Araştırma Makalesi

Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms

Cilt: 5 Sayı: 1 27 Haziran 2025
PDF İndir
EN TR

Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms

Öz

Chlorfenapyr is a pyrrole-class pesticide with a unique mechanism of action that disrupts mitochondrial oxidative phosphorylation. Despite its broad-spectrum insecticidal use, publicly available toxicological data on chlorfenapyr remain limited, particularly regarding organ-specific and long-term effects. To address this data gap, the present study implements a multi-model in silico toxicity assessment using three AI-based platforms—SwissADME, ProTox-II, and ADMETlab 2.0—to predict key toxicokinetic and toxicodynamic properties from the compound’s SMILES representation. Physicochemical and pharmacokinetic parameters such as molecular weight, lipophilicity, gastrointestinal absorption, and cytochrome P450 inhibition were consistently predicted across platforms. However, notable discrepancies emerged in blood–brain barrier (BBB) permeability and hepatotoxicity outcomes. Acute toxicity was estimated with a predicted LD₅₀ of 55 mg/kg (Class 3), while organ-specific risks included neurotoxicity and respiratory toxicity. Both platforms highlighted mitochondrial membrane potential disruption and oxidative stress pathways as probable mechanisms of toxicity. Toxicophore analysis further revealed substructures associated with non-genotoxic carcinogenicity, aquatic toxicity, and poor biodegradability, raising environmental safety concerns. By combining complementary model outputs, this AI-supported approach allows for scalable, reproducible, and ethically favorable screening of chemical hazards. The findings demonstrate that multi-endpoint in silico toxicology workflows can effectively identify early warning signals of compound toxicity and guide future experimental priorities—particularly for chemicals like chlorfenapyr, where experimental data are scarce and regulatory insight is urgently needed.

Anahtar Kelimeler

Kaynakça

  1. G. T. Comstock, H. Nguyen, A. Bronstein, and L. Yip, “Chlorfenapyr poisoning: a systematic review,” Clin Toxicol (Phila), vol. 62, no. 7, pp. 412–424, Jul. 2024, doi: 10.1080/15563650.2024.2367658.
  2. S. S. Shinde, P. S. Giram, P. S. Wakte, and S. S. Bhusari, “ADMET tools in the digital era: Applications and limitations,” Adv Pharmacol, vol. 103, pp. 65–80, 2025, doi: 10.1016/bs.apha.2025.01.004.
  3. L. Peltason and J. Bajorath, “Systematic computational analysis of structure-activity relationships: concepts, challenges and recent advances,” Future Med Chem, vol. 1, no. 3, pp. 451–466, Jun. 2009, doi: 10.4155/fmc.09.41.
  4. A. Daina, O. Michielin, and V. Zoete, “SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules,” Sci Rep, vol. 7, p. 42717, Mar. 2017, doi: 10.1038/srep42717.
  5. P. Banerjee, A. O. Eckert, A. K. Schrey, and R. Preissner, “ProTox-II: a webserver for the prediction of toxicity of chemicals,” Nucleic Acids Res, vol. 46, no. W1, pp. W257–W263, Jul. 2018, doi: 10.1093/nar/gky318.
  6. G. Xiong et al., “ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties,” Nucleic Acids Res, vol. 49, no. W1, pp. W5–W14, Jul. 2021, doi: 10.1093/nar/gkab255.
  7. D. F. El Sherif et al., “The binary mixtures of lambda-cyhalothrin, chlorfenapyr, and abamectin, against the house fly larvae, Musca domestica L.,” Molecules, vol. 27, no. 10, p. 3084, 2022.
  8. S. Ohnuki, S. Tokishita, M. Kojima, and S. Fujiwara, “Effect of chlorpyrifos‐exposure on the expression levels of CYP genes in Daphnia magna and examination of a possibility that an up‐regulated clan 3 CYP , CYP360A8 , reacts with pesticides,” Environmental Toxicology, vol. 39, no. 6, pp. 3641–3653, Jun. 2024, doi: 10.1002/tox.24224.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Modelleme ve Simülasyon, Yapay Zeka (Diğer)

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

27 Haziran 2025

Gönderilme Tarihi

8 Nisan 2025

Kabul Tarihi

16 Haziran 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 5 Sayı: 1

Kaynak Göster

APA
Yaman, Ü. (2025). Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms. Journal of Artificial Intelligence and Data Science, 5(1), 44-52. https://izlik.org/JA22EL73PW
AMA
1.Yaman Ü. Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms. Journal of Artificial Intelligence and Data Science. 2025;5(1):44-52. https://izlik.org/JA22EL73PW
Chicago
Yaman, Ünzile. 2025. “Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms”. Journal of Artificial Intelligence and Data Science 5 (1): 44-52. https://izlik.org/JA22EL73PW.
EndNote
Yaman Ü (01 Haziran 2025) Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms. Journal of Artificial Intelligence and Data Science 5 1 44–52.
IEEE
[1]Ü. Yaman, “Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms”, Journal of Artificial Intelligence and Data Science, c. 5, sy 1, ss. 44–52, Haz. 2025, [çevrimiçi]. Erişim adresi: https://izlik.org/JA22EL73PW
ISNAD
Yaman, Ünzile. “Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms”. Journal of Artificial Intelligence and Data Science 5/1 (01 Haziran 2025): 44-52. https://izlik.org/JA22EL73PW.
JAMA
1.Yaman Ü. Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms. Journal of Artificial Intelligence and Data Science. 2025;5:44–52.
MLA
Yaman, Ünzile. “Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms”. Journal of Artificial Intelligence and Data Science, c. 5, sy 1, Haziran 2025, ss. 44-52, https://izlik.org/JA22EL73PW.
Vancouver
1.Ünzile Yaman. Integrative In Silico Toxicity Assessment of Chlorfenapyr Using AI-Driven Platforms. Journal of Artificial Intelligence and Data Science [Internet]. 01 Haziran 2025;5(1):44-52. Erişim adresi: https://izlik.org/JA22EL73PW