scholarly journals ACTIVITY OF PROPYL p-BENZOYLOXYBENZOATE AS A GLUTATHIONE S-TRANSFERASE(S) INHIBITOR: THE COMPARISON BETWEEN COMPUTATIONAL CHEMISTRY APPROACH AND EMPIRICAL OBSERVATION

2010 ◽  
Vol 6 (1) ◽  
pp. 88-93
Author(s):  
Enade Perdana Istyastono ◽  
Agnes Nora Iska Harnita ◽  
Sudibyo Martono
Keyword(s):  
Computational Chemistry ◽  
Quantitative Structure Activity Relationship ◽  
Reaction Model ◽  
Glutathione S Transferase ◽  
Qsar Study ◽  
Anticancer Compounds ◽  
Empirical Observation ◽  
Formation Reaction ◽  
Multifunctional Enzymes ◽  
The Difference

The activity of propyl p-benzoyloxybenzoate as a glutathione S-transferase(s) (GSTs) inhibitor has been examined through computational chemistry based theoretical approach and laboratory experiment. This research was related to the nature of GSTs as multifunctional enzymes, which play an important role in the detoxification of electrophilic compounds, the process of inflammation and the effectivities of anticancer compounds. Quantitative Structure-Activity Relationship (QSAR) study, which was established on curcumin and its derivatives using computational chemistry approach, was used to examine the theoretical activity of p-benzoyloxybenzoate as a GSTs inhibitor. Empirical observation on GSTs inhibition was examined using formation reaction model of GS-CNB conjugate through conjugation of 1-chloro-2,4-dinitrobenzene (CDNB) and glutathione (GSH) with GSTs (prepared from rat's liver) as catalysts. The result showed that the difference between the activities of propyl p-benzoyloxybenzoate as a GSTs inhibitor obtained from the computational chemistry approach and the empirical observation were not statistically significant at 95% level of confidence.   Keywords: Propyl p-benzoyloxybenzoate, inhibitor,  glutathione S-transferase (GSTs), QSAR

scholarly journals QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS OF CURCUMIN AND ITS DERIVATIVES AS GST INHIBITORS BASED ON COMPUTATIONAL CHEMISTRY CALCULATION

2010 ◽  
Vol 3 (3) ◽  
pp. 179-186 ◽  
Author(s):  
Enade Perdana Istyastono ◽  
Sudibyo Martono ◽  
Harno Dwi Pranowo ◽  
Iqmal Tahir
Keyword(s):  
Computational Chemistry ◽  
Linear Regression Analysis ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Equation Model ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Glutathione S Transferase ◽  
Relationship Analysis ◽  
Structure Activity

The Quantitative Structure-Activity Relationship (QSAR) study was established on curcumin and its derivatives as glutathione S-transferase(s) (GSTs) inhibitors using atomic net charges as the descriptors. The charges were resulted by semiempirical AM1 and PM3 quantum-chemical calculations using computational chemistry approach. The inhibition activity was expressed as the concentration that gave 50% inhibition of GSTs activity (IC50). The selection of the best QSAR equation models was determined by multiple linear regression analysis. This research was related to the nature of GSTs as multifunctional enzymes, which play an important role in the detoxification of electrophilic compounds, the process of inflammation and the effectivity of anticancer compounds. The result showed that AM1 semiempirical method gave better descriptor for the construction of QSAR equation model than PM3 did. The best QSAR equation model was described by : log 1/IC50 = -2,238 - 17,326 qC2' + 1,876 qC4' + 9,200 qC6' The equation was significant at 95% level with statistical parameters : n = 10, m = 3, r­ = 0,839, SE = 0,254, F = 4,764, F/Ftable = 1,001.   Keywords: QSAR analysis, curcumin, glutathione S-transferase(s) (GSTs), atomic net charge

Prediction of Lipophilicity of some Quinolone Derivatives by using Quantitative Structure- Activity Relationship

2019 ◽  
Vol 16 ◽  
Author(s):  
Meysam Shirmohammadi ◽  
Zakiyeh Bayat ◽  
Esmat Mohammadinasab
Keyword(s):  
Partition Coefficient ◽  
Principal Component ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Selection Methods ◽  
Qsar Study ◽  
Structure Activity ◽  
Descriptor Selection

: Quantitative structure activity relationship (QSAR) was used to study the partition coefficient of some quinolones and their derivatives. These molecules are broad-spectrum antibiotic pharmaceutics. First, data were divided into two categories of train and test (validation) sets using random selection method. Second, three approaches including stepwise selection (STS) (forward), genetic algorithm (GA), and simulated annealing (SA) were used to select the descriptors, with the aim of examining the effect feature selection methods. To find the relation between descriptors and partition coefficient, multiple linear regression (MLR), principal component regression (PCR) and partial least squares (PLS) were used. QSAR study showed that the both regression and descriptor selection methods have vital role in the results. Different statistical metrics showed that the MLR-SA approach with (r2=0.96, q2=0.91, pred_r2=0.95) gives the best outcome. The proposed expression by MLR-SA approach can be used in the better design of novel quinolones and their derivatives.

Action of Thioglycosides of 1,2,4-Triazoles and Imidazoles on the Oxidative Stress and Glycosidases in Mice with Molecular Docking

2019 ◽  
Vol 16 (6) ◽  
pp. 696-710
Author(s):  
Mahmoud Balbaa ◽  
Doaa Awad ◽  
Ahmad Abd Elaal ◽  
Shimaa Mahsoub ◽  
Mayssaa Moharram ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Molecular Docking ◽  
Active Sites ◽  
Biological Activities ◽  
Imidazole Ring ◽  
Quantitative Structure Activity Relationship ◽  
Binding Interaction ◽  
Qsar Study

Background: ,2,3-Triazoles and imidazoles are important five-membered heterocyclic scaffolds due to their extensive biological activities. These products have been an area of growing interest to many researchers around the world because of their enormous pharmaceutical scope. Methods: The in vivo and in vitro enzyme inhibition of some thioglycosides encompassing 1,2,4- triazole N1, N2, and N3 and/or imidazole moieties N4, N5, and N6. The effect on the antioxidant enzymes (superoxide dismutase, glutathione S-transferase, glutathione peroxidase and catalase) was investigated as well as their effect on α-glucosidase and β-glucuronidase. Molecular docking studies were carried out to investigate the mode of the binding interaction of the compounds with α- glucosidase and β -glucuronidase. In addition, quantitative structure-activity relationship (QSAR) investigation was applied to find out the correlation between toxicity and physicochemical properties. Results: The decrease of the antioxidant status was revealed by the in vivo effect of the tested compounds. Furthermore, the in vivo and in vitro inhibitory effects of the tested compounds were clearly pronounced on α-glucosidase, but not β-glucuronidase. The IC50 and Ki values revealed that the thioglycoside - based 1,2,4-triazole N3 possesses a high inhibitory action. In addition, the in vitro studies demonstrated that the whole tested 1,2,4-triazole are potent inhibitors with a Ki magnitude of 10-6 and exhibited a competitive type inhibition. On the other hand, the thioglycosides - based imidazole ring showed an antioxidant activity and exerted a slight in vivo stimulation of α-glucosidase and β- glucuronidase. Molecular docking proved that the compounds exhibited binding affinity with the active sites of α -glucosidase and β-glucuronidase (docking score ranged from -2.320 to -4.370 kcal/mol). Furthermore, QSAR study revealed that the HBD and RB were found to have an overall significant correlation with the toxicity. Conclusion: These data suggest that the inhibition of α-glucosidase is accompanied by an oxidative stress action.

Antioxidant Enzyme Levels Inversely Covary with Hearing Loss After Amikacin Treatment

2003 ◽  
Vol 14 (03) ◽  
pp. 134-143 ◽  
Author(s):  
James J. Klemens ◽  
Robert P. Meech ◽  
Larry F. Hughes ◽  
Satu Somani ◽  
Kathleen C.M. Campbell
Keyword(s):  
Hearing Loss ◽  
Enzyme Activity ◽  
Antioxidant Enzyme ◽  
Guinea Pigs ◽  
Auditory Brainstem ◽  
Antioxidant Enzyme Activity ◽  
Control Group ◽  
Glutathione S Transferase ◽  
Brainstem Response ◽  
The Difference

This study's purpose was to determine if a correlation exists between cochlear antioxidant activity changes and auditory function after induction of aminoglycoside (AG) ototoxicity. Two groups of five 250-350 g albino guinea pigs served as subjects. For 28 days, albino guinea pigs were administered either 200 mg/kg/day amikacin, or saline subcutaneously. Auditory brainstem response testing was performed prior to the first injection and again before sacrifice, 28 days later. Cochleae were harvested and superoxide dismutase, catalase, glutathione peroxidase, glutathione-S-transferase, glutathione reductase activities and malondialdehyde levels were measured. All antioxidant enzymes had significantly lower activity in the amikacin group (p ≤ 0.05) than in the control group. The difference in cochlear antioxidant enzyme activity between groups inversely correlated significantly with the change in ABR thresholds. The greatest correlation was for the high frequencies, which are most affected by aminoglycosides. This study demonstrates that antioxidant enzyme activity and amikacin-induced hearing loss significantly covary.

scholarly journals A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Li Wen ◽  
Qing Li ◽  
Wei Li ◽  
Qiao Cai ◽  
Yong-Ming Cai
Keyword(s):  
Standard Deviation ◽  
Correlation Coefficient ◽  
Nonlinear Models ◽  
Predictive Ability ◽  
Quantitative Structure Activity Relationship ◽  
Support Vector ◽  
Qsar Study ◽  
Stability Robustness ◽  
Qsar Models ◽  
Leave One Out

Hydroxyl benzoic esters are preservative, being widely used in food, medicine, and cosmetics. To explore the relationship between the molecular structure and antibacterial activity of these compounds and predict the compounds with similar structures, Quantitative Structure-Activity Relationship (QSAR) models of 25 kinds of hydroxyl benzoic esters with the quantum chemical parameters and molecular connectivity indexes are built based on support vector machine (SVM) by using R language. The External Standard Deviation Error of Prediction (SDEPext), fitting correlation coefficient (R2), and leave-one-out cross-validation (Q2LOO) are used to value the reliability, stability, and predictive ability of models. The results show that R2 and Q2LOO of 4 kinds of nonlinear models are more than 0.6 and SDEPext is 0.213, 0.222, 0.189, and 0.218, respectively. Compared with the multiple linear regression (MLR) model (R2=0.421, RSD = 0.260), the correlation coefficient and the standard deviation are both better than MLR. The reliability, stability, robustness, and external predictive ability of models are good, particularly of the model of linear kernel function and eps-regression type. This model can predict the antimicrobial activity of the compounds with similar structure in the applicability domain.

scholarly journals Structural Alerts for Predicting Clastogenic Activity of Pro-oxidant Flavonoid Compounds

2011 ◽  
Vol 17 (2) ◽  
pp. 216-224 ◽  
Author(s):  
Estela Guardado Yordi ◽  
Enrique Molina Pérez ◽  
Maria Joao Matos ◽  
Eugenio Uriarte Villares
Keyword(s):  
Molecular Design ◽  
Biological Effects ◽  
Screening Method ◽  
Automatic Generation ◽  
Quantitative Structure Activity Relationship ◽  
Hydroxyl Group ◽  
Hydroxyl Groups ◽  
Qsar Study ◽  
Molecular Features ◽  
Structural Alerts

Flavonoids have been reported to exert multiple biological effects that include acting as pro-oxidants at very high doses. The authors determined a structural alert to identify the clastogenic activity of a series of flavonoids with pro-oxidant activity. The methodology was based on a quantitative structure–activity relationship (QSAR) study. Specifically, the authors developed a virtual screening method for a clastogenic model using the topological substructural molecular design (TOPS-MODE) approach. It represents a useful platform for the automatic generation of structural alerts, based on the calculation of spectral moments of molecular bond matrices appropriately weighted, taking into account the hydrophobic, electronic, and steric molecular features. Therefore, it was possible to establish the structural criteria for maximal clastogenicity of pro-oxidant flavonoids: the presence of a 3-hydroxyl group and a 4-carbonyl group in ring C, the maximal number of hydroxyl groups in ring B, the presence of methoxyl and phenyl groups, the absence of a 2,3-double bond in ring C, and the presence of 5,7 hydroxyl groups in ring A. The presented clastogenic model may be useful for screening new pro-oxidant compounds. This alert could help in the design of new and efficient flavonoids, which could be used as bioactive compounds in nutraceuticals and functional food.

scholarly journals 2D-QSAR Study of Indolylpyrimidines Derivative as Antibacterial against Pseudomonas aeruginosa and Staphylococcus aureus: A Comparative Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Prasanna A. Datar
Keyword(s):  
Staphylococcus Aureus ◽  
Pseudomonas Aeruginosa ◽  
Qsar Model ◽  
Antibacterial Activities ◽  
Quantitative Structure Activity Relationship ◽  
Comparative Approach ◽  
Qsar Study ◽  
Qsar Analysis ◽  
Leave One Out ◽  
And Staphylococcus Aureus

A set of 15 indolylpyrimidine derivatives with their antibacterial activities in terms of minimum inhibitory concentration against the gram-negative bacteria Pseudomonas aeruginosa and gram-positive Staphylococcus aureus were selected for 2D quantitative structure activity relationship (QSAR) analysis. QSAR was performed using a combination of various descriptors such as steric, electronic and topological. Stepwise regression method was used to derive the most significant QSAR equation for predicting the inhibitory activity of this class of molecules. The best QSAR model was further validated by a leave one out technique as well as by the random trials. A high correlation between experimental and predicted inhibitory values was observed. A comparative picture of behavior of indolylpyrimidines against both of the microorganisms is discussed.

scholarly journals QSAR Study of N-Myristoyltransferase Inhibitors of Antimalarial Agents

Molecules ◽  
2018 ◽  
Vol 23 (9) ◽  
pp. 2348 ◽  
Author(s):  
Letícia Santos-Garcia ◽  
Marco de Mecenas Filho ◽  
Kamil Musilek ◽  
Kamil Kuca ◽  
Teodorico Ramalho ◽  
...  
Keyword(s):  
Quantitative Structure Activity Relationship ◽  
New Drugs ◽  
Protozoan Parasites ◽  
Training Set ◽  
First Line ◽  
Qsar Study ◽  
Antimalarial Agents ◽  
Genus Plasmodium ◽  
Qsar Models ◽  
Test Sets

Malaria is a disease caused by protozoan parasites of the genus Plasmodium that affects millions of people worldwide. In recent years there have been parasite resistances to several drugs, including the first-line antimalarial treatment. With the aim of proposing new drugs candidates for the treatment of disease, Quantitative Structure–Activity Relationship (QSAR) methodology was applied to 83 N-myristoyltransferase inhibitors, synthesized by Leatherbarrow et al. The QSAR models were developed using 63 compounds, the training set, and externally validated using 20 compounds, the test set. Ten different alignments for the two test sets were tested and the models were generated by the technique that combines genetic algorithms and partial least squares. The best model shows r2 = 0.757, q2adjusted = 0.634, R2pred = 0.746, R2m = 0.716, ∆R2m = 0.133, R2p = 0.609, and R2r = 0.110. This work suggested a good correlation with the experimental results and allows the design of new potent N-myristoyltransferase inhibitors.

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