Network Toxicology Prediction and Molecular Docking-based Strategy to Explore the Potential Toxicity Mechanism of Metformin Chlorination Byproducts in Drinking Water

Abstract

Background: Metformin (MET), a worldwide used drug for treating type 2 diabetes but not metabolized by humans, has been found with the largest amount in the aquatic environment. Two MET chlorination byproducts, including Y and C, were transformed into drinking water during chlorination. However, the potential toxicity of the byproducts in hepatotoxicity and reproduction toxicity remains unclear. Methods: The TOPKAT database predicted the toxicological properties of metformin disinfection by-products. The targets of metformin disinfection by-products were mainly obtained from the PharmMapper database, and then the targets of hepatotoxicity and reproductive toxicity were screened from GeneCards. The overlapping targets of toxic component targets and the hepatotoxicity or reproduction toxicity targets were regarded as the key targets. Then, the STRING database analyzed the key target to construct a protein-protein interaction network (PPI) and GO, and KEGG analysis was performed by the DAVID platform. Meanwhile, the PPI network and compound-target network were constructed by Cytoscape 3.9.1. Finally, Discovery Studio 2019 software was used for molecular docking verification of the two toxic compounds and the core genes. Results: Y and C exhibited hepatotoxicity, carcinogenicity, and mutagenicity evaluated by TOPKAT. There were 22 potential targets relating to compound Y and hepatotoxicity and reproduction toxicity and 14 potential targets relating to compound C and hepatotoxicity and reproduction toxicity. PPI network analysis showed that SRC, MAPK14, F2, PTPN1, IL2, MMP3, HRAS, and RARA might be the key targets; the KEGG analysis indicated that compounds Y and C caused hepatotoxicity through Hepatitis B, Pathways in cancer, Chemical carcinogenesis-reactive oxygen species, Epstein-Barr virus infection; compound Y and C caused reproduction toxicity through GnRH signaling pathway, Endocrine resistance, Prostate cancer, Progesterone-mediated oocyte maturation. Molecular docking results showed that 2 compounds could fit in the binding pocket of the 7 hub genes. Conclusion: This study preliminarily revealed the potential toxicity and possible toxicity mechanism of metformin disinfection by-products and provided a new idea for follow-up research.

Exploring the mechanisms underlying effects of bisphenol a on cardiovascular disease by network toxicology and molecular docking

“…In addition, network toxicology strategy was used to assess toxicity and mechanisms of ATBC-induced brain toxicity [ 24 ]. Furthermore, hepatotoxicity, carcinogenicity, mutagenicity and testicular injury induced by metformin chlorination byproducts and cantharidin were also reported to explored by network toxicology [ 25 , 26 ]. However, the underlying molecular mechanisms of environmental pollutants, such as BPA on CVD remain elusive.…”

Tripterygium wilfordii Hook.f induced kidney injury through mediating inflammation via PI3K-Akt/HIF-1/TNF signaling pathway: A study of network toxicology and molecular docking

“…[20] Through analyzing the network connection between organism and toxic compounds that contribute to abnormal biological functions, we can explain the toxicological mechanisms of toxic compounds. [21] Molecular docking is a theoretical simulation technology which often used to study inter-molecular interactions and predict their binding modes and affinities for further new drug discovery. [22,23] In the study, we conducted a multi-compounds, multitargets and multi-approaches study using network toxicology and molecular docking to determine the main toxic compounds of TwHF induced KI and explain the toxicology mechanism of TwHF-induced KI.…”

“…[ 20 ] Through analyzing the network connection between organism and toxic compounds that contribute to abnormal biological functions, we can explain the toxicological mechanisms of toxic compounds. [ 21 ] Molecular docking is a theoretical simulation technology which often used to study inter-molecular interactions and predict their binding modes and affinities for further new drug discovery. [ 22 , 23 ]…”