Selenoprotein thioredoxin reductase mediated menadione reduction: catalytic properties & inhibition effects / 生物工程学报

Thioredoxin reductase (TrxR) is one class of the most important antioxidant selenoproteins and is involved in regulating tumor genesis and progression. It has been reported that naphthoquinones can target and inhibit TrxR1 activity therefore produce reactive oxygen species (ROS) mediated by TrxR1, resulting into cellular redox imbalance and making the naphthoquinone compounds to become potential antitumor chemotherapy drugs. The purpose of this work is to explore the interaction between TrxR1 and menadione using biochemical and mass-spectrometric (MS) analyses, to further reveal the detailed mechanisms of TrxR1-mediated naphthoquinone reduction and inhibition of TrxR1 by naphthoquinone compounds. Using the site-directed mutagenesis and recombinantly expressed TrxR1 variants, we measured the steady-state kinetic parameters of menadione reduction mediated by TrxR1 and its variants, performed the inhibition analysis of menadione on TrxR1 activity, and eventually identified the interaction between menadione and TrxR1 through MS analysis. We found that Sec-to-Cys mutation at residue of 498 significantly enhanced the efficiency of TrxR1-mediated menadione reduction, though the Sec⁴⁹⁸ is capable to catalyze the menadione reduction, indicating that TrxR1-mediated menadione reduction is dominantly in a Se-independent manner. Mutation experiments showed that Cys⁴⁹⁸ is mainly responsible for menadione catalysis in comparison to Cys⁴⁹⁷, while the N-terminal Cys⁶⁴ is slightly stronger than Cys⁵⁹ regarding the menadione reduction. LC-MS results detected that TrxR1 was arylated with one molecule of menadione, suggesting that menadione irreversibly modified the hyper-reactive Sec residue at the C-terminus of selenoprotein TrxR1. This study revealed that TrxR1 catalyzes the reduction of menadione in a Se-independent manner meanwhile its activity is irreversibly inhibited by menadione. Hereby it will be useful for the research and development of naphthoquinone anticancer drugs targeting TrxR1.

Genetic Variations in TXNRD1 as Potential Predictors of Drug-Induced Liver Injury

PURPOSE: Drug-induced liver injury (DILI) is the most common adverse drug reaction; however, it is not easily predicted. We hypothesize that DILI has a common genetic basis. Based on the findings of previous animal studies on toxic hepatitis, we selected the thioredoxin reductase 1 gene (TXNRD1) as a candidate marker of DILI for this genetic association study. METHODS: Records from 118 patients with DILI were extracted from the database of the Adverse Drug Reaction Research Group in South Korea. Causative drugs included antituberculosis drugs (n=68, 57.6%), antibiotics (n=22, 18.6%), antiepileptic drugs (n=7, 5.9%), non-steroidal anti-inflammatory drugs (n=5, 4.2%), and others (n=16, 13.7%). Seven single nucleotide polymorphisms (SNPs) in TXNRD1 (rs10735393, rs4964287, rs4595619, rs10861201, rs11111997, rs4246270, and rs4246271) were scored in 118 DILI patients and in 120 drug-matched controls without liver injury. RESULTS: No differences were found between the frequencies of any of the 7 SNPs in the cases and controls; however, a significant association was found between a TTA haplotype composed of rs10735393, rs4964287, and rs4595619 and DILI using an allele model (odds ratio, 1.79; 95% confidence interval, 1.18-2.73; P=0.008; Bonferroni corrected P=0.024). CONCLUSIONS: These results suggest that genetic variations in TXNRD1 favor the development of DILI, although a larger confirmative study is needed.

Thioredoxin system: a model for determining novel lead molecules for breast Cancer chemotherapy

Thioredoxin reductase 1 [TXNRD1] and thioredoxin interacting protein [TXNIP] also known as thioredoxin binding protein 2 or vitamin D3-upregulated protein 1 are key players in oxidative stress control. Thioredoxin [TRX] is one of the major components of the thiol reducing system and plays multiple roles in cellular processes. Computational analyses of TXNRD1, TXNIP and TRX expressions have not been analyzed in relation to prognosis of breast cancer. High expression of TXNRD1 and low expression of TXNIP are associated with worst prognosis in breast cancer. Using bioinformatics applications we studied sequence analysis, molecular modeling, template and fold recognition, docking and scoring of thioredoxin as a target. The resultant model obtained was validated based on the templates from I-TASSER server and binding site residues were predicted. The predicted model was used for Threading and Fold recognition and was optimized using GROMACS. The generated model was validated using programs such as Procheck, Ramachandran plot, verify-3d and Errat value from Saves server, and the results show that the model is reliable. Next we obtained small molecules from pubchem and chembank which are databases for selecting suitable ligands for our modeled target. These molecules were screened for docking, using GOLD and scoring was obtained using Chemscore as a scoring function. This study predicted the ligand interaction of four molecules with the minimized protein modeled structure and the best ligand with top scores from about 500 molecules screened. These were 3-hydroxy-2,3-diphenylbutanoic acid, 4-amino-3-pentadecylphenol, 3-[hydroxyimino]-2,4-diphenylbutanenitrile and 2-ethyl-1,2-diphenylbutyl carbamate, which are proposed as possible hit molecules for the drug discovery and development process