Mechanism of AGT-Mediated Repair of dG-dC Cross-Links in the Drug Resistance to Chloroethylnitrosoureas: Molecular Docking, MD Simulation, and ONIOM (QM/MM) Investigation.

Chloroethylnitrosoureas (CENUs) are important chemotherapies applied in the treatment of cancer. They exert anticancer activity by inducing DNA interstrand cross-links (ICLs) via the formation of two O6-alkylguanine intermediates, O6-chloroethylguanine (O6-ClEtG) and N1,O6-ethanoguanine (N1,O6-EtG). However, O6-alkylguanine-DNA alkyltransferase (AGT), a DNA-repair enzyme, can restore the O6-alkylguanine damages and thereby obstruct the formation of ICLs (dG-dC cross-link). In this study, the inhibitory mechanism of ICL formation was investigated to elucidate the drug resistance of CENUs mediated by AGT in detail. Based on the structures of the substrate-enzyme complexes obtained from docking and MD simulations, two ONIOM (QM/MM) models with different sizes of the QM region were constructed. The model with a larger QM region, which included the substrate (O6-ClEtG or N1,O6-EtG), a water molecule, and five residues (Tyr114, Cys145, His146, Lys165, and Glu172) in the active pocket of AGT, accurately described the repairing reaction and generated the results coinciding with the experimental outcomes. The repair process consists of two sequential steps: hydrogen transfer to form a thiolate anion on Cys145 and alkyl transfer from the O6 site of guanine (the rate-limiting step). The repair of N1,O6-EtG was more favorable than that of O6-ClEtG from both kinetics and thermodynamics aspects. Moreover, the comparison of the repairing process with the formation of dG-dC cross-link and the inhibition of AGT by O6-benzylguanine (O6-BG) showed that the presence of AGT could effectively interrupt the formation of ICLs leading to drug resistance, and the inhibition of AGT by O6-BG that was energetically more favorable than the repair of O6-ClEtG could not prevent the repair of N1,O6-EtG. Therefore, it is necessary to completely eliminate AGT activity before CENUs medication to enhance the chemotherapeutic effectiveness. This work provides reasonable explanations for the supposed mechanism of AGT-mediated drug resistance of CENUs and will assist in the development of novel CENU chemotherapies and their medication strategies.

The rat acute oral toxicity of trifluoromethyl compounds (TFMs): a computational toxicology study combining the 2D-QSTR, read-across and consensus modeling methods.

All areas of the modern society are affected by fluorine chemistry. In particular, fluorine plays an important role in medical, pharmaceutical and agrochemical sciences. Amongst various fluoro-organic compounds, trifluoromethyl (CF3) group is valuable in applications such as pharmaceuticals, agrochemicals and industrial chemicals. In the present study, following the strict OECD modelling principles, a quantitative structure-toxicity relationship (QSTR) modelling for the rat acute oral toxicity of trifluoromethyl compounds (TFMs) was established by genetic algorithm-multiple linear regression (GA-MLR) approach. All developed models were evaluated by various state-of-the-art validation metrics and the OECD principles. The best QSTR model included nine easily interpretable 2D molecular descriptors with clear physical and chemical significance. The mechanistic interpretation showed that the atom-type electro-topological state indices, molecular connectivity, ionization potential, lipophilicity and some autocorrelation coefficients are the main factors contributing to the acute oral toxicity of TFMs against rats. To validate that the selected 2D descriptors can effectively characterize the toxicity, we performed the chemical read-across analysis. We also compared the best QSTR model with public OPERA tool to demonstrate the reliability of the predictions. To further improve the prediction range of the QSTR model, we performed the consensus modelling. Finally, the optimum QSTR model was utilized to predict a true external set containing many untested/unknown TFMs for the first time. Overall, the developed model contributes to a more comprehensive safety assessment approach for novel CF3-containing pharmaceuticals or chemicals, reducing unnecessary chemical synthesis whilst saving the development cost of new drugs.

A multi-functional hypoxia/esterase dual stimulus responsive and hyaluronic acid-based nanomicelle for targeting delivery of chloroethylnitrosouea.

Carmustine (BCNU), a vital type of chloroethylnitrosourea (CENU), inhibits tumor cells growth by inducing DNA damage at O6 position of guanine and eventually forming dG-dC interstrand cross-links (ICLs). However, the clinical application of BCNU is hindered to some extent by the absence of tumor selectivity, poor stability and O6-alkylguanine-DNA alkyltransferase (AGT) mediated drug resistance. In recent years, tumor microenvironment has been widely utilized for advanced drug delivery. In the light of the features of tumor microenvironment, we constructed a multifunctional hypoxia/esterase-degradable nanomicelle with AGT inhibitory activity named HACB NPs for tumor-targeting BCNU delivery and tumor sensitization. HACB NPs was self-assembled from hyaluronic acid azobenzene AGT inhibitor conjugates, in which O6-BG analog acted as an AGT inhibitor, azobenzene acted as a hypoxia-responsive linker and carboxylate ester bond acted as both an esterase-sensitive switch and a connector with hyaluronic acid (HA). The obtained HACB NPs possessed good stability, favorable biosafety and hypoxia/esterase-responsive drug-releasing ability. BCNU-loaded HACB/BCNU NPs exhibited superior cytotoxicity and apoptosis-inducing ability toward the human uterine cervix carcinoma HeLa cells compared with traditional combined medication of BCNU plus O6-BG. In vivo studies further demonstrated that after a selective accumulation in the tumor site, the micelles could respond to hypoxic tumor tissue for rapid drug release to an effective therapeutic dosage. Thus, this multifunctional stimulus-responsive nanocarrier could be a new promising strategy to enhance the anticancer efficacy and reduce the side effects of BCNU and other CENUs.

Molecular Toxicology and Cancer Prevention.

Molecular toxicology is a field that investigates the interactions between chemical or biological molecules and organisms at the molecular level [...].

Identification of Pharmacophoric Fragments of DYRK1A Inhibitors Using Machine Learning Classification Models.

Dual-specific tyrosine phosphorylation regulated kinase 1 (DYRK1A) has been regarded as a potential therapeutic target of neurodegenerative diseases, and considerable progress has been made in the discovery of DYRK1A inhibitors. Identification of pharmacophoric fragments provides valuable information for structure- and fragment-based design of potent and selective DYRK1A inhibitors. In this study, seven machine learning methods along with five molecular fingerprints were employed to develop qualitative classification models of DYRK1A inhibitors, which were evaluated by cross-validation, test set, and external validation set with four performance indicators of predictive classification accuracy (CA), the area under receiver operating characteristic (AUC), Matthews correlation coefficient (MCC), and balanced accuracy (BA). The PubChem fingerprint-support vector machine model (CA = 0.909, AUC = 0.933, MCC = 0.717, BA = 0.855) and PubChem fingerprint along with the artificial neural model (CA = 0.862, AUC = 0.911, MCC = 0.705, BA = 0.870) were considered as the optimal modes for training set and test set, respectively. A hybrid data balancing method SMOTETL, a combination of synthetic minority over-sampling technique (SMOTE) and Tomek link (TL) algorithms, was applied to explore the impact of balanced learning on the performance of models. Based on the frequency analysis and information gain, pharmacophoric fragments related to DYRK1A inhibition were also identified. All the results will provide theoretical supports and clues for the screening and design of novel DYRK1A inhibitors.

Chemometric QSAR modeling of acute oral toxicity of Polycyclic Aromatic Hydrocarbons (PAHs) to rat using simple 2D descriptors and interspecies toxicity modeling with mouse.

The information of the acute oral toxicity for most polycyclic aromatic hydrocarbons (PAHs) in mammals are lacking due to limited experimental resources, leading to a need to develop reliable in silico methods to evaluate the toxicity endpoint. In this study, we developed the quantitative structure-activity relationship (QSAR) models by genetic algorithm (GA) and multiple linear regression (MLR) for the rat acute oral toxicity (LD50) of PAHs following the strict validation principles of QSAR modeling recommended by OECD. The best QSAR model comprised eight simple 2D descriptors with definite physicochemical meaning, which showed that maximum atom-type electrotopological state, van der Waals surface area, mean atomic van der Waals volume, and total number of bonds are main influencing factors for the toxicity endpoint. A true external set (554 compounds) without rat acute oral toxicity values, and 22 limit test compounds, were firstly predicted along with reliability assessment. We also compared our proposed model with the OPERA predictions and recently published literature to prove the prediction reliability. Furthermore, the interspecies toxicity (iST) models of PAHs between rat and mouse were also established, validated and employed for filling data gap. Overall, our developed models should be applicable to new or untested or not yet synthesized PAHs falling within the applicability domain (AD) of the models for rapid acute oral toxicity prediction, thus being important for environmental or personal exposure risk assessment under regulatory frameworks.

Quantitative Structure-Activity Relationship (QSAR) Studies on the Toxic Effects of Nitroaromatic Compounds (NACs): A Systematic Review.

Nitroaromatic compounds (NACs) are ubiquitous in the environment due to their extensive industrial applications. The recalcitrance of NACs causes their arduous degradation, subsequently bringing about potential threats to human health and environmental safety. The problem of how to effectively predict the toxicity of NACs has drawn public concern over time. Quantitative structure-activity relationship (QSAR) is introduced as a cost-effective tool to quantitatively predict the toxicity of toxicants. Both OECD (Organization for Economic Co-operation and Development) and REACH (Registration, Evaluation and Authorization of Chemicals) legislation have promoted the use of QSAR as it can significantly reduce living animal testing. Although numerous QSAR studies have been conducted to evaluate the toxicity of NACs, systematic reviews related to the QSAR modeling of NACs toxicity are less reported. The purpose of this review is to provide a thorough summary of recent QSAR studies on the toxic effects of NACs according to the corresponding classes of toxic response endpoints.

Synergistic Effect between Human Papillomavirus 18 and 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone on Malignant Transformation of Immortalized SHEE Cells.

4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is an important tobacco-specific nitrosamine (TSNA) that induces malignant tumors in rodents. High-risk human papillomavirus (hr-HPV) infection is an important cause of several human cancers. Epidemiological evidence has shown that HPV cooperatively induces carcinogenesis with tobacco smoke. In the present study, the synergistic carcinogenesis of NNK and HPV18 was investigated. Immortalized human esophageal epithelial SHEE cells containing the HPV18 E6E7 gene were constructed by lentiviral transfection. SHEE-E6E7 cells were exposed to NNK along with SHEE-V cells without HPV18 E6E7 as a negative control. The cooperation of NNK and HPV was examined by wound-healing, transwell, and colony-forming assays. The results showed that NNK exposure promoted the migration, invasion, and proliferation abilities of both SHEE-E6E7 and SHEE-V cells; however, the changes in these phenotypic features were remarkably stronger in SHEE-E6E7 cells than those in SHEE-V cells. Our findings indicate that NNK promotes malignant transformation of human esophageal epithelial cells and suggest a synergistic carcinogenesis with the HPV18 E6E7 oncogene. As reported previously, the formation of pyridyloxybutylated DNA adducts is a crucial step in NNK-mediated carcinogenesis. In order to clarify the influence of HPV on the formation of NNK-induced DNA adducts, the amounts of 4-hydroxy-1-(3-pyridyl)-1-butanone (HPB)-releasing DNA adducts were determined using high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry. We observed that the levels of HPB-releasing adducts in SHEE-E6E7 cells were significantly higher (p < 0.01) than those of SHEE-V cells, which was in line with results of the phenotypic assays. In conclusion, this study provides direct evidence that NNK and HPV18 exhibit a synergistic effect on formation of DNA adducts, resulting in malignant transformation of esophageal epithelial cells. Such knowledge on the interaction between infection and smoking habits in the development of cancers informs cancer-prevention strategies. Further studies to delineate the molecular mechanism and to identify specific intervention targets are worthwhile.

Identification and Biological Evaluation of CK2 Allosteric Fragments through Structure-Based Virtual Screening.

Casein kinase II (CK2) is considered as an attractive cancer therapeutic target, and recent efforts have been made to develop its ATP-competitive inhibitors. However, achieving selectivity with respect to related kinases remains challenging due to the highly conserved ATP-binding pocket of kinases. Allosteric inhibitors, by targeting the much more diversified allosteric site relative to the highly conserved ATP-binding pocket, might be a promising strategy with the enhanced selectivity and reduced toxicity than ATP-competitive inhibitors. The previous studies have highlighted the traditional serendipitousity of discovering allosteric inhibitors owing to the complicate allosteric modulation. In this current study, we identified the novel allosteric inhibitors of CK2α by combing structure-based virtual screening and biological evaluation methods. The structure-based pharmacophore model was built based on the crystal structure of CK2α-compound 15 complex. The ChemBridge fragment library was searched by evaluating the fit values of these molecules with the optimized pharmacophore model, as well as the binding affinity of the CK2α-ligand complexes predicted by Alloscore web server. Six hits forming the holistic interaction mechanism with the αD pocket were retained after pharmacophore- and Alloscore-based screening for biological test. Compound 3 was found to be the most potent non-ATP competitive CK2α inhibitor (IC50 = 13.0 µM) with the anti-proliferative activity on A549 cancer cells (IC50 = 23.1 µM). Our results provide new clues for further development of CK2 allosteric inhibitors as anti-cancer hits.

Prediction on the mutagenicity of nitroaromatic compounds using quantum chemistry descriptors based QSAR and machine learning derived classification methods.

Nitroaromatic compounds (NACs) are an important type of environmental organic pollutants. However, it is lack of sufficient information relating to their potential adverse effects on human health and the environment due to the limited resources. Thus, using in silico technologies to assess their potential hazardous effects is urgent and promising. In this study, quantitative structure activity relationship (QSAR) and classification models were constructed using a set of NACs based on their mutagenicity against Salmonella typhimurium TA100 strain. For QSAR studies, DRAGON descriptors together with quantum chemistry descriptors were calculated for characterizing the detailed molecular information. Based on genetic algorithm (GA) and multiple linear regression (MLR) analyses, we screened descriptors and developed QSAR models. For classification studies, seven machine learning methods along with six molecular fingerprints were applied to develop qualitative classification models. The goodness of fitting, reliability, robustness and predictive performance of all developed models were measured by rigorous statistical validation criteria, then the best QSAR and classification models were chosen. Moreover, the QSAR models with quantum chemistry descriptors were compared to that without quantum chemistry descriptors and previously reported models. Notably, we also obtained some specific molecular properties or privileged substructures responsible for the high mutagenicity of NACs. Overall, the developed QSAR and classification models can be utilized as potential tools for rapidly predicting the mutagenicity of new or untested NACs for environmental hazard assessment and regulatory purposes, and may provide insights into the in vivo toxicity mechanisms of NACs and related compounds.

Reductive Activity and Mechanism of Hypoxia- Targeted AGT Inhibitors: An Experimental and Theoretical Investigation.

O6-alkylguanine-DNA alkyltransferase (AGT) is the main cause of tumor cell resistance to DNA-alkylating agents, so it is valuable to design tumor-targeted AGT inhibitors with hypoxia activation. Based on the existing benchmark inhibitor O6-benzylguanine (O6-BG), four derivatives with hypoxia-reduced potential and their corresponding reduction products were synthesized. A reductase system consisting of glucose/glucose oxidase, xanthine/xanthine oxidase, and catalase were constructed, and the reduction products of the hypoxia-activated prodrugs under normoxic and hypoxic conditions were determined by high-performance liquid chromatography electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). The results showed that the reduction products produced under hypoxic conditions were significantly higher than that under normoxic condition. The amount of the reduction product yielded from ANBP (2-nitro-6-(3-amino) benzyloxypurine) under hypoxic conditions was the highest, followed by AMNBP (2-nitro-6-(3-aminomethyl)benzyloxypurine), 2-NBP (2-nitro-6-benzyloxypurine), and 3-NBG (O6-(3-nitro)benzylguanine). It should be noted that although the levels of the reduction products of 2-NBP and 3-NBG were lower than those of ANBP and AMNBP, their maximal hypoxic/normoxic ratios were higher than those of the other two prodrugs. Meanwhile, we also investigated the single electron reduction mechanism of the hypoxia-activated prodrugs using density functional theory (DFT) calculations. As a result, the reduction of the nitro group to the nitroso was proven to be a rate-limiting step. Moreover, the 2-nitro group of purine ring was more ready to be reduced than the 3-nitro group of benzyl. The energy barriers of the rate-limiting steps were 34-37 kcal/mol. The interactions between these prodrugs and nitroreductase were explored via molecular docking study, and ANBP was observed to have the highest affinity to nitroreductase, followed by AMNBP, 2-NBP, and 3-NBG. Interestingly, the theoretical results were generally in a good agreement with the experimental results. Finally, molecular docking and molecular dynamics simulations were performed to predict the AGT-inhibitory activity of the four prodrugs and their reduction products. In summary, simultaneous consideration of reduction potential and hypoxic selectivity is necessary to ensure that such prodrugs have good hypoxic tumor targeting. This study provides insights into the hypoxia-activated mechanism of nitro-substituted prodrugs as AGT inhibitors, which may contribute to reasonable design and development of novel tumor-targeted AGT inhibitors.

QSAR and Classification Study on Prediction of Acute Oral Toxicity of N-Nitroso Compounds.

To better understand the mechanism of in vivo toxicity of N-nitroso compounds (NNCs), the toxicity data of 80 NNCs related to their rat acute oral toxicity data (50% lethal dose concentration, LD50) were used to establish quantitative structure-activity relationship (QSAR) and classification models. Quantum chemistry methods calculated descriptors and Dragon descriptors were combined to describe the molecular information of all compounds. Genetic algorithm (GA) and multiple linear regression (MLR) analyses were combined to develop QSAR models. Fingerprints and machine learning methods were used to establish classification models. The quality and predictive performance of all established models were evaluated by internal and external validation techniques. The best GA-MLR-based QSAR model containing eight molecular descriptors was obtained with Q²loo = 0.7533, R² = 0.8071, Q²ext = 0.7041 and R²ext = 0.7195. The results derived from QSAR studies showed that the acute oral toxicity of NNCs mainly depends on three factors, namely, the polarizability, the ionization potential (IP) and the presence/absence and frequency of C⁻O bond. For classification studies, the best model was obtained using the MACCS keys fingerprint combined with artificial neural network (ANN) algorithm. The classification models suggested that several representative substructures, including nitrile, hetero N nonbasic, alkylchloride and amine-containing fragments are main contributors for the high toxicity of NNCs. Overall, the developed QSAR and classification models of the rat acute oral toxicity of NNCs showed satisfying predictive abilities. The results provide an insight into the understanding of the toxicity mechanism of NNCs in vivo, which might be used for a preliminary assessment of NNCs toxicity to mammals.

Insights into the Impact of Linker Flexibility and Fragment Ionization on the Design of CK2 Allosteric Inhibitors: Comparative Molecular Dynamics Simulation Studies.

Protein kinase is a novel therapeutic target for human diseases. The off-target and side effects of ATP-competitive inhibitors preclude them from the clinically relevant drugs. The compounds targeting the druggable allosteric sites outside the highly conversed ATP binding pocket have been identified as promising alternatives to overcome current barriers of ATP-competitive inhibitors. By simultaneously interacting with the αD region (new allosteric site) and sub-ATP binding pocket, the attractive compound CAM4066 was named as allosteric inhibitor of CK2α. It has been demonstrated that the rigid linker and non-ionizable substituted fragment resulted in significant decreased inhibitory activities of compounds. The molecular dynamics simulations and energy analysis revealed that the appropriate coupling between the linker and pharmacophore fragments were essential for binding of CAM4066 with CK2α. The lower flexible linker of compound 21 lost the capability of coupling fragments A and B to αD region and positive area, respectively, whereas the methyl benzoate of fragment B induced the re-orientated Pre-CAM4066 with the inappropriate polar interactions. Most importantly, the match between the optimized linker and pharmacophore fragments is the challenging work of fragment-linking based drug design. These results provide rational clues to further structural modification and development of highly potent allosteric inhibitors of CK2.

In Silico Prediction of O6-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods.

O6-methylguanine-DNA methyltransferase (MGMT), a unique DNA repair enzyme, can confer resistance to DNA anticancer alkylating agents that modify the O6-position of guanine. Thus, inhibition of MGMT activity in tumors has a great interest for cancer researchers because it can significantly improve the anticancer efficacy of such alkylating agents. In this study, we performed a quantitative structure activity relationship (QSAR) and classification study based on a total of 134 base analogs related to their ED50 values (50% inhibitory concentration) against MGMT. Molecular information of all compounds were described by quantum chemical descriptors and Dragon descriptors. Genetic algorithm (GA) and multiple linear regression (MLR) analysis were combined to develop QSAR models. Classification models were generated by seven machine-learning methods based on six types of molecular fingerprints. Performances of all developed models were assessed by internal and external validation techniques. The best QSAR model was obtained with Q²Loo = 0.83, R² = 0.87, Q²ext = 0.67, and R²ext = 0.69 based on 84 compounds. The results from QSAR studies indicated topological charge indices, polarizability, ionization potential (IP), and number of primary aromatic amines are main contributors for MGMT inhibition of base analogs. For classification studies, the accuracies of 10-fold cross-validation ranged from 0.750 to 0.885 for top ten models. The range of accuracy for the external test set ranged from 0.800 to 0.880 except for PubChem-Tree model, suggesting a satisfactory predictive ability. Three models (Ext-SVM, Ext-Tree and Graph-RF) showed high and reliable predictive accuracy for both training and external test sets. In addition, several representative substructures for characterizing MGMT inhibitors were identified by information gain and substructure frequency analysis method. Our studies might be useful for further study to design and rapidly identify potential MGMT inhibitors.

Synthesis and antitumor activity evaluation of a novel combi-nitrosourea prodrug: Designed to release a DNA cross-linking agent and an inhibitor of O(6)-alkylguanine-DNA alkyltransferase.

The drug resistance of CENUs induced by O(6)-alkylguanine-DNA alkyltransferase (AGT), which repairs the O(6)-alkylated guanine and subsequently inhibits the formation of dG-dC cross-links, hinders the application of CENU chemotherapies. Therefore, the discovery of CENU analogs with AGT inhibiting activity is a promising approach leading to novel CENU chemotherapies with high therapeutic index. In this study, a new combi-nitrosourea prodrug 3-(3-(((2-amino-9H-purin-6-yl)oxy)methyl)benzyl)-1-(2-chloroethyl)-1-nitrosourea (6), designed to release a DNA cross-linking agent and an inhibitor of AGT, was synthesized and evaluated for its antitumor activity and ability to induce DNA interstrand cross-links (ICLs). The results indicated that 6 exhibited higher cytotoxicity against mer(+) glioma cells compared with ACNU, BCNU, and their respective combinations with O(6)-benzylguanine (O(6)-BG). Quantifications of dG-dC cross-links induced by 6 were performed using HPLC-ESI-MS/MS. Higher levels of dG-dC cross-link were observed in 6-treated human glioma SF763 cells (mer(+)), whereas lower levels of dG-dC cross-link were observed in 6-treated calf thymus DNA, when compared with the groups treated with BCNU and ACNU. The results suggested that the superiority of 6 might result from the AGT inhibitory moiety, which specifically functions in cells with AGT activity. Molecular docking studies indicated that five hydrogen bonds were formed between the O(6)-BG analogs released from 6 and the five residues in the active pocket of AGT, which provided a reasonable explanation for the higher AGT-inhibitory activity of 6 than O(6)-BG.

Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking.

DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O6 position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O6-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR) study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment) were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Qcv² = 0.672 and Rncv² = 0.997) and CoMSIA (Qcv² = 0.703 and Rncv² = 0.946) models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Qext² = 0.691, Rpred² = 0.738 and slope k = 0.91) was observed with acceptable external test-set validation values rather than the CoMSIA model (Qext² = 0.307, Rpred² = 0.4 and slope k = 0.719). Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity.

BRTO assisted endoscopic Histoacryl injection in treating gastric varices with gastrorenal shunt.

AIMS: We evaluated the feasibility, efficacy and safety of a novel technique of balloon-occluded retrograde transvenous obliteration (BRTO) assisted endoscopic Histoacryl (N-buthyl-2-cyanoacrylate) injection. MATERIAL AND METHODS: A total with 11 patients were enrolled and analyzed in this single center, open-label, prospective study. Patients with high-risk gastric varices (defined as fundal varices, large GV (>5 mm), presence of a red spot, and Child-Pugh score C) and concurrent gastrorenal shunt underwent endoscopic Histoacryl injection while the gastrorenal shunt was temporarily occluded with an occlusion balloon. Feasibility, hemostatic effect, intra- and postoperative complications, and varices recurrence were evaluated. RESULTS: All procedures were successfully done per protocol. Except for one patient who underwent rescue Histoacryl injection due to residual varices, single therapy was sufficient to eliminate gastric varices in ten patients. Intra-operative hemorrhage occurred in one case and was stopped after additional Histoacryl injection. One patient was confirmed to have treatment-related fungemia. No death or major complications occurred, including ectopic embolism, worsening of hepatic and renal function, etc. No recurrence of the varices was found during a median follow-up time (mean ± SD) of 228 ± 153 days. CONCLUSIONS: BRTO assisted endoscopic Histoacryl injection is effective and safe for patients with high-risk gastric varices and concurrent gastrorenal shunt.

Increased FAT10 expression is related to poor prognosis in pancreatic ductal adenocarcinoma.

It has been reported that FAT10 plays an important role in cell proliferation. Their activity is increased in malignant cells compared to benign cells. However, the clinical and functional significance of FAT10 expression has not been characterized previously in pancreatic ductal adenocarcinoma (PDAC). The purpose of this study was to assess FAT10 expression and to explore its contribution to PDAC. Real-time quantitative PCR was performed to examine FAT10 expression in 38 pairs of fresh frozen PDAC tissues and corresponding noncancerous tissues. Using immunohistochemistry, we performed a retrospective study of the FAT10 expression levels on 134 archival PDAC paraffin-embedded samples. The relationship between FAT10 mRNA expression and clinicopathological features was analyzed by appropriate statistics. Kaplan-Meier analysis and Cox proportional hazards regression models were used to investigate the correlation between FAT10 expression and prognosis of PDAC patients. The relative mRNA expression of FAT10 was significantly higher in PDAC tissues than in adjacent noncancerous tissues (P<0.001). By immunohistochemistry, the data revealed that high FAT10 expression was significantly correlated with clinical stage (P<0.001), histological differentiation (P=0.004), and lymph node metastasis (P=0.013). Consistent with these results, we found that high expression of FAT10 was significantly correlated with poor survival in PDAC patients (P<0.001). Furthermore, Cox regression analyses showed that FAT10 expression was an independent predictor of overall survival. In conclusion, this study confirmed the overexpression of FAT10 and its association with tumor progression in PDAC. It also provided the first evidence that FAT10 expression in PDAC was an independent prognostic factor of patients, which might be a potential diagnostic and therapeutic target of PDAC.

Investigations on the effect of O(6)-benzylguanine on the formation of dG-dC interstrand cross-links induced by chloroethylnitrosoureas in human glioma cells using stable isotope dilution high-performance liquid chromatography electrospray ionization tandem mass spectrometry.

Chloroethylnitrosoureas (CENUs) are bifunctional alkylating agents widely used for the clinical treatment of cancer. They exert anticancer activity by inducing DNA interstrand cross-links (ICLs) within GC base pairs to form dG-dC cross-links. This lesion inhibits DNA double strand separation during replication and transcription and results in the apoptosis of cancer cells. However, O(6)-alkylguanine DNA alkyltransferase (AGT) repairs the DNA ICLs by removing the alkyl group at the O(6) position of either O(6)-(2-chloroethyl)deoxyguanosine (O(6)-ClEtdGuo) or N1,O(6)-ethanodeoxyguanosine (N1,O(6)-EtdGuo), which are intermediates in the formation of dG-dC cross-links. The action of AGT leads to drug resistance against CENUs. O(6)-Benzylguanine (O(6)-BG) was identified as an effective AGT inhibitor that enhances the antitumor effects of CENUs. In this study, the effect of O(6)-BG on the formation of dG-dC cross-links was investigated by treating human brain glioma SF767 cells with 1-[(4-amino-2-methyl-5-pyrimidinyl)methyl]-3-(2-chloroethyl)-3-nitrosourea (ACNU). The levels of dG-dC cross-link were determined using stable isotope dilution high-performance liquid chromatography electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). The results indicated that ACNU induced higher levels of dG-dC cross-link in SF767 cells pretreated with O(6)-BG compared to cells without O(6)-BG pretreatment. The highest dG-dC cross-linking levels were generally observed at 12 h for all drug concentration groups, a result which was consistent with cytotoxicity assay. These results provided direct evidence for the enhancement of dG-dC cross-linking levels caused by the inhibition of AGT by O(6)-BG. These data indicate that dG-dC cross-links may be developed as a biomarker for evaluating the activity of novel O(6)-BG analogues as AGT inhibitors for combination therapy with CENUs.

An α-glucan isolated from root of Isatis Indigotica, its structure and adjuvant activity.

The root of Isatis indigotica is a traditional Chinese herbal medicine. An α-glucan (IIP-A-1) was firstly isolated from the roots. In this study we elucidated the chemical structure of IIP-A-1 and determined its adjuvant activity by co-immunizing mice with H1N1 influenza virus split and recombinant hepatitis B surface antigen (HBsAg), respectively. The polysaccharide was pretreated with periodate oxidation, Smith degradation and methylation in order to analyze its structure using GC, HPGPC, FT-IR, NMR and GC-MS. The adjuvant effect was evaluated by determining the antibody titers of serum against H1N1 influenza and HBsAg using ELISA. The proliferation and TNF-α secretion of macrophages administrated with different dose of IIP-A-1 were measured in vitro. The results of this study revealed that IIP-A-1 was an α-glucan with the molecular weight of 3,600 Da. The backbone was α-(1 → 4)-D-glucan with (1 → 6) branch chain. The α-glucan could significantly enhance the immune response of mice immunized with H1N1 influenza or HBsAg in vivo and exert good dose-dependent effects on the proliferation and the TNF-α secretion of macrophages in vitro. These results supported that IIP-A-1 was expected to be an efficacious adjuvant candidate for prophylactic and therapeutic vaccines.