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Background <p>The importance of computational toxicology as a modern tool in chemical safety assessment has become significant, helping with rapid, low-cost predictions of toxicological outcomes and reducing animal testing.</p> Objective <p>For this purpose, the current study was carried out to identify the phytochemicals through GCMS and integrated the identified compounds with computational tools for toxicity analysis.</p> Methodology <p><i>A. cotula</i> L. flower extracts (ethanolic and methanolic) were evaluated for their phytochemical and toxicological profiles via the integration of state-of-the-art in silico platforms (ProTox 3.0 and StopTOX) with GCMS analysis.</p> Results <p>The GCMS analysis showed that the ethanolic fraction provided 11 phyto-ligands which include 1, 3 Difluoro-2-propanol (AFE-1), 1 deoxy-d-mannitol (AFE 2), and Phloropyrone (AFE 11) and the methanolic fraction provided 7 compounds of which name includes Hexadecanoic acid, ethyl ester (AFM-1) and trichloromethane (AFM-2) with their details in terms of 2D/3D structures and SMILES notations. Predictions made using the ethanolic fraction through ProTox 3.0 yielded probabilities of hepatotoxicity ranging from 58% to 99% and flagged moderate nephrotoxicity for AFE-2 (55%) and AFE 10 (57%). Moreover, StopTOX evaluations indicated that AFE-1 (63%) had positive acute inhalation toxicity, positive for AFE-7 (50%) and AFE-9 (60%) acute inhalation, positive only marginally for AFE-1 (86%) and negative for AFE-6 (0%) and AFE-7 (0%) acute oral, and positive only for AFE-1 (71%) and negative for AFE-6 (0%) and AFE-9 (0%) acute dermal toxicity. On the other hand, the methanolic fraction presented low toxicity since AFM-2 is predicted to be moderately toxic by the oral route (97% confidence) and by the dermal route (64%) with a high (94%) probability of eye irritation.</p> Conclusion <p>Overall, combining computational toxicology with experimental data can prove useful as a method of early hazard screening, and these results point out that although the other compounds are effective at suppressing thermal pain signals, it would be worth validating these for safety before applying them as therapeutics.</p> Graphical Abstract <p></p>

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GCMS Integrated Machine Learning-Driven Computational Toxicology of A. Cotula L. Flowers

  • 期刊论文

  • 发表日期：

    2026年2月3日

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  • Afnan M. Alnajeebi

摘要

Background

The importance of computational toxicology as a modern tool in chemical safety assessment has become significant, helping with rapid, low-cost predictions of toxicological outcomes and reducing animal testing.

Objective

For this purpose, the current study was carried out to identify the phytochemicals through GCMS and integrated the identified compounds with computational tools for toxicity analysis.

Methodology

A. cotula L. flower extracts (ethanolic and methanolic) were evaluated for their phytochemical and toxicological profiles via the integration of state-of-the-art in silico platforms (ProTox 3.0 and StopTOX) with GCMS analysis.

Results

The GCMS analysis showed that the ethanolic fraction provided 11 phyto-ligands which include 1, 3 Difluoro-2-propanol (AFE-1), 1 deoxy-d-mannitol (AFE 2), and Phloropyrone (AFE 11) and the methanolic fraction provided 7 compounds of which name includes Hexadecanoic acid, ethyl ester (AFM-1) and trichloromethane (AFM-2) with their details in terms of 2D/3D structures and SMILES notations. Predictions made using the ethanolic fraction through ProTox 3.0 yielded probabilities of hepatotoxicity ranging from 58% to 99% and flagged moderate nephrotoxicity for AFE-2 (55%) and AFE 10 (57%). Moreover, StopTOX evaluations indicated that AFE-1 (63%) had positive acute inhalation toxicity, positive for AFE-7 (50%) and AFE-9 (60%) acute inhalation, positive only marginally for AFE-1 (86%) and negative for AFE-6 (0%) and AFE-7 (0%) acute oral, and positive only for AFE-1 (71%) and negative for AFE-6 (0%) and AFE-9 (0%) acute dermal toxicity. On the other hand, the methanolic fraction presented low toxicity since AFM-2 is predicted to be moderately toxic by the oral route (97% confidence) and by the dermal route (64%) with a high (94%) probability of eye irritation.

Conclusion

Overall, combining computational toxicology with experimental data can prove useful as a method of early hazard screening, and these results point out that although the other compounds are effective at suppressing thermal pain signals, it would be worth validating these for safety before applying them as therapeutics.

Graphical Abstract