Deep neural network and molecular docking supported toxicity profile of prometryn

Investigation of multidirectional toxicity induced by high-dose molybdenum exposure with Allium test

In this study, the multifaceted toxicity induced by high doses of the essential trace element molybdenum in Allium cepa L. was investigated. Germination, root elongation, weight gain, mitotic index (MI), micronucleus (MN), chromosomal abnormalities (CAs), Comet assay, malondialdehyde (MDA), proline, superoxide dismutase (SOD), catalase (CAT) and anatomical parameters were used as biomarkers of toxicity. In addition, detailed correlation and PCA analyzes were performed for all parameters discussed. On the other hand, this study focused on the development of a two hidden layer deep neural network (DNN) using Matlab. Four experimental groups were designed: control group bulbs were germinated in tap water and application group bulbs were germinated with 1000, 2000 and 4000 mg/L doses of molybdenum for 72 h. After germination, root tips were collected and prepared for analysis. As a result, molybdenum exposure caused a dose-dependent decrease (p < 0.05) in the investigated physiological parameter values, and an increase (p < 0.05) in the cytogenetic (except MI) and biochemical parameter values. Molybdenum exposure induced different types of CAs and various anatomical damages in root meristem cells. Comet assay results showed that the severity of DNA damage increased depending on the increasing molybdenum dose. Detailed correlation and PCA analysis results determined significant positive and negative interactions between the investigated parameters and confirmed the relationships of these parameters with molybdenum doses. It has been found that the DNN model is in close agreement with the actual data showing the accuracy of the predictions. MAE, MAPE, RMSE and R2 were used to evaluate the effectiveness of the DNN model. Collective analysis of these metrics showed that the DNN model performed well. As a result, it has been determined once again that high doses of molybdenum cause multiple toxicity in A. cepa and the Allium test is a reliable universal test for determining this toxicity. Therefore, periodic measurement of molybdenum levels in agricultural soils should be the first priority in preventing molybdenum toxicity.

LC-MS/MS, GC-MS and molecular docking analysis for phytochemical fingerprint and bioactivity of Beta vulgaris L

The plants that we consume in our daily diet and use as a risk preventer against many diseases have many biological and pharmacological activities. In this study, the phytochemical fingerprint and biological activities of Beta vulgaris L. leaf extract, which are widely consumed in the Black Sea region, were investigated. The leaf parts of the plant were dried in an oven at 35 °C and then ground into powder. The main constituents in B. vulgaris were identified by LC-MS/MS and GC-MS analyses. Phenolic content, betaxanthin and betacyanin levels were investigated in the extracts obtained using three different solvents. The biological activity of the extract was investigated by anti-microbial, anti-mutagenic, anti-proliferative and anti-diabetic activity tests. Anti-diabetic activity was investigated by in vitro enzyme inhibition and in-silico molecular docking was performed to confirm this activity. In the LC-MS analysis of B. vulgaris extract, a major proportion of p_coumaric acid, vannilin, protecatechuic aldehyde and sesamol were detected, while the major essential oils determined by GC-MS analysis were hexahydrofarnesyl acetone and phytol. Among the solvents used, the highest extraction efficiency of 2.4% was obtained in methanol extraction, and 36.2 mg of GAE/g phenolic substance, 5.1 mg/L betacyanin and 4.05 mg/L betaxanthin were determined in the methanol extract. Beta vulgaris, which exhibited broad-spectrum anti-microbial activity by forming a zone of inhibition against all tested bacteria, exhibited anti-mutagenic activity in the range of 35.9-61.8% against various chromosomal abnormalities. Beta vulgaris extract, which did not exhibit mutagenic, sub-lethal or lethal effects, exhibited anti-proliferative activity by reducing proliferation in Allium root tip cells by 21.7%. 50 mg/mL B. vulgaris extract caused 58.9% and 55.9% inhibition of α-amylase and α-glucosidase activity, respectively. The interactions of coumaric acid, vanniline, hexahydrofarnesyl acetone and phytol, which are major compounds in phytochemical content, with α-amylase and α-glucosidase were investigated by in silico molecular docking and interactions between molecules via various amino acids were determined. Binding energies between the tested compounds and α-amylase were obtained in the range of - 4.3 kcal/mol and - 6.1 kcal/mol, while for α-glucosidase it was obtained in the range of - 3.7 kcal/mol and - 5.7 kcal/mol. The biological activities of B. vulgaris are closely related to the active compounds it contains, and therefore studies investigating the phytochemical contents of plants are very important. Safe and non-toxic plant extracts can help reduce the risk of various diseases, such as diabetes, and serve as an alternative or complement to current pharmaceutical practices.

In-vivo and in-silico studies to identify toxicity mechanisms of permethrin with the toxicity-reducing role of ginger

In this study, the toxic effects of permethrin on Allium cepa L. and the protective role of Zingiber officinale rhizome extract (Zoex) were investigated. In this context, 6 different groups were formed. While the control group was treated with tap water, the groups II and III were treated with 10 µg/mL and 20 µg/mL Zoex, respectively, and the group IV was treated with 100 µg/L permethrin. The protective effect of Zoex against permethrin toxicity was studied as a function of dose, and groups V and VI formed for this purpose were treated with 10 µg/mL Zoex + 100 µg/L permethrin and 20 µg/mL Zoex + 100 µg/L permethrin, respectively. After 72 h of germination, cytogenetic, biochemical, physiological, and anatomical changes in meristematic cells of A. cepa were studied. As a result, permethrin application decreased the mitotic index (MI) and increased the frequency of micronuclei (MN), and chromosomal abnormalities. The increase in malondialdehyde (MDA), superoxide dismutase (SOD), and catalase (CAT) and the decrease in glutathione (GSH) indicate that permethrin causes oxidative damage. Compared to the control group, a 68.5% decrease in root elongation (p < 0.05) and an 81.8% decrease (p < 0.05) in weight gain were observed in the permethrin-treated group. It was found that the application of Zoex together with permethrin resulted in regression of all detected abnormalities, reduction in the incidence of anatomical damage, MN and chromosomal aberrations, and improvement in MI rates. The most significant improvement was observed in group VI treated with 20 µg/mL Zoex, and Zoex was also found to provide dose-dependent protection. The toxicity mechanism of permethrin was also elucidated by molecular docking and spectral studies. From the data obtained during the study, it was found that permethrin has toxic effects on A. cepa, a non-target organism, while Zoex plays a protective role by reducing these effects.

In silico interactions and deep neural network modeling for toxicity profile of methyl methanesulfonate

In this study, the toxicity induced by the alkylating agent methyl methanesulfonate (MMS) in Allium cepa L. was investigated. For this aim, bulbs were divided into 4 groups as control and application (100, 500 and 4000 µM MMS) and germinated for 72 h at 22-24 °C. At the end of the germination period root tips were collected and made ready for analysis by applying traditional preparation methods. Germination, root elongation, weight, mitotic index (MI) values, micronucleus (MN) and chromosomal abnormality (CAs) numbers, malondialdehyde (MDA) levels, superoxide dismutase (SOD) and catalase (CAT) activities and anatomical structures of bulbs were used as indicators to determine toxicity. Moreover the extent of DNA fragmentation induced by MMS was determined by comet assay. To confirm the DNA fragmentation induced by MMS, the DNA-MMS interaction was examined with molecular docking. Correlation and principal component analyses (PCA) were performed to examine the relationship between all parameters and understand the underlying structure and relationships among these parameters. In the present study, a deep neural network (DNN) with two hidden layers implemented in Matlab has been developed for the comparison of the estimated data with the real data. The effect of MDA levels, SOD and CAT activities at 4 different endpoints resulting from administration of various concentrations of MMS, including MN, MI, CAs and DNA damage, was attempted to be estimated by DNN model. It is assumed that the predicted results are in close agreement with the actual data. The effectiveness of the model was evaluated using 4 different metrics, MAE, MAPE, RMSE and R2, which together show that the model performs commendably. As a result, the highest germination, root elongation, weight gain and MI were measured in the control group. MMS application caused a decrease in all physiological parameters and an increase in cytogenetic (except MI) and biochemical parameters. MMS application caused an increase in antioxidant enzyme levels (SOD and CAT) up to a concentration of 500 µM and a decrease at 4000 µM. MMS application induced different types of CAs and anatomical damages in root meristem cells. The results of the comet assay showed that the severity of DNA fragmentation increased with increasing MMS concentration. Molecular docking analysis showed a strong DNA-MMS interaction. The results of correlation and PCA revealed significant positive and negative interactions between the studied parameters and confirmed the interactions of these parameters with MMS. It has been shown that the DNN model developed in this study is a valuable resource for predicting genotoxicity due to oxidative stress and lipid peroxidation. In addition, this model has the potential to help evaluate the genotoxicity status of various chemical compounds. At the end of the study, it was concluded that MMS strongly supports a versatile toxicity in plant cells and the selected parameters are suitable indicators for determining this toxicity.