionizable ones, challenging assessments of environmental persistence, bioaccumulation capability, and long-range transport potential. We also find that a predictive tool's AD coverage of chemicals depends on how the AD is defined, for example, by the distance of a predicted chemical from the centroid of the training chemicals or by the presence or absence of structural features.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.