Investigation of the Toxicity and Mechanisms of Acetyl Tributyl Citrate in Chronic Liver Injury Using Network Toxicology and Molecular Docking Techniques
DOI:
https://doi.org/10.54097/b39h2z79Keywords:
Acetyl Tributyl Citrate (ATBC), Network Toxicology, Liver Injury, Molecular DockingAbstract
Acetyl tributyl citrate (ATBC) is a commonly used plasticizing agent. Recent studies have shown that long-term exposure to ATBC may cause liver injury, but the mechanism of injury still needs to be further studied. The aim of this study is to investigate the hepatotoxicity and potential mechanism of ATBC using network toxicology strategy. Two online sites, ADMETlab and ProTex, were used to search the toxic effects of acetyl-tributyl citrate. Then six databases, ChEMBL, STITCH, SwissTargetPrediction, GeneCards, TTD, OMIM, were used to search the toxic effects of acetyl-tributyl citrate. We identified 43 potential biomarkers associated with ATBC exposure and liver injury. Using comprehensive analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we found that the targets of ATBC induced liver injury were mainly enriched in metabolic disorders, oxidative stress, inflammatory response, organelle dysfunction, abnormal enzyme activity, and protein kinase signaling pathway disorders. Then we used Cytoscape software and STRING website optimization to highlight five core targets. Finally, we used molecular docking technology to combine these five core targets, and confirmed the high binding affinity of ATBC with the core targets. In summary, these results suggest that ATBC may induce liver injury through a closely related cascade of metabolism imbalance, organelle dysfunction, oxidative stress, inflammation, and fibrosis. On the basis of previous findings, this study confirmed that ATBC causes chronic liver injury, explored its injury mechanism, and provided a systematic and effective framework for researchers to evaluate the potential toxicity of various chemical products and medical devices.
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[1] Ziani K, Ioniță-Mîndrican CB, Mititelu M, et al. Microplastics: A Real Global Threat for Environment and Food Safety: A State of the Art Review. Nutrients. 2023;15(3):617. doi:10. 3390/ nu15030617.
[2] Tao W, Xu X, Wang X, et al. Network pharmacology-based prediction of the active ingredients and potential targets of Chinese herbal Radix Curcumae formula for application to cardiovascular disease. J Ethnopharmacol. 2013;145(1):1-10. doi:10.1016/j.jep.2012.09.051.
[3] Y Z, J L, G S. Comprehensively screening of citric acid ester (CAE) plasticizers in Chinese foodstuffs, and the food-based assessment of human exposure risk of CAEs. The Science of the total environment. 2022;817. doi:10.1016/j. scitotenv. 2022. 152933.
[4] Yu L, Yang M, Cheng M, et al. Associations between urinary phthalate metabolite concentrations and markers of liver injury in the US adult population. Environ Int. 2021;155:106608. doi:10.1016/j.envint.2021.106608.
[5] Ae G, U B, G D. Phthalate esters and their effect on the liver. Hepatology (Baltimore, Md). 1984;4(3). doi:10.1002/ hep. 1840040331.
[6] Fu L, Shi S, Yi J, et al. ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support. Nucleic Acids Res. 2024; 52 (W1): W422-W431. doi:10.1093/nar/gkae236.
[7] Nowotka MM, Gaulton A, Mendez D, Bento AP, Hersey A, Leach A. Using ChEMBL web services for building applications and data processing workflows relevant to drug discovery. Expert Opin Drug Discov. 2017;12(8):757-767. doi: 10. 1080/17460441.2017.1339032.
[8] Stelzer G, Rosen N, Plaschkes I, et al. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. Curr Protoc Bioinformatics. 2016;54:1.30.1-1.30.33. doi: 10.1002/cpbi.5.
[9] Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498-2504. doi:10. 1101/ gr. 1239303.
[10] Szklarczyk D, Kirsch R, Koutrouli M, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023;51(D1):D638-D646. doi:10. 1093/ nar/gkac1000.
[11] Shi W, Zhang X, Xu C, et al. Identification of Hub Genes and Pathways Associated with Oxidative Stress of Cartilage in Osteonecrosis of Femoral Head Using Bioinformatics Analysis. Cartilage. 2022;13(1):19476035221074000. doi:10.1177/ 194 76035221074000.
[12] Wu T, Hu E, Xu S, et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation (Camb). 2021;2(3):100141. doi: 10.1016/j.xinn.2021.100141.
[13] Gene Ontology Consortium. Gene Ontology Consortium: going forward. Nucleic Acids Res. 2015;43(Database issue): D1049-1056. doi:10.1093/nar/gku1179.
[14] Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27-30. doi:10.1093/ nar/ 28.1.27.
[15] Liu Y, Yang X, Gan J, Chen S, Xiao ZX, Cao Y. CB-Dock2: improved protein-ligand blind docking by integrating cavity detection, docking and homologous template fitting. Nucleic Acids Res. 2022;50(W1):W159-W164. doi:10.1093/ nar/gkac 394.
[16] Liu Y, Cao Y. Protein-Ligand Blind Docking Using CB-Dock2. Methods Mol Biol. 2024; 2714:113-125. doi:10.1007/978-1-0716-3441-7_6.
[17] Cao H, Cai Q, Guo W, et al. Malonylation of Acetyl-CoA carboxylase 1 promotes hepatic steatosis and is attenuated by ketogenic diet in NAFLD. Cell Rep. 2023;42(4):112319. doi: 10. 1016/j.celrep.2023.112319.
[18] Calle RA, Amin NB, Carvajal-Gonzalez S, et al. ACC inhibitor alone or co-administered with a DGAT2 inhibitor in patients with non-alcoholic fatty liver disease: two parallel, placebo-controlled, randomized phase 2a trials. Nat Med. 2021;27 (10): 1836-1848. doi:10.1038/s41591-021-01489-1.
[19] Lally JSV, Ghoshal S, DePeralta DK, et al. Inhibition of Acetyl-CoA Carboxylase by Phosphorylation or the Inhibitor ND-654 Suppresses Lipogenesis and Hepatocellular Carcinoma. Cell Metab. 2019;29(1):174-182.e5. doi:10.1016/j. cmet. 2018.08.020.
[20] Convertini P, Santarsiero A, Todisco S, et al. ACLY as a modulator of liver cell functions and its role in Metabolic Dysfunction-Associated Steatohepatitis. J Transl Med. 2023; 21 (1):568. doi:10.1186/s12967-023-04431-w.
[21] Morrow MR, Batchuluun B, Wu J, et al. Inhibition of ATP-citrate lyase improves NASH, liver fibrosis, and dyslipidemia. Cell Metab. 2022;34(6):919-936.e8. doi:10.1016/j. cmet.2022. 05. 004.
[22] Burke AC, Huff MW. ATP-citrate lyase: genetics, molecular biology and therapeutic target for dyslipidemia. Curr Opin Lipidol. 2017;28(2):193-200. doi:10.1097/MOL. 00000000 00000390.
[23] Paul B, Lewinska M, Andersen JB. Lipid alterations in chronic liver disease and liver cancer. JHEP Rep. 2022;4(6):100479. doi:10.1016/j.jhepr.2022.100479.
[24] Granchi C. ATP citrate lyase (ACLY) inhibitors: An anti-cancer strategy at the crossroads of glucose and lipid metabolism. Eur J Med Chem. 2018;157:1276-1291. doi:10. 1016/ j.ejmech.2018.09.001.
[25] Gu L, Zhu Y, Lin X, et al. The IKKβ-USP30-ACLY Axis Controls Lipogenesis and Tumorigenesis. Hepatology. 2021;73(1):160-174. doi:10.1002/hep.31249.
[26] Park BY, Jeon JH, Go Y, et al. PDK4 Deficiency Suppresses Hepatic Glucagon Signaling by Decreasing cAMP Levels. Diabetes. 2018;67(10):2054-2068. doi:10.2337/db17-1529.
[27] Zhao Y, Tran M, Wang L, Shin DJ, Wu J. PDK4-Deficiency Reprograms Intrahepatic Glucose and Lipid Metabolism to Facilitate Liver Regeneration in Mice. Hepatol Commun. 2020;4(4):504-517. doi:10.1002/hep4.1484.
[28] Duan L, Ramachandran A, Akakpo JY, Woolbright BL, Zhang Y, Jaeschke H. Mice deficient in pyruvate dehydrogenase kinase 4 are protected against acetaminophen-induced hepatotoxicity. Toxicol Appl Pharmacol. 2020;387:114849. doi: 10. 1016/j.taap.2019.114849.
[29] Tao S, Tao K, Cai X. Pan-cancer analysis reveals PDK family as potential indicators related to prognosis and immune infiltration. Sci Rep. 2024;14(1):5665. doi:10.1038/s41598-024-55455-1.
[30] Qin YJ, Lin TY, Lin XL, et al. Loss of PDK4 expression promotes proliferation, tumorigenicity, motility and invasion of hepatocellular carcinoma cells. J Cancer. 2020;11 (15): 4397-4405. doi:10.7150/jca.43459.
[31] Goedeke L, Bates J, Vatner DF, et al. Acetyl-CoA Carboxylase Inhibition Reverses NAFLD and Hepatic Insulin Resistance but Promotes Hypertriglyceridemia in Rodents. Hepatology. 2018;68(6):2197-2211. doi:10.1002/hep.30097.
[32] Lv T, Fan X, He C, et al. SLC7A11-ROS/αKG-AMPK axis regulates liver inflammation through mitophagy and impairs liver fibrosis and NASH progression. Redox Biol. 2024;72: 103159. doi:10.1016/j.redox.2024.103159.
[33] Kikuchi S, Piraino G, O’Connor M, et al. Hepatocyte-Specific Deletion of AMPKα1 Results in Worse Outcomes in Mice Subjected to Sepsis in a Sex-Specific Manner. Front Immunol. 2020; 11:210. doi:10.3389/fimmu.2020.00210.
[34] Kim P, Piraino G, O’Connor M, et al. Metformin Exerts Beneficial Effects in Hemorrhagic Shock in An AMPKα1-Independent Manner. Shock. 2018;49(3):277-287. doi:10. 1097/ SHK.0000000000000984.
[35] Sun H, Kemper JK. MicroRNA regulation of AMPK in nonalcoholic fatty liver disease. Exp Mol Med. 2023;55(9): 1974-1981. doi:10.1038/s12276-023-01072-3.
[36] Jang HJ, Lee YH, Dao T, et al. Thrap3 promotes nonalcoholic fatty liver disease by suppressing AMPK-mediated autophagy. Exp Mol Med. 2023;55(8):1720-1733. doi:10.1038/s12276-023-01047-4.
[37] Tuleta I, Frangogiannis NG. Diabetic fibrosis. Biochim Biophys Acta Mol Basis Dis. 2021;1867(4):166044. doi:10. 1016/ j. bbadis. 2020.166044.
[38] Chen H, Wong CC, Liu D, et al. APLN promotes hepatocellular carcinoma through activating PI3K/Akt pathway and is a druggable target. Theranostics. 2019;9(18):5246-5260. doi:10. 7150/ thno.34713.
[39] Marí M, Fernández-Checa JC. Sphingolipid signalling and liver diseases. Liver Int. 2007;27(4):440-450. doi:10.1111/j. 1478-3231. 2007. 01475. x.
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