Differential modulation of Bax/Bcl-2 ratio and onset of caspase-3/7 activation induced by derivatives of Justicidin B in human melanoma cells A375

Alqathama, Aljawharah; Gibbons, Simon; Prieto, José M.

doi:10.18632/oncotarget.21625

Cited by 19 publications

(13 citation statements)

References 30 publications

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“…When Bcl-2 is relatively predominant in cells, Bcl-2 will form a heterodimer with Bax, thus inhibiting apoptosis. However, when Bax is predominant in cells, Bax itself will form the homodimer, thus promoting apoptosis (16,17). Therefore, the Bax/Bcl-2 ratio has important significance for the occurrence and degree of apoptosis.…”

Section: Discussionmentioning

confidence: 99%

Puerarin in inducing apoptosis of bladder cancer cells through inhibiting SIRT1/p53 pathway

Kan

Chen

et al. 2018

Oncol Lett

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Regulatory effect of puerarin on bladder cancer T24-cell apoptosis and its possible mechanism were investigated. The experimental subjects were divided into the experimental group, the control group and the blank control group, and the cell inhibition rates after treatment were detected, respectively. Then, subjects were further divided into the control group, the puerarin group (treated with puerarin), the agonist group [treated with silent information regulator 1 (SIRT1) agonist SRT1720], the inhibitor group (treated with SIRT1 inhibitor EX527) and the combination group (treated with SRT1720, and then with puerarin). Apoptosis in each group was detected via flow cytometry, and the expression of apoptosis-related proteins, and SIRT1 and p53 proteins in each group was detected via western blotting. Moreover, the expression of SIRT1 and p53 messenger ribonucleic acid (mRNA) was detected via reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The inhibition rate of bladder cancer T24 cells was significantly increased after treatment with puerarin at different concentrations. Compared with those in the normal control group, the inhibition rates at 24, 48 and 72 h after treatment with puerarin were significantly increased (p<0.05). Compared with those in the control group, the apoptosis rate of T24 cells was remarkably increased after treatment with different doses of puerarin or EX527, and the expression level of apoptosis-related protein Bcl-2-associated X protein (Bax) was also significantly increased, but the expression level of B-cell lymphoma 2 (Bcl-2) was decreased, and both the protein and mRNA expression levels of SIRT1 and p53 also significantly declined. Compared with those in the puerarin group, the apoptosis rate in the combination group was decreased, and the expression level of apoptosis-related protein Bax was also significantly decreased, but the expression level of Bcl-2 was increased, and SIRT1 and p53 protein expression levels were also remarkably increased. Puerarin can inhibit the proliferation of bladder cancer T24 cells and induce apoptosis, and the possible mechanism is related to the inhibition of SIRT1/p53 signaling pathway.

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Section: Discussionmentioning

confidence: 99%

Puerarin in inducing apoptosis of bladder cancer cells through inhibiting SIRT1/p53 pathway

Kan

Chen

et al. 2018

Oncol Lett

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“…Additionally, the high value and closeness of cross-validated regression-coefficient (Q 2 cv ) to the regression-coefficient (R 2 ) showed that the model was not over-fitted. The high R 2 pred as shown in the model explains that the generated model can provide good and valid predictions for the new compounds. A good and acceptable QSAR model must obey the following criteria: regression-coefficient (R 2 ) and adjusted regression-coefficient (R 2 adj) values close to one.…”

Section: Qsar Model and Validationmentioning

confidence: 85%

“…The coefficient of determination cR 2 p for Y-randomization is another parameter calculated which should be greater than 0.5 for passing this test as in Eq. (6): cR 2 p is Coefficient of determination for Y-randomization, R is the coefficient of determination for Y-randomization and R r is average 'R' of random models.…”

Section: Qsar Model Development and Validationmentioning

confidence: 99%

“…SK-MEL-5 is a human melanoma cell line derived from a metastatic axillary node of a young female patient, and is characterized by a high level of expression of the V600E mutation of BRAF and the wild-type NRAS [1], as well as by relatively high levels of the ABCB1 transcript [2]. It has been used in various studies to explore new therapies against melanoma in various in vitro experiments [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Design of potential anti-melanoma agents against SK-MEL-5 cell line using QSAR modeling and molecular docking methods

2020

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SK-MEL-5 is a human melanoma cell line that has been used in several researches to explore new therapies against melanoma. Based on this study we report on the development of quantitative structure-activity relationship (QSAR) model and molecular docking simulation able to predict the cytotoxic effect of diverse chemical compounds on this cancer cell line. The dataset of seventy-two (72) cytotoxic compounds were downloaded from the National Cancer Institute database. It contains the data of compounds for which cytotoxicity results expressed by pGI 50 was recorded. The QSAR model was built using fifty (50) compounds and the best-generated model based on multiple linear regression showed, respectively good quality of fits [ R 2 (0.864), R 2 adjusted (0.846), Q 2 cv (0.841) and R 2 pred (0.885)]. The model's predictive ability was determined by a test set of twenty-two (22) compounds and the applicability domain was assessed through leveraged approach. Compounds 41 and 69 were selected as templates for in silico design because they had high pGI 50 activity and are within the model's applicability domain. The obtained information from the model was explored to design novel compounds by introducing various substituents. Moreover, the designed compounds were docked into the active site of the protein (PDB CODE: 3OG7) which is responsible for melanoma cancer to elucidate their binding mode. Ia (− 12.4 kcal mol −1) and IIb (− 12.3 kcal mol −1) showed a better binding affinity for the target when compared with (vemurafenib, − 11.3 kcal mol −1) the known inhibitor of the target (V600E-BRAF). These results may be of great help in early anticancer drug discovery.

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“…Therefore, although therapeutic options are now better for patients with advanced melanoma than they were a decade ago, there is still a need for developing new drugs targeting melanoma, and a variety of approaches are still explored, from evaluating new targets (11) to exploring new delivery systems for old compounds (12). SK-MEL-5 is a human melanoma cell line derived from a metastatic axillary node of a young female patient, and is characterized by a high level of expression of the V600E mutation of B-Raf, of the wild-type N-Ras (13), as well as by relatively high levels of the ABCB1 transcript (14). This is unlike SK-MEL-2 melanoma cell line, which has wild-type B-Raf, but normal N-Ras (11).…”

Section: Introductionmentioning

confidence: 99%

Development of QSAR machine learning-based models to forecast the effect of substances on malignant melanoma cells

et al. 2019

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SK-MEL-5 is a human melanoma cell line that has been used in various studies to explore new therapies against melanoma in different in vitro experiments. Based on this study we report on the development of quantitative structure-activity relationship (QSAR) models able to predict the cytotoxic effect of diverse chemical compounds on this cancer cell line. The dataset of cytotoxic and inactive compounds were downloaded from the PubChem database. It contains the data for all chemical compounds for which cytotoxicity results expressed by GI 50 was recorded. In total 13 blocks of molecular descriptors were computed and used, after appropriate pre-processing in building QSAR models with four machine learning classifiers: Random forest (RF), gradient boosting, support vector machine and random k-nearest neighbors. Among the 186 models reported none had a positive predictive value (PPV) higher than 0.90 in both nested cross-validation and on an external dataset testing, but 7 models had a PPV higher than 0.85 in both evaluations, all seven using the RFs algorithm as a classifier, and topological descriptors, information indices, 2D-autocorrelation descriptors, P-VSA-like descriptors, and edge-adjacency descriptors as sets of features used for classification. The y-scrambling test was associated with considerably worse performance (confirming the non-random character of the models) and the applicability domain was assessed through three different methods.

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Differential modulation of Bax/Bcl-2 ratio and onset of caspase-3/7 activation induced by derivatives of Justicidin B in human melanoma cells A375

Cited by 19 publications

References 30 publications

Puerarin in inducing apoptosis of bladder cancer cells through inhibiting SIRT1/p53 pathway

Puerarin in inducing apoptosis of bladder cancer cells through inhibiting SIRT1/p53 pathway

Design of potential anti-melanoma agents against SK-MEL-5 cell line using QSAR modeling and molecular docking methods

Development of QSAR machine learning-based models to forecast the effect of substances on malignant melanoma cells

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